· Information and Orders: Publisher : Bank Indonesia Jl. MH Thamrin No.2, Jakarta Indonesia This...

No. 29, September 2017FINANCIAL STABILITY REVIEW

FINA

NC

IAL STA

BILITY REV

IEW

MACROPRUDENTIAL POLICY DEPARTMENT

No

. 29, Septem

ber 2017

Maintaining Financial System Stabilty Stimulating the Economy

Information and Orders:

Publisher :Bank Indonesia

Jl. MH Thamrin No.2, Jakarta

Indonesia

This edition is published in September 2017 dan didasarkan pada data dan informasi per and is based on

data and information available as of Juni 2017, unless stated otherwise.

The PDF format is downloaded from

https://www.bi.go.id

Source : Bank Indonesia, unless stated otherwise.

For inquiries, comment and feedback please contact :Bank Indonesia

Departemen Kebijakan Makroprudensial

Jl. MH Thamrin No.2, Jakarta, Indonesia

Email : [email protected]

The preparation of the Financial Stability Review is one of the avenues through which

Bank Indoensia achieves its mission ”to safeguard the stability of the Indonesian Rupiah by maintaining

monetary and financial system stability for sustainable national economic development”

FSR is published biannually with the objectives :

• To improve public insight in terms of understanding financial system stability

• To evaluate protential risks to financial system stability

• To analyze the developments of and issues within the financial system

• To offer policy recommendations to promote and maintain financial system stabilty


Director Erwin Rijanto - Filianingsih Hendarta - Linda Maulidina - Farida Peranginangin

Coordinator and Editor Rozidyanti – Theresia Silitonga - Agus Fadjar Setiawan - Riza Putera – Agung Bayu Purwoko

Drafting Team Retno Ponco Windarti, M. Firdaus Muttaqin, Kurniawan Agung, Ita Rulina, Indra Gunawan, Ndari

Suryaningsih, Cicilia A. Harun, Sri Noerhidajati, Mirza Yuniar, Januar Hafidz, Viana Sari, Khairani

Syafitri, Bayu Adi Gunawan, Susana Wibisana, Heny Sulistyaningsih, Hero Wonida, Vienella

Zarmida, Lisa Rienellda, Arifatul Khorida, Zulfia Fathma, Anita, Sagita Rachmanira, Astrid Fiona

H., Annisaa Prima Astuti, Maulana Harris Muhajir, Ibrahim Adrian Nugroho, Anindhita Kemala D,

Apsari Anindita N.P, Rani Wijayanti, Harris Dwi Putra, Pita Pratita, Vergina Hapsari, Ardo Prayoga,

Kartina Eka Darmawanti, Aski Catranti, Saraswati, Prayudhi Azwar, Mario Simatupang, Noviati,

Rakhma Fatmaningrum, Tri Siwi Permadi Astuti, Fransiskus Xaverius Tyas Prasaja, Martha K. Pratiwi,

Muhammad Adrianto Eko Budhi Setiyanto, Donny Ananta, Lely Yudha Prasetyaningsih,Taufik

Saleh, I Gede Arnawa.

Translated by Matthew Burrows.

OTHER DEPARTMENT CONTRIBUTION ON SELECTED ANALYSIS Economic and Monetary Policy Department

Financial System Surveillance Department

SME Development Department

Islamic Economics and Finance Department

Statistics Department

Financial Market Development Department

Payment System Policy and Oversight Department

Payment System Management Department

East Java Representative Office Bank Indonesia

PRODUCTION AND DISSEMINATION TEAM Saprudin, Elsa Puspa Silfia, I Made Yogi


“Maintaining Financial System StabiltyStimulating the Economy”

FINANCIAL STABILITY REVIEWNo. 29, September 2017

II BANK INDONESIA

1. Financial System Stability1.1. Risks in the Global and Regional Financial Markets

1.2. Domestic Economic Risks

1.3. Financial System Stability

1.4. Domestic Financial Imbalances

Boks 1.1. Bank Indonesia Systemic Risk Survey in the First Semester of 2017

Boks 1.2. International Recognition of Successful Financial Sector Reforms in Indonesia

according to FASP 2016/2017

Boks 1.3. Tax Amnesty Realisation

2. The Financial Markets2.1. Role of the Financial Markets as a Source of Economic Financing

2.2. Financial Market Dynamics and Risk

2.3. Islamic Financial Market Dynamics and Risks

Boks 2.1. The National Financial Market Development Strategy (SN-PPK)

Boks 2.2. Regulating Treasury Certification and Implementing a Market Code of Conduct

3. Households and Corporations3.1. Household Sector

3.2. Corporate Sector

Boks 3.1. Steel Industry Performance in East Java

4. Banks and Nonbank Financial Institutions4.1. Banking Sector Dynamics and Risks

4.2. Nonbank Financial Industry

4.3. Islamic Banking Sector Dynamics and Risks

Boks 4.1. Seasonal Liquidity Trends during Eid-ul-Fitr

Boks 4.2. Correlation Analysis of Bank Deposits with Expansion of the Government’s Expenditure

Budget in East Java

3

5

8

11

18

22

25

31

35

49

57

60

67

74

87

96

128

138

151

154

1

28

64

92

Foreword

Executive Summary

XIV

XVIII

CONTENTS

IIIBANK INDONESIA

ArticleArticle 1. The Impact of Domestic Government Financing on Deposits in the Banking Industry

Article 2. The Impact of Interconnectedness in the Interbank Money Market

on Banking Industry Efficiency in Indonesia204

218

6. Bank Indonesia’s Policy Response Backing Financial System Stability6.1. Refining the Short-Term Liquidity Loans

6.2. Maintaining the Countercyclical Capital Buffer (CCyB) at 0%

6.3. Assessment of the RR-Loan to Funding Ratio (RR-LFR)

6.4. Assessment of the Loan-to-Value (LTV) and Financing-to-Value (FTV) Ratios for Property

Loans/Financing and Downpayments on Automotive Loans

6.5. Policy Coordination between Bank Indonesia and Other Relevant Authorities

Boks 6.1. Average Reserve Requirement Ratios

Boks 6.2. Innovative Islamic Financial Instruments: Awqaf-Linked Sukuk

181

183

187

189

194

199

200

178

5. Financial System Infrastructure5.1. Payment System Performance

5.2. Payment System Transactions

5.3. Payment System Indicators

5.4. Payment System Risks and Mitigation Efforts

5.5. Financial Inclusion and Digital Financial Services

Box 5.1. Unlicensed Nonbank Money Changers

160163

165

167

168

170

176


IV BANK INDONESIA

LIST OF TABLE

1. Financial System StabilityTable 1.1 Global Economic Outlook 4

Table 1.2 National Economic Growth in Indonesia 5

Box Table 1.1.1. Respondent Recapitulation 18

2. The Financial MarketsTable 2.1. Bank and Nonbank Financing (Rp, trillions) 31

Table 2.2. Sources of Funds by Bank Total 33

Table 2.3. Sources of Bank Funds by Volume 34

Table 2.4. Comparison of Average NDF Spreads in

Neighbouring Countries

40

Table 2.5. Composition of SBN Holdings (%) 40

Table 2.6. Regional 10-Year SBN Yields 42

Table 2.7. Regional 10-Year SBN Yield Volatility 42

Table 2.8. Corporate Bond Holdings 43

Table 2.9. Sectoral Index Volatility (Semester Average) 46

Table 2.10. Distribution of the Islamic Securities List 50

3. Households and CorporationsTable 3.1. DSR Composition by Monthly Income 70

Table 3.2. Composition of Savings by Monthly Income 70

Table 3.3. Household Sector Credit by Loan Type 73

Table 3.4. Financial Performance Indicators of Non-

Financial Corporations

76

Table 3.5. Financial Performance Indicators of Major

Commodity-Based Corporations

78

Table 3.6. Corporate Loans by Economic Sector 81

Table 3.7. Credit Based on Main Export Commodities 81

Table 3.8 Restructured External Debt by Economic

Sector

85

Table 3.9. Types of Positive and Negative Tone

External Debt Restructuration

86

Box Table 3.1.1. Trend and Share of Loan Disbursements by

Sector

88

4. Banks and Nonbank Financial Institutions

Table 4.1. LA/NCD by BUKU Bank Group 97

Table 4.2. Growth of Liquid Assets 97

Table 4.3. Loan-to-Deposit Ratio (LDR) by BUKU Bank

Group

98

Table 4.4. Market Share of Deposits based on

Maturity

99

Table 4.5. Deposit Growth by BUKU Bank Group (%,

yoy)

100

Table 4.6. Receipts of Tax Amnesty Funds by BUKU

Bank Group

100

Table 4.7. Deposit Share by Island 102

Table 4.8. GDP growth by Economic Sector 103

Table 4.9. Market Share of Credit by Project Location 104

Table 4.10. Credit Growth by BUKU Bank Group (%,

yoy)

105

Table 4.11. MSME Credit Growth and Share by BUKU

Bank Group

107

Table 4.12. Gross NPL by Region 111

Table 4.13. Gross NPL Ratio by BUKU Bank Group 111

Table 4.14. Share of Restructured Loans to Total Credit 112

Table 4.15. Deposit Rates by BUKU Bank Group 115

Table 4.16. Lending Rates by BUKU Bank Group 115

Table 4.17. Value of SBN Holdings by Bank Group 118

Table 4.18. Share of SBN Holdings by Bank Group 118

Table 4.19 Banking Industry Profit/Loss (Rp, trillions) 122

Table 4.20. Breakdown of Income (Rp, trillions) 122

Table 4.21. Breakdown of Expenses (Rp, trillions) 123

Table 4.22. CAR Performance by BUKU Bank Group 125

Table 4.23. Interconnectedness between the Banking

Industry and Finance Companies

133

Table 4.24. Investment Ratio by Insurance Type 135

Table 4.25. Insurance Industry Assets and Financial

Performance

135

Table 4.26. Interconnectedness between the Banking

and Insurance Industries

137

VBANK INDONESIA

Table 4.27. Risk-Based Capital of Public Listed Insurance

Companies

138

Table 4.28. LA/NCD of Islamic Banks by BUKU Bank

Group

139

Table 4.29. Financing-to-Deposit Ratio (FDR) by BUKU

Bank Group

140

Table 4.30. Deposit Share by Island 142

Table 4.31. Disbursed Financing by BUKU Bank Group 145

Table 4.32. Gross NPF Ratio of Islamic Banks by BUKU

Bank Group147

Table 4.33. Rate of Return on Deposits 148

Table 4.34. Rate of Return on Disbursed Financing 148

Table 4.35. P&L by BUKU Group 150

Table 4.36. CAR of Islamic Banks by BUKU Group 150

Box Table 4.1.1. Liquidity Ratio by Bank Type 151

Box Table 4.2.1. Government Expenditure Budget

Realisation in East Java (Rp, billions)

156

Box Table 4.2.2. Increase (Decrease) of Bank Deposits in East

Java (Rp, billions)

157

Box Table 4.2.3 Correlation between Government

Expenditure Budget Expansion and Bank

Deposits in East Java

158

5. Financial System InfrastructureTable 5.1. BI-RTGS, BI-SSSS and SKNBI Performance 164

Table 5.2. Card-Based Payment Instruments and

Electronic Money Transactions

165

Table 5.3. Queue Transaction 168

Table 5.4. Core Banks in the BI-RTGS System 169

Table 5.5. Total Individual and Business DFS Agents

in 2017

172

6. Bank Indonesia’s Policy Response Backing Financial System Stability

Table 6.1. Housing Loan Performance by Type 192

Table 6.2. Housing Loan Performance by Bank Activity 192

Table 6.3. Housing Loans by Province 195

Article 1:Article Table 1.1. Summary of OJK Regulations concerning

Nonbank SBN Holdings

206

Article Table 1.2. Data Summary for the ECM and VECM

Methods

212

Article Table 1.3. Unit Root with an Augmented Dicky Fuller

(ADF) Test

212

Article Table 1.4. Long-Term Equation 212

Article Table 1.5. Short-Term Equation 213

Article 2:Article Table 2.1. Inefficiency Equations 224

Article Table 2.2. Data 224

Article Table 2.3. Cost Frontier Estimation Results 228

Article Table 2.4. Profit Frontier Estimation Results 229


VI BANK INDONESIA

1. The Condition of Financial System Stability

Graph 1.1. Major Export Commodity Prices 4

Graph 1.2. Brent Oil Price 4

Graph 1.3. JCI and Global Stock Indexes 4

Graph 1.4. CDS in Advanced Economies

and Regional4

Graph 1.5. Inflation and GDP Growth 7

Graph 1.6. Balance of Payments 7

Graph 1.7. Rupiah Exchange Rate 7

Graph 1.8. Appreciation and Depreciation against

the USD7

Graph 1.9. Non-Resident Capital Flows 7

Graph 1.10. Exchange Rate Volatility (ytd) in the Region 7

Graph 1.11. Financial System Stability Index (FSSI) 10

Graph 1.12. Financial Institution Stability Index (FISI) 10

Graph 1.13. Financial Market Stability Index (FMSI) 10

Graph 1.14. Banking Systemic Risk Index (BSRI) 10

Graph 1.15. Asset Composition of Financial Institutions 11

Graph 1.16. Financial Cycle 11

Graph 1.17. Banking Lending Procyclicality 11

Graph 1.18. Components of State Revenue in the First

Semester of 201712

Graph 1.19. Growth of State Revenue Components in

the First Semester of 201712

Graph 1.20. Components of State Expenditure in the

First Semester of 201713

Graph 1.21. External Debt Composition based on Loan

Type and External Debt to GDP14

Graph 1.22. Private Nonbank External Debt by Original

Maturity15

Graph 1.23. Debt Service Ratio (DSR) 15

Graph 1.24. Non-Resident Investor Holdings in SBN 16

Graph 1.25. Non-Resident Investor Holdings in Stocks 16

Graph 1.26. Foreign and Domestic Holdings in Bank

Indonesia Certificates (SBI)17

Graph 1.27. The Development of Price and Volume of

Stock Transactions17

Graph 1.28. SBN Transaction Volume and Prices 17

Box Graph 1.1.1. Sources of Shocks in Indonesia’s Financial

System19

Box Graph 1.1.2. Characteristics of Vulnerabilities in

Indonesia’s Financial System19

Box Graph 1.1.3. Confidence in National Financial System

Stability21

Box Graph 1.3.1. Tax Amnesty Fees 26

Box Graph 1.3.2. Declared Assets through the Tax Amnesty 26

Box Graph 1.3.3. Ratio of Tax to GDP (%) 26

2. Financial MarketsGraph 2.1. IPO and Right Issue Volume on the Stock

Market31

Graph 2.2. Comparison of Corporate Bond Yield Curve

and Average Interest Rates on Investment

Loans and Working Capital Loans

32

Graph 2.3. Bond Issuance Value 32

Graph 2.4. Value of Outstanding MTN and NCD 32

Graph 2.5. Outstanding MTN and NCD by Maturity 32

Graph 2.6. Nominal Value of MTN and NCD Issuances 33

Graph 2.7. Financial Markets Volatility 35

Graph 2.8. Non-Resident Capital Flows to Stocks, SBN

and SBI35

Graph 2.9. Rupiah O/N Interbank Rate 36

Graph 2.10. O/N Interbank Rate Volatility 36

Graph 2.11. Rupiah Interbank Money Market

Performance37

Graph 2.12. Rupiah Interbank Money Market

Transaction Trends37

Graph 2.13. Foreign Exchange Interbank Money Market

Performance37

Graph 2.14. Foreign Exchange O/N Interbank Rate 37

Graph 2.15. Foreign Exchange Interbank Rate Volatility 38

Graph 2.16. Foreign Exchange Interbank Money Market

Transaction Behaviour38

Graph 2.17. Interbank Repo Transactions 38

Graph 2.18. Rupiah Exchange Rate Performance 39

Graph 2.19. Rupiah Volatility 39

Graph 2.20. Foreign Exchange Market Risk Premium 39

Graph 2.21. Composition of the Domestic Foreign

Exchange Market40

Graph 2.22. Composition of SBN Holdings 41

Graph 2.23. Net Foreign Flows to SBN and IDMA 41

Graph 2.24. SBN Yield Curve 41

Graph 2.25. Rebased SBN Yield by Tenor 41

Graph 2.26. SBN Yield Volatility by Tenor 41

Graph 2.27. Transaction Turnover of SBN and Corporate

Bonds41

Graph 2.28. SBN to GDP Ratio 42

LIST OF GRAPHAND FIGURE

VIIBANK INDONESIA

Graph 2.29. Rebased 10-Year Benchmark Yields in

Emerging Markets42

Graph 2.30. Net Foreign Flows and Foreign Holdings of

Corporate Bonds43

Graph 2.31. Corporate Bond Yield Curve 44

Graph 2.32. Corporate Bond Yield Volatility by Tenor 44

Graph 2.33. Corporate Bond Issuances by Economic

Sector44

Graph 2.34. Stock Price Index Developments 45

Graph 2.35. Stock Price Volatility 45

Graph 2.36. Foreign Capital Flows to Regional Stock

Markets45

Graph 2.37. Foreign Net Buy/Sell in the Stock Market

and JCI45

Graph 2.38. Comparison of Regional Indexes 45

Graph 2.39. Stock Market Turnover 46

Graph 2.40. JCI and LQ45 Capitalisation 46

Graph 2.41. EBITDA and JCI Performance 46

Graph 2.42. The Performance of Mutual Funds 47

Graph 2.43. NAV of Mutual Funds by Fund Type 47

Graph 2.44. NAV Volatility of Mutual Funds by Fund

Type47

Graph 2.45. Growth of Mutual Funds (yoy) 47

Graph 2.46. Risk Profile of Mutual Fund Products 48

Graph 2.47. NAV of Open-Ended and Closed-End

Mutual Funds48

Graph 2.48. Accumulated Funds in the Islamic Capital

Market49

Graph 2.49. Average Growth of Islamic Capital Market 49

Graph 2.50. Islamic Capital Market Developments 49

Graph 2.51. Islamic Capital Market Share 50

Graph 2.52. Islamic Securities List 50

Graph 2.53. JCI and ISSI Comparison 51

Graph 2.54. Market Capitalisation Growth (yoy) 51

Graph 2.55. Islamic Stock Indexes 52

Graph 2.56. Stock Index Volatility 52

Graph 2.57. Net Asset Value of Islamic Mutual Funds 52

Graph 2.58. NAV Growth of Islamic Mutual Funds 52

Graph 2.59. NAV of Islamic Mutual Funds by Fund Type 53

Graph 2.60. Issuances of Government Securities 53

Graph 2.61. Sukuk Issuances by Type 53

Graph 2.62. Outstanding Government Sukuk 54

Graph 2.63. Growth of Outstanding SBN 54

Graph 2.64. Composition of Sukuk based on SBSN Series 54

Graph 2.65. Composition of Sukuk based on Maturity 54

Graph 2.66. Holdings of Tradeable Government Islamic

Securities (SBSN)55

Graph 2.67. Growth of Corporate Bonds and Sukuk 55

Graph 2.68. Market Share of Corporate Sukuk 55

Graph 2.69. Corporate Sukuk Holdings 55

Graph 2.70. Corporate Bond Holdings 55

Graph 2.71. Accumulation and Disbursement of Zakat

Funds56

Graph 2.72. Accumulation and Disbursement of Zakat

Funds by Province56

Box Figure 2.1.1. Financial Market Development Framework 59

Box Graph 2.2.1. Certified Treasury Professionals 62

3. Households and CorporationsGraph 3.1. Contribution of Household Consumption

to GDP67

Graph 3.2. Real Sales Growth 68

Graph 3.3. Consumer Confidence Index (CCI), Current

Economic Condition Index (CECI), and

Consumer Expectation Index (CEI)

68

Graph 3.4. Three-Month Price Expectations Index (PEI) 69

Graph 3.5. Six-Month Price Expectations Index (PEI) 69

Graph 3.6. Allocation of Household Spending 70

Graph 3.7.a. Composition and Growth of Deposits 71

Graph 3.7.b. Value and Total of Deposit Accounts 72

Graph 3.8. Composition and Growth of Household

Deposits72

Graph 3.9 Composition of Bank Loans 72

Graph 3.10. Household Consumer Loan Developments

by Component73

Graph 3.11. Value and NPL of Household Consumer

Loans73

Graph 3.12. Household Consumer NPL by Component 73

Graph 3.13. Household Consumer Loan Composition by

Loan Type73

Graph 3.14. Commodity Prices 74

Graph 3.15. Indonesia’s Exports and Imports 75

Graph 3.16. Predicted and Actual Business Expansion 76

Graph 3.17. Utilised Production Capacity 76

Graph 3.18. Key Performance Indicators 76

Graph 3.19. Financial Performance of Public Non-

Financial Corporations78

Graph 3.20. Non-Financial Corporate Repayment

Capacity78


VIII BANK INDONESIA

Graph 3.21. Financial Performance of Major

Commodity-Based Corporations79

Graph 3.22. Corporate Performance per the Altman

Z-Score80

Graph 3.23. Distressed Corporate Performance against

GDP80

Graph 3.24. Corporate Loans by BUKU Bank Group 80

Graph 3.25. Performance of Corporate Deposits 82

Graph 3.26. Corporate Deposits by BUKU Bank Group 83

Graph 3.27 External Debt in Indonesia 84

Graph 3.28 Private External Debt Growth and Value 84

Graph 3.29 Restructured External Debt of Non-

Financial Corporations85

Graph 3.30 Outstanding Restructured External Debt

(USD, millions)86

Graph 3.31 Share of Outstanding Restructured External

Debt to Total Restructure External Debt (%)86

Graph 3.32 Interest and Principal Payments on Positive

and Negative Tone Restructured External

Debt

86

Box Graph 3.1.1 Bank Loans in East Java 87

Box Graph 3.1.2 Trend and Share of Loan Disbursements

by Sector87

Box Graph 3.1.3 Loans Disbursed operational to the Base

Metals Industry88

Box Graph 3.1.4. Iron and Steel Exports 88

Box Graph 3.1.5. Profitability of the Steel Industry 89

Box Graph 3.1.6. Productivity of the Steel Industry 89

Box Graph 3.1.7. NPL of the Manufacturing Industry in East

Java90

4. Banking and IKNBGraph 4.1 Bank Liquidity Ratios 97

Graph 4.2 Liquid Assets of the Banking industry 97

Graph 4.3 Liquidity Growth in the Economy and Bank

Liquidity Ratios97

Graph 4.4 Government Net Expansion 97

Graph 4.5 Deposit and Credit Growth (yoy) 98

Graph 4.6 Lending Standards 99

Graph 4.7 Deposit Growth (yoy) 99

Graph 4.8 Market Share of Deposits based on Core

Depositors/Non-Core Depositors100

Graph 4.9 Deposit Growth by Type 101

Graph 4.10 Composition of Bank Deposits 101

Graph 4.11 Deposit Performance by Depositor Group 101

Graph 4.12 Bank Credit Growth (yoy) 102

Graph 4.13 Credit Growth by Loan Type 103

Graph 4.14 Credit Share by Loan Type 103

Graph 4.15 Credit Growth by Economic Sector (yoy) 104

Graph 4.16 Credit Growth by Economic Sector (Rp,

trillions)104

Graph 4.17 Rupiah Lending Rates by BUKU Bank Group 105

Graph 4.18. MSME Loan Performance 105

Graph 4.19. MSME Credit Growth in 6 Economic Sectors 107

Graph 4.20. KUR Realisation against Target, 2015-2017 108

Graph 4.21. Market Share of People’s Business Loans

(KUR) 108

Graph 4.22 NPL Ratio 109

Graph 4.23 Gross NPL Ratio by Loan Type 109

Graph 4.24 Gross NPL Ratio by Economic Sector (%) 110

Graph 4.25 Gross NPL Growth by Economic Sector (Rp,

trillions)110

Graph 4.26 Restructured Loan Developments 112

Graph 4.27 Gross NPL Ratio of MSME Loans by Year 113

Graph 4.28 Gross NPL Ratio of MSME Loans by Business

Scale113

Graph 4.29 KUR NPL and NPG 114

Graph 4.30 Lending and Deposit Rates 114

Graph 4.31 Total NOP and NOP Ratio by Bank Group 116

Graph 4.32 SBN Yield Volatility 117

Graph 4.33. External Debt in Indonesia 119

Graph 4.34. Government and Private External Debt 119

Graph 4.35. Share of Private External Debt 119

Graph 4.36. External Debt Growth in the Banking

Industry119

Graph 4.37. External Debt by Bank Type 120

Graph 4.38. External Debt Maturity 120

Graph 4.39. Ratio of Short-Term External Debt to

Capital in the Banking Industry120

Graph 4.40. Maturity Profile of Long-Term External

Debt in the Banking Industry121

Graph 4.41 Maturity Composition of Long-Term

External Debt in the Banking Industry121

Graph 4.42 ROA by BUKU Bank Group 122

Graph 4.43. NIM by BUKU Bank Group 122

Graph 4.44. BOPO Efficiency Ratio by BUKU Bank Group

(%)124


IXBANK INDONESIA

Graph 4.45 Cost-to-Income Ratio (CIR) by BUKU Bank

Group (%)124

Graph 4.46 Banking Industry CAR (%) 124

Graph 4.47 Tier 1 Ratio in the Banking Industry (%) 124

Graph 4.48. Credit Risk (NPL) Scenarios 125

Graph 4.49. SBN Yield Scenarios 125

Graph 4.50. Currency Depreciation Risk Scenarios 126

Graph 4.51. Currency Risk Scenarios 126

Graph 4.52. Aggregate Stress Test Results 126

Graph 4.53. Share of Capital Shortfall in the Banking

Industry (Aggregate)127

Graph 4.54. Stress Test Results by BUKU Group (Severe

Scenario)127

Graph 4.55. Stress Test Results by BUKU Group (PSG

Scenario)127

Graph 4.56. Finance Company Assets and Financing 129

Graph 4.57. Finance Company Financing by Business

Activity129

Graph 4.58. Financing by Types of Forex 130

Graph 4.59. Ratio of NPF PP (%) 130

Graph 4.60. Financing and Funding Growth 131

Graph 4.61. Sources of Funds 131

Graph 4.62. Market Share of Finance Company

Borrowings based on Lending Rates131

Graph 4.63. External Debt at Finance Companies 132

Graph 4.64. ROA, ROE and BOPO Efficiency Ratio of

Finance Companies133

Graph 4.65 Asset Share in the Insurance Industry 134

Graph 4.66. Insurance Industry Assets and Investments 134

Graph 4.67. Insurance Industry Asset and Investment

Composition136

Graph 4.68. Gross Premiums to Claims Ratio 136

Graph 4.69. Ratio of Current Assets to Current

Liabilities136

Graph 4.70. Insurance Industry Indicators 136

Graph 4.71. Insurance Industry External Debt 137

Graph 4.72 Weighted Average Deposit Rate in Rupiah

at BUKU 1 Banks138

Graph 4.73 Liquidity Ratios in the Islamic Banking

Industry139

Graph 4.74 Banking Industry Liquid Assets 139

Graph 4.75 Deposit and Financing Growth (yoy) 140

Graph 4.76 Deposit Growth (yoy) 140

Graph 4.77 Deposit Growth by Type 141

Graph 4.78 Deposit Composition in the Islamic Banking

Industry141

Graph 4.79 Rate of Return on Deposits 142

Graph 4.80 Composition of Disbursed Funds 142

Graph 4.81 Securities Holdings of the Islamic Banking

Industry142

Graph 4.82 Financing Growth (yoy) by Currency 143

Graph 4.83 Disbursed Financing Growth by Type (yoy) 143

Graph 4.84 Disbursed Financing Growth by Contract

(yoy)144

Graph 4.85 Disbursed Financing Growth by Economic

Sector144

Graph 4.86 Composition of Disbursed Financing 144

Graph 4.87 Rate of Return on Disbursed Financing 144

Graph 4.88 Non-Performing Financing 145

Graph 4.89 NPF Ratio by Financing Type 146

Graph 4.90 NPF Ratio by Contract 146

Graph 4.91 NPF Ratio by Economic Sector 147

Graph 4.92 Comparison of Returns on Disbursed

Financing at Islamic Banks, Lending Rats

and the BI 7-Day (Reverse) Repo Rate

149

Graph 4.93 ROA by BUKU Group 149

Graph 4.94 ROA Comparison between Islamic and

Conventional Banks150

Graph 4.95 NOM by BUKU Group 150

Graph 4.96 BOPO Efficiency Ratio by BUKU Group 150

Graph 4.97 BOPO Comparison between Islamic and

Conventional Banks150

Graph 4.98 CAR 150

Box Graph 4.1.1. Liquidity Ratios in the Banking Industry 151

Box Graph 4.1.2 Annual Liquidity Ratio Trends in the

Banking Industry151

Box Graph 4.1.3. Annual Liquid Asset Trends in the Banking

Industry151

Box Graph 4.1.4. Liquid Assets and Interbank Rates 152

Box Graph 4.1.5. Interbank Rate by Tenor 152

Box Graph 4.1.6. Interbank Money Market Transaction

Volume153

Box Graph 4.1.7. Net Interbank Money Market by Bank Type 153

Box Graph 4.2.1. Average Regional Expenditure Budget

Realisation 2014-2016155

Box Graph 4.2.2. Government Expenditure Budget

Realisation in East Java 2014-2016

(quarterly)

156


X BANK INDONESIA

Box Graph 4.2.3. Bank Deposits in East Java 157

Box Graph 4.2.4. Government Deposits in East Java 157

Box Graph 4.2.5. Composition of Government and Private

Deposits158

5. Financial System InfrastructureGraph 5.1. MO Placements 167

Graph 5.2. Turnover Ratio x Monetary Operations 168

Graph 5.3. Indonesia Financial Inclusion Composite

Index (IKKI)170

Figure 5.1 DFS Agents in Indonesia 171

Graph 5.4. Total DFS Agents in 2017 172

Graph 5.5. Percentage of E-Money Transactions at DFS

Agents172

Graph 5.6. E-Money Account Holders at DFS Agents

(millions)172

6. Responds of Bank Indonesia’s Policy Graph 6.1. Credit-to-GDP Gap 184

Graph 6.2. CCyB Rate per the Leading Indicator 184

Graph 6.3. Financial Cycle of Indonesia 185

Graph 6.4. Real GDP Growth 185

Graph 6.5. Inflation (yoy) 185

Graph 6.6. Exchange Rate (Rp/USD) 185

Graph 6.7. Private External Debt in Rupiah (yoy) 185

Graph 6.8. Credit Growth (yoy) 186

Graph 6.9. Deposit Growth (yoy) 186

Graph 6.10. NPL Ratio (%) 186

Graph 6.11. ROA Ratio (%) 186

Graph 6.12. Capital Adequacy Ratio (%) 186

Graph 6.13. Loan-to-Deposit Ratio (%) 186

Graph 6.14. JCI Volatility 187

Graph 6.15. Loan-to-Deposit Ratio (LDR) and Financing-

to-Deposit Ratio (FDR) Developments188

Graph 6.16. Loans, Deposits and Securities 188

Graph 6.17 The Number of Banks Fulfilling the RR-Loan

to Funding Ratio (RR-LFR)189

Graph 6.18. Housing Loans 190

Graph 6.19. Housing Loans by Type 190

Graph 6.20. Housing Loan Performance by Bank Activity 191

Graph 6.21. NPL of Housing Loans 194

Graph 6.22. NPL of Housing Loans by Type 194

Box Figure 6.2.1. Awqaf-Linked Sukuk 201

Article 1:Graph Article 1.1. SBN, Deposit and GDP Growth 205

Graph Article 1.2. SBN Holdings by Financial Institution

(December 2014 and December 2016)206

Graph Article 1.3. Holdings of SBN and Deposits by Nonbanks

(Rp, billions)207

Graph Article 1.4. SBN Yield and Deposit Rate Developments 208

Graph Article 1.5. Keynesian Liquidity Preference 210

Article 2:Article Figure 2.1. Network Types 221

Article Graph 2.1. Composition of Banks Transacting in the

Interbank Money Market225

Article Graph 2.2. Weighted Degree by Bank Type and

Average per Bank by Bank Type225

Article Graph 2.3. Weighted Indegree by Bank Type 225

Article Graph 2.4. Weighted Outdegree by Bank Type 226

Article Graph 2.5. Large and Small Bank Interaction 226

Article Graph 2.6. Interbank Rate Interaction between Large

and Small Banksl226

Article Graph 2.7. Average Closeness 227

Article Graph 2.8. Industry Betweenness 227

Article Graph 2.9. Industry Average Clustering Coefficient 227

Article Graph 2.10. Degree Distribution 227

Article Graph 2.11. Alpha Coefficient (Power Law) 227


XIBANK INDONESIA


XII BANK INDONESIA

LIST OF ABBREVIATIONS

ABIF : ASEAN Banking Integration Framework

AFS : Available for Sale

AKSI : Indonesia Islamic Financial Architecture

APMK : Card-based Payment Instruments

AS : United States of America

ASEAN : Association of Southeast Asian Nations

ATM : Automated Teller Machine

ATMR : Risk-Weighted Assets (RWA)

BBM : Fossil Fuels

BCBS : Basel Committee on Banking Supervision

BIS : Bank for International Settlements

BI-RTGS : Bank Indonesia – Real Time Gross Settlement

BI-SSSS : Bank Indonesia – Scripless Securities Settlement System

BOJ : Bank of Japan

BOPO : BOPO Efficiency Ratio

BPD : Regional Banks

BPR : Rural Banks

bps : Basis point

BUKU : Commercial Bank Classification

CAR : Capital Adequacy Ratio

CCB : Countercyclical Capital Buffer

CDS : Credit Default Swaps

CIR : Cost-to-Income Ratio

CPO : Crude Palm Oil

DER : Debt-to-Equity Ratio

DPK : Private Deposits

D-SIB : Domestic Systemically Important Banks

DSR : Debt Service Ratio

DP : Downpayment

EAPP : Expanded Asset Purchase Program

ECB : European Central Bank

EM : Emerging Market

FA : Financial Account

FDI : Foreign Direct Investment

FKSSK : Financial System Stability Coordination Forum (FSSCF)

FLI : Intraday Liquidity Facility (ILF)

FSB : Financial Stability Board

G20 : The Group of Twenty

GDP : Gross Domestic Product

GNNT : National Noncash Movement

GWM : Reserve Requirement

HTM : Hold to Maturity

IDMA : Inter-dealer Market Association

IEK : Consumer Expectation Index (CEI)

IHK : Consumer Price Index (CPI)

IHSG : Jakarta Composite Index (JCI)

IKK : Consumer Confidence Index (CCI)

IKNB : Nonbank Financial Institution

IMF : International Monetary Fund

ISIK : Financial Institution Stability Index (FISI)

ISPK : Financial Market Stability Index (FMSI)

ISSK : Financial System Stability Index (FSSI)

JIBOR : Jakarta Interbank Offered Rate

JPSK : Financial System Safety Net (FSSN)

KI : Investment Loan

KK : Consumer Loan

KMK : Working Capital Loan

KPA : Housing Loan (Apartment)

KPMM : Minimum Capital Adequacy Requirement

KPR : Housing Loan (House)

KPwDN : Domestic Bank Indonesia Representative Office

KSSK : Financial System Stability Committee

LCR : Liquidity Coverage Ratio

LDR : Loan-to-Deposit Ratio

LKD : Digital Financial Services (DFS)

LTV : Loan-to-Value Ratio

XIIIBANK INDONESIA

LPS : Deposit Insurance Corporation (DIC)

L/R : Profit/Loss (P/L)

Minerba : Mineral and Coal Mining

MTM : Marked to Market

MTN : Medium-Term Notes

NAB : Net Asset value (NAV)

NCD : Negotiable Certificate of Deposit

NFA : Net Foreign Asset

NFL : Net Foreign Liabilities

NII : Net Interest Income

NIM : Net Interest Margin

NPF : Non-Performing Financing

NPI : Indonesia Balance of Payments

NPL : Non-Performing Loan

OJK : Indonesia Financial Services Authority

OM : Monetary Operations

OTC : Over the Counter

PBOC : People’s Bank of China

PD : Probability of Default

PDB : Gross Domestic Product (GDP)

PDN : Net Open Position (NOP)

PIN : Personal Identification Number

PLN : Foreign Loan

PMK : Crisis Management Protocol (CMP)

PP : Finance Company

PUAB : Interbank Money Market

QAB : Qualified ASEAN Bank

RBB : Bank Business Plan

ROA : Return on Assets

ROE : Return on Equity

SBDK : Prime Lending Rate

SBI : Bank Indonesia Certificate

SBN : Tradeable Government Security

SBT : Weighted Net Balance (WNB)

SD : Certificate of Deposit

SIMA : Interbank Mudharabah Investment Certificate

SKDU : Bank Indonesia Business Survey

SKNBI : National Clearing System

SNRT : Household Balance Sheet Survey

SUN : Government Debt Security

TDL : Base Electricity Rate

TOR : Turnover Ratio

TPT : Textiles and Articles Thereof

ULN : External Debt

UMKM : Micro, Small and Medium Enterprises (MSME)

WEO : World Economic Outlook


xiv BANK INDONESIA

FOREWORD

xvBANK INDONESIA

All praise to God Almighty for His blessings in the

completion of the Financial Stability Review (FSR)

No. 29, September 2017 Edition. The Financial

Stability Review is compiled biannually as a form

of transparency and accountability underlying the

execution of duties and authority at Bank Indonesia,

particularly macroprudential regulation and

supervision, as well as to support financial system

stability.

As a routine publication, the FSR contains

assessments and research concerning financial

system dynamics, including sources of vulnerability

and imbalances that could trigger financial system

instability. Assessments are conducted to control

potential financial system instability as early as

possible stemming from contagion in part or all of

the financial system. Contagion may originate from

several factors, including interaction between the

size and business complexity of financial institutions,

interconnectedness between financial institutions

and financial markets as well as procyclicality.

Based on the assessments conducted, Bank Indonesia

perceived relatively stable economic conditions

during the first half of 2017, recording positive

economic and financial developments despite a

backdrop of domestic and global economic shocks

and challenges. Furthermore, the results of the

previous Financial Sector Assessment Program (FSAP)

also confirmed solid macroeconomic conditions in

Indonesia, coupled with a stable financial system

in the face of global financial system volatility and

domestic fragilities.

In addition, Bank Indonesia also acknowledged that

financial system stability improved on conditions in

the previous period, corroborated by an FSS Index

of 0.82. The FSS Index was in line with the Banking

Systemic Risk Index (BSRI), which reflected normal

conditions well below the threshold, supported by

adequate capital in the banking sector that helped

to maintain banking industry resilience and relatively

stable financial market volatility. Notwithstanding

the accomplishments, several risks continued to

demand vigilance, including non-performing loans

(NPL).

Congruent with the improving conditions in the

banking industry, Islamic banks also posted gains

in the form of increasing assets. Furthermore, the

nonbank financial industry also performed well as

profitability increased despite an accumulation of

risks at finance companies. Likewise, non-financial

public corporations improved, as reflected by the

return on assets (ROA) and return on equity (ROE)

indicators as well as a stronger repayment capacity.

Nevertheless, the recent improvements have been

unable to catalyse adequate growth of new loans

due to corporate reluctance to expand against

a backdrop of global and domestic economic

challenges and uncertainty.

Complementing the general FSS assessments of

financial system components, including Islamic

finance, Bank Indonesia has also assessed payment

system performance, as part of financial system

infrastructure, along with other factors that could

trigger financial instability and systemic risk. The

policies instituted in response formed an integral

part of Bank Indonesia’s policy mix to achieve and

maintain price (rupiah) stability.

Following the enforcement of the Financial System

Crisis Prevention and Mitigation (PPKSK) Act,

Bank Indonesia issued implementation guidelines


xvi BANK INDONESIAxvi BANK INDONESIA

Jakarta, September 2017

Governor of Bank Indonesia

Agus D. W. Martowardojo

in the first semester of 2017 as Bank Indonesia

Regulation (PBI) No. 19/3/PBI/2017 concerning

the Short-Term Liquidity Facility for Conventional

Commercial Banks and Bank Indonesia Regulation

(PBI) No. 19/4/PBI/2017 concerning the Short-Term

Liquidity Facility for Islamic Banks. Furthermore,

Bank Indonesia also monitored and evaluated the

effectiveness of several existing macroprudential

policies, including monitoring the LTV ratio and RR-

loan to funding ratio (RR-LFR), while also maintaining

the countercyclical capital buffer (CCyB) at 0%.

Considering policy synergy between financial sector

authorities can enhance policy effectiveness, the

evaluation of existing regulations formed part of the

coordination and communication strategy amongst

relevant authorities, bilaterally and through the

Financial System Stability Committee (FSSC).

In closing, I hope that this edition of the Financial

Stability Review (FSR) will help all readers to

understand the current economic dynamics and

risks as well as the policy responses taken to

maintain financial system stability. Any comments

and suggestions as well as constructive criticisms

are welcome in order to improve future policies and

analysis.

xviiBANK INDONESIA xviiBANK INDONESIA


xviii BANK INDONESIA

EXECUTIVE SUMMARY

xixBANK INDONESIA

Increasing bank capital and liquidity, coupled with

financial market stability, underpinned financial

system stability during the first semester of 2017.

In general, such developments were reflected

by the Financial System Stability Index (FSSI) and

Banking Systemic Risk Index (BSRI), which improved

on their previous positions despite the higher risks

attributed to non-performing loans (NPL). The

bank intermediation function experienced slower

growth but maintained a positive trend on the back

of government infrastructure projects. Additionally,

financial system stability was threatened by a build-

up of risk in the global financial markets due to the

Federal Reserve’s move to hike the Federal Funds

Rate (FFR) and unwind its balance sheet along with

other externalities that influenced regional and

domestic financial market developments.

Domestic economic stability was relatively well

maintained despite the need to monitor various risks.

Nevertheless, the domestic economic risks were

contained, supported by low and stable inflation in

the target corridor of 4.0±1%, despite inflationary

pressures stemming from administered prices (AP).

Furthermore, increasing investment, export growth

and tenacious household consumption buoyed the

economic recovery. The balance of payments (BOP)

continued to record a surplus, bolstered by the capital

and financial account, which posted a significant

surplus off the back of a surge of portfolio and

direct investment inflows as the domestic economic

outlook stoked investor interest. The balance of

payments surplus was also accompanied by rupiah

appreciation, stemming from low rupiah volatility

and a deluge of non-resident capital inflows as well

as financial market deepening.

Against a backdrop of global economic

imbalances and maintained domestic economic

expansion, several sources of instability continued

to overshadow financial system stability in the

first half of 2017, including: (i) bank lending

procyclicality and a financial cycle contraction;

(ii) limited fiscal space; (iii) comparatively high-

risk external debt at nonbank corporations; and

(iv) large non-resident holdings in the domestic

financial markets.

Congruent with the credit slowdown, the financial

cycle in Indonesia continued to contract due

to limited increases of aggregate demand, as

reflected by economic growth of 5.01% (yoy)

despite accelerating on the 4.94% (yoy) posted

in 2016. Meanwhile, bank lending procyclicality

fed through to a rising NPL ratio, with the banks

becoming more selective and cautious when

lending. Such procyclicality must be anticipated in

order to avoid a deeper economic downturn.

On the fiscal side, the absorption of government

spending combined with increasing government

revenues supplemented fiscal space. Limited

expenditure realisation led to a 1.3% deficit of GDP

as of June 2017 despite improving on conditions

in the previous year at 1.9% of GDP. Government

revenues, however, increased on the same period

one year earlier. On the other hand, tax revenue

decreased as the contribution of non-oil and gas

taxes declined. Nevertheless, broad fiscal space

alleviated risks in the financial system. Furthermore,

more limited government expansion in the reporting

period helped to maintain liquidity in the financial

system.


xx BANK INDONESIAxx BANK INDONESIA

Improving global and domestic economic

dynamics prompted an increase of external debt.

Consequently, external debt stood at USD335.29

billion in the first semester of 2017, with growth

recorded at 2.85% (yoy). The risks associated with

private nonbank external debt, most of which

was long term, were relatively well mitigated but

an increase of outstanding external debt in the

reporting period required close monitoring as a

source of potential vulnerability in the domestic

financial markets. Moreover, the risks linked to

corporate repayment capacity, as indicated by the

Tier-1 debt service ratio (DSR), remained high.

Seeking to mitigate the risks contained in corporate

external debt, Bank Indonesia applied a hedging

ratio applicable to all nonbank corporations holding

foreign debt.

Another source of vulnerability in the financial

system has been the large non-resident investor

holdings in the domestic financial markets. In the

stock market and SBN market, foreign holdings

spiked significantly in March and April 2017 due

to positive sentiment after Indonesia’s sovereign

rating was upgraded to investment grade by several

ratings agencies. Such developments demonstrated

the high level of non-resident investor confidence in

the domestic economic outlook. On the other hand,

however, this also precipitated the risk of a sudden

capital reversal and transaction volatility, triggered

by external shocks originating from economic and

global financial market dynamics, for example an

unanticipated FFR hike or geopolitical shocks in

neighbouring countries such as North Korea.

Amid bank consolidation in terms of lending,

economic financing from the financial markets

increased considerably in the first half of 2017,

primarily stemming from increasing issuances of

corporate bonds and sukuk through initial public

offerings (IPO) and rights issues. Bullish global

sentiment, the improving domestic economic

outlook and the upgraded sovereign rating further

supported the increase in economic financing from

the financial markets. In terms of prices, more

competitive corporate bonds, particularly those

rated AAA to A, compared to bank loans, especially

in the long term, compelled the corporate sector

to increase financing through corporate bonds.

In addition, several corporations used financing

through corporate bonds as an alternative to

external debt as global interest rates ticked upwards.

Congruent with vibrant stock and bond market

growth, the positive trends also affected Negotiable

Certificates of Deposit (NCD) and Medium-Term

Notes (MTN). NCD instruments appealed to bank

issuers as an alternative source of short-term

financing of less than one year. Meanwhile, most

MTN issuances were used as working capital

(business expansion) and for refinancing purposes.

The surge of funding through NCD and MTN

instruments was also driven by simpler requirements

with no mandatory rating at the time of issue.

Promulgation of Bank Indonesia Regulation (PBI)

No. 19/2/PBI/2017 on 16th March 2017 concerning

Certificate of Deposit Transactions in the Money

Market, which standardised NCD instruments,

further boosted sentiment in the NCD market and

broadened the NCD investor base.

In general, risks in the global and domestic financial

markets were relatively stable and contained in the

first half of the year, which attracted an influx of non-

resident capital to the domestic financial markets.

Volatility in the rupiah interbank money market,

foreign exchange market, stock market and bond

market – both government bonds and corporate

xxiBANK INDONESIA xxiBANK INDONESIA

bonds – eased, indicating less risk in the domestic

financial markets. Despite milder risks in the foreign

exchange market, prudential principles were still

applied. Derivative transactions, particularly swap

transactions, tracked an upward trend, which was

indicative of ongoing financial market deepening,

thus providing an alternative instrument for market

players to manage foreign exchange risk. In the SBN

market, soaring demand for tradeable government

securities (SBN), particularly from non-resident

investors, triggered downward pressures on yields

and volatility. A deluge of inflows, however,

expanded foreign SBN holdings to nearly 40%. The

benchmark 10-year yield fell by around 6-7% with

volatility at below 5%, which was consistent with

falling SBN yields in several neighbouring countries

due to positive global sentiment. In the stock

market, the Jakarta Composite Index (JCI) rallied

10% in the first semester of 2017, accompanied

by comparatively high PER compared to other

countries in the region, which demanded vigilance.

Furthermore, issuer profit performance was the

primary focus of investors, especially non-resident

investors.

In line with the generally sound performance of

the financial markets, the Islamic financial market

also tracked an upward trend, with the Islamic

stock index posting gains, the share of state sukuk

continuing to expand as a source of state budget

financing and Islamic investment funds continuing

to develop. In addition, the social financial sector

also recorded positive developments. Zakat and

waqf funds also continued to expand.

Despite stronger national economic growth in

Indonesia, the household sector failed to keep

pace, as reflected by households less inclined

to spend on consumption and a decline in the

proportion of household consumption spending to

GDP. Nevertheless, households remained upbeat

on future economic conditions, as indicated by

household consumer loan growth as well as gains in

the Real Sales Index (RSI) and Consumer Confidence

Index (CCI). Furthermore, household optimism was

expected to edge up future deposit growth and

improve loan and financing quality compared to

conditions in the first semester of 2017.

In the corporate sector, export growth accelerated

on the previous period. Nonetheless, corporate

sector performance was undermined by the

sluggish global economic recovery and persistently

low and volatile international commodity prices.

Consequently, non-financial public corporations

strived to enhance efficiency to maintain financial

positions, as reflected by stronger profitability

indicators on the back of rising net profits.

Bank lending to the corporate sector slowed in the

first semester of 2017, primarily loans extended to the

transportation, warehousing and communication

sector as well as the manufacturing industry. As an

aggregate, however, corporate loan quality tended

to improve, with the gross NPL ratio decreasing on

the previous period. Improving non-performing

loans tended to originate from the transportation,

warehousing and communication sector as well as

the manufacturing industry. Notwithstanding, the

gross NPL ratio for the mining sector failed to show

any improvement due to subdued mining industry

performance as a result of fluctuating and sliding

mining commodity prices, coupled with weaker

demand for mining products.

In general, the performance of national banking

indicators varied in the first half of 2017. Banks

and their customers tended to be cautious and wait


xxii BANK INDONESIAxxii BANK INDONESIA

and see the latest economic developments before

taking any banking decisions. The total assets of

the banking industry continued to expand, albeit

slightly more moderately compared to the previous

period, driven primarily by deposit growth.

The bank intermediation function also tended to

slow. Dwindling corporate demand for new loans

undermined credit growth, including MSME loans

because the corporate sector tended to wait and

see the latest economic developments. Slower

credit growth primarily affected BUKU 2 and 4

banks. The failure of major commodity prices to

rebound, particularly coal, coupled with a lack

of improvement in public purchasing power also

influenced customer demand for loans. Additionally,

the banks tended to become more selective when

lending, raising lending standards which further

undermined borrower interest in new loans.

Nonetheless, intense financing of government

infrastructure projects along with bank efforts to

reduce lending rates prevented further moderation

of credit growth.

Deposit growth accelerated, primarily due to

repatriated funds from the tax amnesty and financial

expansion by the government. Deposit growth was

predominantly reported by BUKU 2 and 4 banks

and affected term deposits of above Rp2 billion.

Bank dependence on core depositors and expensive

sources of funds remained relatively high despite

bank efforts to expand and divert funding sources

to current and saving accounts (CASA).

In general, the banking industry posted larger profits,

indicated by a higher return on assets (ROA) at all

BUKU bank groups. The ROA gains mainly stemmed

from bank business efficiency, including lower

operating costs to bolster reserves. Furthermore, the

banks also lowered lending rates to boost demand

for loans, which has not significantly eroded bank

profits.

The banking industry mitigated risk during the first

half of the year at a safe level. Liquidity risk was

shown to ease due mainly to the rise in deposits.

Bank customers and borrowers tended to deposit

their funds in the banking system and refrain from

expanding their businesses. The ratio of liquid assets

to non-core deposits remained high at 101.26%.

On the other hand, credit risk tended to accumulate,

primarily affecting investment loans and consumer

loans. The gross NPL ratio deteriorated from 2.93%

to 2.96%. The banks attributed rising credit risk

to the major mining products, particularly coal

prices, as well as stagnant public purchasing power.

Meanwhile, credit restructuring experienced a

relatively large bump to 5.53%, which was ascribed

to the relaxation of credit requirements through

OJK Regulation (POJK) No. 11/POJK.03/2015

concerning Prudential Regulations for Commercial

Banks to Stimulate the National Economy, issued on

24th August 2015.

Interest rate risk was also well mitigated. Bank efforts

to reduce lending rates have successfully narrowed

the intermediation spread and not significantly

eroded bank profits. The banks maintained a

relatively low net open position (2.32%), indicating

that interest rate risk was contained. Furthermore,

the national banking industry tended to favour a

long position as the rupiah appreciated. On the

other hand, the banking industry mitigated market

risk in line with lower SBN yields and volatility.

Furthermore, SBN holdings in the banking industry

increased due to inflows of repatriated funds

from the successful tax amnesty. The larger SBN

holdings were also in line with slower growth of

xxiiiBANK INDONESIA xxiiiBANK INDONESIA

bank lending, particularly affecting available for sale

(AFS) and held to maturity (HTM) portfolios as liquid

assets and long-term investments rather than for

trading purposes.

The Islamic banking industry also performed

soundly in the reporting period, with a healthy

intermediation function. Asset growth was driven

by funding growth, primarily demand deposits

and term deposits. Likewise, the Islamic banking

industry successfully mitigated the risks. Liquidity

risk was observed to decline but remained above

the threshold. Meanwhile, financing risk eased

with a lower NPF ratio reported. A high capital ratio

helped the Islamic banking industry to absorb the

risks the emerged.

Consistent with weaker credit growth in general,

MSME loans also experienced slower growth,

accompanied by a build-up of MSME credit risk.

Loans extended to micro and small enterprises

were the main contributors to slower MSME loan

growth, while People’s Business Loans (KUR) also

decelerated on the same period one year earlier. In

2017, financial institutions in the form of finance

companies and cooperatives also disbursed KUR

loans in addition to the approved banks.

Nonbank financial industry performance improved

in terms of financing and funding, driven by

finance companies and insurance companies.

Meanwhile, an increase in the non-performing

financing (NPF) ratio pointed to higher financing

risk in the nonbank financial industry. Furthermore,

the interconnectedness between banks and the

nonbank financial industry increased, as indicated

by more loans allocated by the banking industry

to finance companies as well as placements of

insurance funds in the banking sector.

The payment systems operated by Bank Indonesia

and the industry remained secure, efficient and

reliable, thereby supporting monetary and financial

system stability, while also facilitating economic

activities, as evidenced by improving leading and

supporting payment system indicators. Bank

Indonesia continued efforts and payment system

policies that focused on enhancing economic

efficiency by consistently and sustainably

strengthening and developing payment system

infrastructure, thus demonstrating Bank Indonesia’s

avowed commitment to ensure the payment system

supports financial system stability and the national

economy.

Payment system risks were well mitigated, including

settlement risk, liquidity risk, operational risk and

systemic risk. Settlement and liquidity risk were

relatively mild in the first semester of 2017, with

a low volume and value of unsettled transactions

as well as no requests recorded for the Intraday

Liquidity Facility (ILF) or Islamic Intraday Liquidity

Facility by participants of the BI non-cash payment

system. Meanwhile, operational and systemic risk

were also contained. In terms of the operational

risk, Bank Indonesia prepared a business continuity

plan that could be activated immediately when a

disruption was detected in the main system. To

control the systemic risk, Bank Indonesia conducted

regular and intensive monitoring of various payment

system indicators that could detect systemic

disruptions.

Bank Indonesia also strengthened the financial

system infrastructure, supported by expanding public

access to finance through inclusive digital financial

services. As a form of Bank Indonesia commitment

to the National Financial Inclusion Strategy and

part of the National Noncash Movement (GNNT) to


xxiv BANK INDONESIAxxiv BANK INDONESIA

encourage the public to use the non-cash payment

system and non-cash payment instruments, Bank

Indonesia has launched various non-cash programs

that aim to digitise all physical payment methods in

order to expand financial access as well as enhance

the efficiency, effectiveness and accountability

of financial management by the government,

business community and public. Some of the

non-cash programs developed by Bank Indonesia

in conjunction with the Government include the

electronification of social assistance disbursements,

village funds, toll roads, remittances and local

government transactions.

In the first semester of 2017, Bank Indonesia

instituted accommodative macroprudential policy as

a countercyclical instrument, which aimed to offset

the downturn and stimulate credit growth in order

to accelerate the domestic economic recovery while

maintaining financial system stability. Furthermore,

Bank Indonesia maintained the countercyclical

capital buffer (CCyB) at 0% in May 2017 because

excessive credit growth was not detected that

could trigger systemic risk, as indicated by the

credit-to-GDP gap as the primary CCyB indicator

along with supporting indicators in the form of

macroprudential, macroeconomic, banking and

asset price indicators.

Bank Indonesia also strengthened the lender of last

resort (LOLR) function to support the implementation

of accommodative macroprudential policy as part

of Bank Indonesia’s function to maintain financial

system stability pursuant to the Bank Indonesia Act

that was reinforced by the promulgation of the

Financial System Crisis Prevention and Mitigation

(PPKSK) Act in 2016, namely that Bank Indonesia

shall provide a short-term liquidity facility to banks

experiencing short-term liquidity difficulties. The

LOLR function is necessary to prevent and mitigate

instability in the financial system due to a liquidity

shortfall experienced by a bank that could trigger

default and spillovers, through contagion, and

adversely affect the financial system and ultimately

the economy.

In response to Bank Indonesia honing the RR-loan

to funding ratio (RR-LFR) in August 2016 by raising

the lower bound from 78% to 80%, despite a lower

LFR ratio recorded in the first semester of 2017, the

banks began to utilise securities as the main source

of bank funding, as reflected by a surge of securities

issued by the banking industry in 2017 compared to

conditions in 2016. Such developments were in line

with policy to include bank-issued securities in the

LFR calculation that aims to expand funding sources

for the banking industry, while supporting financial

market deepening. The declines observed in the LDR

and LFR were caused by deposit growth outpacing

credit growth as a result of the tax amnesty in line

with weaker economic growth.

Lacklustre property sector performance forced

Bank Indonesia to continue easing loan-to-value

(LTV) policy, which was initiated in 2015. The policy

successfully stemmed the decline of housing loans

and financing disbursed by the banking industry but

failed to stimulate credit and financing growth, thus

necessitating further policy easing to catalyse credit

growth in the property sector while maintaining

prudential principles. To that end, Bank Indonesia

further eased LTV policy through promulgation of

Bank Indonesia Regulation (PBI) No. 18/16/PBI/2016

concerning the loan-to-value (LTV) ratio for property

loans, the financing-to-value ratio (FTV) for property

financing and the downpayments on automotive

loans and financing. The LTV/FTV policy adjustment

quickly began to bear fruit, with the growth of

xxvBANK INDONESIA xxvBANK INDONESIA

housing loans accelerating from 6.21% in August

2016 to 7.51% in June 2017, despite remaining

below total bank credit growth at 7.75%.

In broader terms, Bank Indonesia’s accommodative

macroprudential policy has also been supported

by coordination amongst authorities under the

umbrella of the Financial System Stability Committee

pursuant to Act No. 9 of 2016 concerning Financial

System Crisis Prevention and Mitigation (PPKSK)

in order to maintain financial system stability.

This is crucial considering the interconnectedness

and/or various intricacies of task implementation

and authority. Additionally, to further facilitate

coordination between Bank Indonesia and the

Indonesia Financial Services Authority (OJK) and

follow-up PPKSK Act implementation, as of 15th

June 2017, eight implementation guidelines for

BI-OJK cooperation and coordination mechanisms

had been drawn up and executed, signed by

the OJK Chairman and BI Governor. In terms

of following up PPKSK implementation, Bank

Indonesia has also strengthened coordination with

the Deposit Insurance Corporation (LPS), entering

the implementation phase in the first semester of

2017 through data and information exchange, joint

research and the implementation of cooperation

agreements concerning the purchase by Bank

Indonesia of tradeable government securities (SBN)

held by LPS.

Gunungan are puppets that are shaped like a mountain. Gunungan puppets signify the start and end

of a performance, playing the roles of land, jungle, roads and so on, accompanied by dialogue from the

puppeteer. Gunungan impart philosophical lessons about wisdom. In terms of financial system stability,

gunungan can be interpreted as FSS conditions that may be influenced by sources of imbalances with risks

that could become systemic.

In general, financial system stability in Indonesia was relatively stable throughout the

first semester of 2017, supported by a solid capital base in the banking industry. Stable

financial system stability was reflected in the Financial System Stability Index (FSSI)

and Banking Systemic Risk Index (BSRI), which improved on their previous positions,

particularly in terms of bank capital and liquidity along with stable financial markets.

Nevertheless, several global and domestic risks continued to demand vigilance. At

home, a high non-performing loans (NPL) ratio and moderating bank intermediation

function as of May 2017 represented the main challenges. Globally, however, risks

continued to blight the global financial markets stemming from the Federal Funds

Rate (FFR) hike and the Federal Reserve’s plan to unwind its balance sheet, which

influenced regional financial markets.

Against a backdrop of maintained financial system stability, domestic financial

imbalances lingered with the potential to trigger vulnerabilities in the financial system,

including bank lending procyclicality during the financial cycle contraction and limited

fiscal space despite government efforts to improve fiscal performance and boost

revenues. In addition, high-risk nonbank corporate external debt, especially at indebted

corporations failing to hedge, as well as the large portion of non-resident holdings in

domestic financial markets were also a threat to domestic financial instability due to

the growing risk of a potential sudden capital reversal.

FINANCIAL SYSTEM STABILITY

01


2 BANK INDONESIA

Global Risks

• Improving global economic growth

• Stronger emerging market economies (EMEs)

• Rising coal and metal prices

• Falling global oil and crude palm oil (CPO) prices

• Increasing world trade volume (WTV)

Domestic Risks

• Controlled inflation

• Stable economic growth

• BOP surplus and stable current account deficit below

3% of GDP

• Stable and appreciating rupiah exchange rate

• Slower credit growth

• Broader fiscal space

Domestic Financial Imbalances

FINANCIAL SYSTEM STABILITY WAS SOLID IN LINE WITH GLOBAL ECONOMIC GAINS AND DOMESTIC ECONOMIC STABILITY

Improving financial system stability

Bank Lending Procyclicality

and Financial Cycle

Contraction

Limited Fiscal Space Large Non-Resident Holdings in the

Domestic Financial Markets

High-risk Nonbank Corporate

External Debt

3,00

1,50

2,00

0,50

2,50

1,00

0,00

2002

MO

1

2002

MO

7

2003

MO

1

2003

MO

7

2004

MO

1

2004

MO

7

2005

MO

1

2005

MO

7

2006

MO

1

2006

MO

7

2007

MO

1

2007

MO

7

2008

MO

1

2008

MO

7

2009

MO

1

2009

MO

7

2010

MO

1

2010

MO

7

2011

MO

1

2011

MO

7

2012

MO

1

2012

MO

7

2013

MO

1

2013

MO

7

2014

MO

1

2014

MO

7

2015

MO

1

2015

MO

7

2016

MO

1

2016

MO

7

2017

MO

1

2017

MO

6

Suspected Crisis Normal Financial System Stability Index (FSSI)

Juni 170.82

3BANK INDONESIA

Financial Markets Households and Corporations

The Financial System Stability Condition

Financial System InfrastructureBanking and IKNB Responds of Bank

Indonesia’s Policy

slowed and the banking industry consolidated. The

positive global economic developments edged up

world trade volume (WTV) and kept international

commodity prices high. Meanwhile, the FFR hike

was predicted to occur just once at the end of

2017, while the Federal Reserve’s plan to unwind

its balance sheet was expected to be announced in

September 2017.

International commodity prices tended to vary

in the first half of 2017. The major export

commodities from Indonesia, such as coal and

metals, increased on their positions at yearend in

2016 (Graph 1.1). Demand from China elevated

metal prices, while CPO prices tracked a downward

trend due to abundant supply, including production

from Malaysia. The global oil price also decreased

on the previous period (Graph 1.2). The price of

Brent averaged USD50.1 per barrel in the reporting

period, down from USD52.4 per barrel. The decline

was most significant in June 2017, when oil hit its

lowest price for the year at USD44.21 per barrel.

The weak oil price was attributable to abundant

global supply after the US bolstered production

and inventory, which stoked market pessimism

regarding the impact of the production cuts agreed

by OPEC.

Congruent with less uncertainty, the global stock

markets rallied in the first semester of 2017.

Consequently, bullish stock markets flourished in

advanced and developing economies around the

world (Graph 1.3).

Global financial system risks eased in the first half of

2017. The global economic recovery persisted with

the support of robust economic growth in advanced

and developing economies. Furthermore, uncertainty

in the financial markets subsided as confidence

grew concerning the timing of the Federal Funds

Rate (FFR) hike and planned normalisation of the

Federal Reserve’s balance sheet. In the commodity

markets, the prices of major export commodities

from Indonesia, such as coal and metals, remained

high, thereby buoying national export performance.

The oil price, however, continued to slide.

The global economy continued to expand on

the back of growth in advanced and developing

economies. The US economy posted gains in the

first semester of 2017 as investment and private

consumption improved in line with promising

labour market data (Table 1.1). In Europe, economic

growth also accelerated thanks to consumption

and export activities. Geopolitical and financial

risks in Europe eased towards the end of the first

semester of 2017 after the Greece debt crisis

softened, which allowed the European Central

Bank (ECB) to maintain an accommodative policy

stance. Meanwhile, economic growth in developing

countries was underpinned by faster growth in

China on solid consumption and improving exports.

India’s economy, however, moderated as exports

1.1. Risks in the Global and Regional Financial Markets


4 BANK INDONESIA

Jan-

16Ja

n-16

Ja

n-16

Ja

n-16

Ja

n-16

Ja

n-16

Fe

b-16

Feb-

16

Feb-

16

Feb-

16

Feb-

16M

ar-1

6M

ar-1

6 M

ar-1

6 M

ar-1

6 M

ar-1

6 M

ar-1

6Ap

r-16

Apr-1

6 Ap

r-16

Apr-1

6 Ap

r-16

May

-16

May

-16

May

-16

May

-16

May

-16

May

-16

Jun-

16Ju

n-16

Ju

n-16

Ju

n-16

Ju

n-16

Jul-1

6Ju

l-16

Jul-1

6 Ju

l-16

Jul-1

6 Ju

l-16

Aug-

16Au

g-16

Au

g-16

Au

g-16

Au

g-16

Sep-

16Se

p-16

Sep

-16

Sep-

16

Sep-

16

Sep-

16O

ct-1

6O

ct-1

6 O

ct-1

6 O

ct-1

6 O

ct-1

6N

ov-1

6N

ov-1

6 N

ov-1

6 N

ov-1

6 N

ov-1

6 N

ov-1

6De

c-16

Dec-

16

Dec-

16

Dec-

16

Dec-

16Ja

n-17

Jan-

17

Jan-

17

Jan-

17

Jan-

17

Jan-

17

Feb-

17Fe

b-17

Fe

b-17

Fe

b-17

Fe

b-17

Mar

-17

Mar

-17

Mar

-17

Mar

-17

Mar

-17

Mar

-17

Apr-1

7Ap

r-17

Apr-1

7 Ap

r-17

Apr-1

7M

ay-1

7M

ay-1

7 M

ay-1

7 M

ay-1

7 M

ay-1

7 M

ay-1

7Ju

n-17

30

40 49,66

50

20

60

Table 1.1. Global Economic Outlook

Source: Bloomberg

Source: Bloomberg

Source: Bloomberg

Source: Bloomberg

Global Economic Outlook

GDP

Realisation Projected for 2017

2016 2017 WEO-IMF Consensus Forecast

I II III IV I Apr-17 Jul-17 Jun-17 Jul-17

Global 3.3 3.3 3.3 3.6 3.9 3.5 3.5 3.8 3.8

Advanced Economies 1.4 1.4 1.6 1.9 2.0 2.0 2.0 2.0 2.0

United States 1.4 1.2 1.5 1.8 2.0 2.3 2.1 2.2 2.2

Europe 1.7 1.7 1.7 1.9 1.9 1.7 1.9 1.8 1.9

Japan 0.5 0.9 1.1 1.7 1.5 1.2 1.3 1.4 1.4

Emerging and Developing Economies 5.0 5.0 4.8 5.1 5.5 4.5 4.6 5.3 5.4

China 6.7 6.7 6.7 6.8 6.9 6.6 6.7 6.6 6.6

India 7.9 7.1 7.4 7.0 7.0 7.2 7.2 7.3 7.3

12,000 250

8,000150

4,000

50

10,000 200

6,000100

2,000

00

Jan-

07M

ay-0

7Se

p-07

Jan-

08M

ay-0

8Se

p-08

Jan-

09M

ay-0

9Se

p-09

Jan-

10M

ay-1

0Se

p-10

Jan-

11M

ay-1

1Se

p-11

Jan-

12M

ay-1

2Se

p-12

Jan-

13M

ay-1

3Se

p-13

Jan-

14M

ay-1

4Se

p-14

Jan-

15M

ay-1

5Se

p-15

Jan-

16M

ay-1

6Se

p-16

Jan-

17M

ay-1

7

Graph 1.1. Major Export Commodity Prices

WorldEM ASIA

US (Dow Jones)Japan (Nikkei)

England (FTSE)

India (SENSEX)

Hongkong (Hang Seng)

Shanghai (SHCOMP)

Kuala Lumpur (KLCI)Strait Times (STI)

PhilippineThailand (SET)

Vietnam

0% 2% 6%4% 8% 10% 12% 14% 16% 18% 20%

Indonesia (IHSG)

8.5%

8.3%5.2%

4.2%

1.4%

17.5%16.7%

11.6%8.3%

2.5%

14.9%

15.3%

10.06%

18.9%

Thailand

Philippines

Germany

China

Malaysia

30 Jun 2017

31 Des 2016

Indonesia

Turkey

0 50 150100 200 250 300

Brazil

Source: Bloomberg

USD/Metric Ton (Copper)MYR/Metric Ton (Crude Palm Oil)

USD/barrel

USD/Metric Ton

Copper Crude Palm Oil Coal (rhs)

Graph 1.2 Brent Oil Price

Graph 1.3. JCI and Global Stock Indexes Graph 1.4. CDS in Advanced Economies and Regional

5BANK INDONESIA





The domestic economic risks were contained during

the first semester of 2017, supported by maintained

macroeconomic stability in line with controlled

inflation and stable economic growth. Global

pressures on Indonesia’s external balance eased, as

evidenced by the balance of payments (BOP) surplus

and current account deficit consistently below

3% of GDP. On the other hand, the stable and

appreciating rupiah was sustained by favourable

domestic macroeconomic dynamics and milder

external risks.

Investment and exports have supported relatively

stable economic growth in Indonesia. The national

economy expanded at 5.01% (yoy) in the first two

quarters of 2017, up slightly from 4.94% (yoy)

in the fourth quarter of 2016 (Table 1.2). Strong

investment and improving export performance

reinforced economic growth, which offset

moderating household consumption. Investment

accelerated on building investment as the

Government ramped up infrastructure spending

and the private sector became more engaged

1.2. Domestic Economic Risks

Source: BPS-Statistics Indonesia

Table 1.2 National Economic Growth in Indonesia

Components of GDP 2015 2016

20162017

I II III IV I II

Household Consumption 4.96 4.97 5.07 5.01 4.99 5.01 4.94 4.95

Consumption of Non-profit Institutions

Serving Households

-0.62 6.40 6.71 6.64 6.72 6.62 8.05 8.49

Government Consumption 5.32 3.43 6.23 -2.95 -4.05 -0.15 2.68 -1.93

Investment 5.01 4.67 4.18 4.24 4.80 4.48 4.78 5.35

Building Investment 6.11 6.78 5.07 4.96 4.07 5.18 5.87 6.07

Non-Building Investment 1.95 -1.20 1.70 2.16 7.07 2.45 1.49 3.27

Exports -2.12 -3.29 -2.18 -5.65 4.24 -1.74 8.21 3.36

Imports -6.41 -5.14 -3.20 -3.67 2.82 -2.27 5.12 0.55

GDP 4.88 4.92 5.18 5.01 4.94 5.02 5.01 5.01

persen, yoy

in investment projects. Furthermore, exports

rebounded significantly in the first quarter of 2017

on rising prices but subsequently slowed in the

following period due to a slump of manufacturing

exports on dwindling demand from advanced

economies. Households were inclined to consume

due to controlled inflation, which maintained public

purchasing power, coupled with the seasonal spike

in demand during Eid-ul-Fitr that coincided this

year with the second quarter. Nevertheless, the

purchasing power of middle-class consumers and

low-income earners achieved more limited gains,

as evidenced by slower income growth. Income

indicators, including the real wages of builders and

farmers, declined, while the farmers’ terms of trade

(ToT) surplus narrowed. On the other hand, the

upper-middle class was less inclined to consume,

showing a greater propensity to save, with personal

term deposits exceeding Rp2 billion and personal

tradeable government securities (SBN) accelerating

as well as the portion of individuals trading on the

stock market.

Inflation was kept under control in June 2017, thus

supporting the 2017 inflation target of 4.0±1%.

The Consumer Price Index (CPI), as a measure of


6 BANK INDONESIA

headline inflation, stood at 2.38% (ytd) in June

2017 or 4.37% (yoy) annually (Graph 1.5). Low

and stable inflation was achieved thanks to the

considerable efforts of the Government and close

policy coordination with Bank Indonesia during the

approach to Eid-ul-Fitr. By component, volatile foods

(VF) were the main drag on inflation, recording a

lower rate than the seasonal average, while low

core inflation was also maintained. Inflationary

pressures on volatile foods were lower than the

seasonal average for Eid-ul-Fitr over the past three

years due to concerted efforts to maintain the

supply of foodstuffs. Low core inflation was also

maintained in June 2017, with the help of weak

domestic demand, anchored inflation expectations

and a stable exchange rate. Conversely, intense

inflationary pressures on administered prices (AP)

remained in June 2017, primarily as a result of

third-phase adjustments to electricity rates for non-

subsidised 900VA subscribers, coupled with hikes to

airfares, intercity fares and railway tickets. Moving

forward, low inflation is expected to persist, within

the inflation target, supported by a narrow output

gap, stable rupiah exchange rate, lower global

inflation and less risk of further AP hikes.

A significant capital and financial account surplus,

combined with a healthy current account deficit, has

improved the external balance. Indonesia’s balance

of payments (BOP) recorded a USD0.7 billion surplus

in the second quarter of 2017, bolstered by a capital

and financial account surplus that exceeded the

current account deficit (Graph 1.6). After affirmation

that Indonesia’s sovereign rating had been upgraded

to investment grade, strong investor confidence in

the national economic outlook boosted the capital

and financial account surplus. Larger surpluses of

direct investment and portfolio investment swelled

the capital and financial account to USD8.0 billion

and USD5.9 billion in the first and second quarters

of 2017 respectively. On the other hand, the current

account deficit was maintained at the healthy level

of below 3% of GDP in the second quarter of 2017,

despite increasing slightly to 1.96% of GDP from

0.98% in the first quarter of 2017 and 1.8% at the

end of 2016. Consequently, the position of official

reserve assets increased from USD121.9 billion at

the end of the first quarter of 2017 to USD123.1

billion at the end of the subsequent period, which

was equivalent to 8.6 months of imports and

servicing government external debt and well above

the international standard of three months.

The rupiah remained stable and tracked an

appreciating trend in the first semester of 2017,

climbing 1.08% (ytd) from Rp13,473 to Rp13,328/

USD (Graph 1.6 and Graph 1.7). The rupiah

strengthened as the corporate sector sold foreign

exchange and an influx of non-resident capital was

drawn to the domestic financial markets, while

regional markets also achieved greater efficiency

(Graph 1.8). In addition, sound macroeconomic

conditions and milder external risks also buoyed

rupiah appreciation. Positive domestic sentiment

stemmed from controlled inflation in June 2017,

within the target corridor, and affirmation that

S&P had upgraded Indonesia’s sovereign rating to

investment grade. Externally, risks to the rupiah

exchange rate were contained. The 25bps hike to

the Federal Funds Rate (FFR) in June 2017 was fully

anticipated by the markets. Furthermore, weak US

macroeconomic data stoked concerns amongst

investors whether the Federal Reserve would again

raise its reference rate in the coming months.

Rupiah volatility was low throughout the year,

below Indonesia’s peer countries (Graph 1.10).

7BANK INDONESIA





7 % %

5

3

1

6

4

2

0

2013 2014

GDP Growth Inflation (rhs)

2015 2016 2017

Jan

May

Mar Ju

lSe

pN

ov10

8

5

2

9

6

3

7

4

1

0

Jan

May

Mar Ju

lSe

pN

ov Jan

May

Mar Ju

lSe

pN

ov Jan

Jan

May

May

Mar

MarJu

lSe

pN

ov

Graph 1.5 CPI Inflation and GDP Growth

Source: BPS-Statistics Indonesia

Source: Reuters

Source: Reuters, Bloomberg, processed

Source: Bank Indonesia

4

0

-6

-12

Services Account Trade Balance Primary Income Account

CA/GDP (%) (rhs)Secondary Income Account

Preliminary Data Projected Data

Current Account

2

-4

-10

-2

-8

6

2

-4

-10

4

-2

I I I IIII III IIIII II II IIIV IV IV

-8

0

-6

-12

-14* **

* **

Graph 1.6 Balance of Payments

3-Ja

n8-

Jan

13-Ja

n18

-Jan

23-Ja

n28

-Jan

2-Fe

b7-

Feb

12-F

eb17

-Feb

22-F

eb27

-Feb

4-M

ar9-

Mar

14-M

ar19

-Mar

24-M

ar29

-Mar

3-Ap

r13

-Apr

18-A

pr23

-Apr

28-A

pr3-

May

8-M

ay13

-May

18-M

ay23

-May

28-M

ay2-

Jun

7-Ju

n12

-Jun

17-Ju

n22

-Jun

13.500(Rp)

13.300

13.400

13.200

13.450

1336113338

13348

13345

13304

1332113309

13328

1329813.250

IDR/USD

Quarterly Average

Monthly Average

13.350

13.150

13.100

Graph 1.7 Rupiah Exchange Rate

Source: Reuters

30%

15

25

10

20

5

0TRY ZAR

2016 YTD 2017 Average YTD-2017

BRL KRW THB INR SGD MYR PHP IDR

Graph 1.8 Appreciation and Depreciation against the USD

4.000USD mn

Government Islamic Securities (SBSN)

Stocks

Government Debt Securities (SUN)

Bank Indonesia Certificates (SBI)

IDR/USD

IDR/USD (rhs)

3.000

2.000

1.000

-1.000

-2.000

-3.000

-4.000

0

14,500

14,000

13,500

13,000

12,500

12,000

Jan-

15Fe

b-15

Mar

-15

Apr-1

5M

ay-1

5Ju

n-15

Jul-1

5Au

g-15

Sep-

15O

ct-1

5N

ov-1

5De

c-15

Jan-

16Fe

b-16

Mar

-16

Apr-1

6M

ay-1

6Ju

n-16

Jul-1

6Au

g-16

Sep-

16O

ct-1

6N

ov-1

6De

c-16

Jan-

17Fe

b-17

Mar

-17

Apr-1

7M

ay-1

7Ju

n-17

data s.d 30 Jun-17

Graph 1.9 Non-Resident Capital Flows Graph 1.10 Exchange Rate Volatility (ytd) in the Region

Source: Reuters, Bloomberg, processed

-20,0 -15,0 -10,0 -5,0 0,0 5,0 10,0 15,0

%

TRY

MYR

PHP

EUR

IDR

KRW

THB

INR

BRL

ZAR

0.08

4.51

-1.72

-1.60

7.96

1.08

5.39

5.61

5.18

5.09

-16.85

-5.57

-4.88

-2.19

-0.19

1.60

1.62

2.14

9.60

11.17Data as of 30th June 2017

Point-to-Point Average

YTD 2017 vs 2016

2014 2015 2016 2017

USD, Billions

Data as of 30th June 2017

Data as of 30th June 2017

18.716.6

18.6

25.3

13.6

20.7

9.1

13.3

5.16.1

5.06.1

5.37.4

4.8

13.7

4.7

7.1

2.3

8.7


8 BANK INDONESIA

bank that could trigger systemic risk in the banking

industry and spread to the financial system. BSRI for

large banks and nonbanks was maintained within

the normal-stable zone throughout the first half of

2017 despite relatively tight liquidity during Eid-ul-Fitr

at the large banks. In June 2017, BSRI stood at 1.40

(threshold of 3.8), indicating that systemic pressures

on individual banks were contained.

In terms of the financial markets, risk indicators for the

stock and bond markets as well as the rupiah exchange

rate were observed to improve. Furthermore,

risks in the SBN market and rupiah exchange rate

were relatively stable during the first half of 2017.

Concerning the stock market, the Jakarta Composite

Index (JCI) rallied 10.06% on the previous period to

a level of 5,829.71, boosted by better-than-expected

global economic growth and higher profits recorded

by individual issuers. The domestic stock market

gains were consistent with other regional bourses,

including Thailand, Malaysia and the Philippines.

Non-resident investors booked a net buy on bullish

sentiment totalling Rp18.24 trillion in the reporting

period, dominated by trade sector stocks. The SBN

market also performed well, with the Inter-Dealer

Market Association (IDMA) index rallying 4.59% from

99.09 in the previous period to 103.64. Furthermore,

the rupiah exchange rate strengthened against the

USD from Rp13,473 at the end of December 2016 to

Rp13,368/USD at the end of June 2017. In addition to

better-than-expected global economic performance,

the upgrade of Indonesia’s credit rating to investment

grade, affirmed by S&P’s, also contributed to rupiah

appreciation.

1 FMSI consists of several financial market indicators, covering the money market, bond market, stock market, foreign exchange market, credit default swaps (CDS) and external debt. 2 FISI consists of various pressure indicators, intermediation indicators and efficiency indicators of financial institutions, in particular the banking industry.3 BSRI is a composite of the credit risk, liquidity risk, exchange rate risk, SBN risk and capital risk indexes.

Despite a moderating bank intermediation function

and escalating credit risk in the banking industry,

financial system stability was well maintained during

the first half of 2017 with the support of a solid capital

base in the banking industry and relatively stable

volatility in the financial markets. Such dynamics were

evidenced by the Financial System Stability Index

(FSSI), which remained in the normal-stable zone at

0.82 in the middle of 2017, improving from 0.88 in

the previous period and well below the threshold of 2.

Nevertheless, the FSSI was observed to spike in the first

semester of 2017 as credit risk in the banking industry

intensified but returned to normal shortly thereafter.

By component, the Financial Market Stability Index1

(FMSI) was the main contributor to FSSI gains in the

first half of the year, improving from 1.04 to 0.93 on

the back of lower bond yields, stock market volatility,

exchange rate volatility, credit default swaps (CDS)

and external debt to GDP. Conversely, the Financial

Institution Stability Index2 (FISI) deteriorated from 0.63

at the end of 2016 to 0.67 in the middle of 2017

as a result of accumulating credit risk, sluggish bank

intermediation and less liquidity due to the cyclical

effect of Eid-ul-Fitr. On the other hand, the banks

managed to enhance efficiency, while maintaining a

large and stable capital base.

The Banking Systemic Risk Index3 (BSRI) also pointed

to maintained financial system stability. BSRI is a

measure of potential risk originating from an individual

1.3 Financial System Stability

9BANK INDONESIA





Solid financial system stability at home was also

a corollary of promising global and domestic

economic developments during the reporting period.

Nevertheless, the transmission of milder risks and

favourable economic developments through the trade

channel was comparatively weak in line with soft

demand from global investors, the domestic corporate

sector and households, which translated into slower

growth of bank intermediation, particularly credit

growth, and relatively high credit risk despite the banks

successfully increasing efficiency and profitability.

The banking industry maintained performance despite

sluggish intermediation and persistently high credit risk

thanks to a solid capital base and adequate liquidity.

The Capital Adequacy Ratio (CAR), as a measure of

capital in the banking industry, was high and stable

at 22.52% in the middle of 2017, down slightly from

22.69% in 2016. Meanwhile, the cyclical dynamics of

Eid-ul-Fitr were the main drag on bank liquidity after

increasing in the first quarter of 2017 due to financial

expansion by the government. The erosion of liquidity

in the banking system was reflected in the ratio of

liquid assets to deposits, which stood at 21.15% in

the reporting period, down from 21.61% at the end

of 2016.

The banking industry confirmed a depressed

intermediation function. Credit growth in the middle

of 2017 was stifled by low demand for new loans.

The corporate sector gains and improving repayment

capacity achieved in the first half of the year failed

to stimulate credit growth. Additionally, alternative

funding sources from the capital market were

becoming more attractive, including initial public

offerings (IPO) and rights issues, bonds, medium-term

notes (MTN) and Negotiable Certificates of Deposit

(NCD). Furthermore, bond rates fell faster than

lending rates. On the supply side, the banks became

more selective when lending due to stubbornly high

credit risk, which forced the banks to apply more

stringent lending standards despite Bank Indonesia

reducing the policy rate. Consequently, credit growth

moderated from 7.86% (yoy) in the second semester

of 2016 to 7.75% (yoy) in the first semester of 2017.

Non-performing loans (NPL), as a proxy of credit risk,

deteriorated in the middle of the first semester of

2017, reaching 3.04%, but recovered towards the

end of the semester to 2.96%, compared to 2.93%

at the end of 2016. The lower NPL rate at the end

of the first semester was in line with slower nominal

NPl growth and early signs of credit expansion despite

historical credit risk remaining high.

On the other hand, bank intermediation through

deposits tended to improve. Deposit growth stood

at 10.31% at the end of the first semester of 2017,

up from 9.60% at the end of 2016, before slowing

again in June 2017 due to cyclical Eid-ul-Fitr trends.

The successful Tax Amnesty program was the main

contributor to deposit growth along with financial

expansion by the government and banks less inclined

to lend.

The banking industry enhanced efficiency compared

to conditions one year earlier. The BOPO efficiency

ratio improved from 82.85% in December 2016 to

79.48% in June 2017. Congruently, the banks also

maintained profitability, with the return on assets

(ROA) increasing from 2.17% to 2.42%. The banks

improved their ROA by maintaining a stable net


10 BANK INDONESIA

interest margin (NIM) at 5.21% at the end of the first

semester of 2017 despite moderating slightly from

5.47% at the end of 2016. The relatively high NIM

ratio was indicative of the broad spread between the

interest income generated by banks and the amount

of interest paid out.

In general, the asset composition of financial

institutions was dominated by the banking industry,

accounting for 72.06% of the total in the first

semester of 2017. Despite a declining share compared

to conditions in the previous period, banking industry

assets increased from Rp6,729 trillion to Rp6,754

trillion in the reporting period. Considering most

financial institution assets are concentrated in the

banking industry, the associated risks demand

vigilance and intensive mitigation measures, which are

also inextricably linked to the monitoring of risks and

developments in other industries contained under the

umbrella of the financial system, including the financial

markets, in order to maintain financial system stability.

Graph 1.11 Financial System Stability Index (FSSI)

3

1.5

2

0.5

2.5

1

0

2002

MO

1 20

02M

O7

2003

MO

1 20

03M

O7

2004

MO

1 20

04M

O7

2005

MO

1 20

05M

O7

2006

MO

1 20

06M

O7

2007

MO

1 20

07M

O7

2008

MO

1 20

08M

O7

2009

MO

1 20

09M

O7

2010

MO

1 20

10M

O7

2011

MO

1 20

11M

O7

2012

MO

1 20

12M

O7

2013

MO

1 20

13M

O7

2014

MO

1 20

14M

O7

2015

MO

1 20

15M

O7

2016

MO

1 20

16M

O7

2017

MO

1 20

17M

O6

Suspected Crisis Suspected CrisisNormal NormalFSSI FSSI


Graph 1.13 Financial Market Stability Index (FMSI)

3.50

3.00

2.50

2.00

1.50

1.00

0.50

0.00

2002

MO

1 20

02M

O7

2003

MO

1 20

03M

O7

2004

MO

1 20

04M

O7

2005

MO

1 20

05M

O7

2006

MO

1 20

06M

O7

2007

MO

1 20

07M

O7

2008

MO

1 20

08M

O7

2009

MO

1 20

09M

O7

2010

MO

1 20

10M

O7

2011

MO

1 20

11M

O7

2012

MO

1 20

12M

O7

2013

MO

1 20

13M

O7

2014

MO

1 20

14M

O7

2015

MO

1 20

15M

O7

2016

MO

1 20

16M

O7

2017

MO

1 20

17M

O6

Suspected Crisis NormalFMSI


Graph 1.12 Financial Institution Stability Index (FISI)

3

1.5

2

0.5

2.5

1

0

2002

MO

1 20

02M

O7

2003

MO

1 20

03M

O7

2004

MO

1 20

04M

O7

2005

MO

1 20

05M

O7

2006

MO

1 20

06M

O7

2007

MO

1 20

07M

O7

2008

MO

1 20

08M

O7

2009

MO

1 20

09M

O7

2010

MO

1 20

10M

O7

2011

MO

1 20

11M

O7

2012

MO

1 20

12M

O7

2013

MO

1 20

13M

O7

2014

MO

1 20

14M

O7

2015

MO

1 20

15M

O7

2016

MO

1 20

16M

O7

2017

MO

1 20

17M

O6


Graph 1.14 Banking Systemic Risk Index (BSRI)

4.5

2.5

3.5

1.5

0.5

4.0

2.0

3.0

1.0

0.0

Industry Index 1% Percentile

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017


11BANK INDONESIA





Source: Indonesia Financial Services Authority (OJK), processed

2.89%

1.31%

11.20%

2.71% 4.93%

0.13%

0.17% 0.51%

4.08%

72.06%

Banking Industry

Islamic Banks

Rural Banks

Insurance Companies

Pension Funds

Finance Companies

Venture Capital Firms

Guarantee Companies

Pawn Brokers

Mutual Funds NAV

Graph 1.15 Asset Composition of Financial Institutions

1.4 Domestic Financial Imbalances

1.4.1. Bank Lending Procyclicality and the

Financial Cycle Contraction

The financial cycle of Indonesia (SKI) experienced

a contractionary phase during the first semester

of 2017 (Graph 1.16), which was primarily caused

by the ongoing credit slump. Credit growth has

continued to slide since the end of 2014, reaching

7.75% (yoy) in the first semester of 2017. Credit

growth was recorded at 7.86% (yoy) in the previous

period. Sluggish credit growth has been attributed

to tepid increases in aggregate demand, as reflected

by economic growth of 5.01% (yoy), which was

nevertheless up slightly from 4.94% (yoy) at the

end of 2016.

The troubling impact of bank lending procyclicality

on economic growth has been the deteriorating NPL

ratio in the banking industry, which increased from

2.93% in the second semester of 2016 to 2.96% in

the first semester of 2017. Nonetheless, the level of

non-performing loans (NPL) in the banking sector

Graph 1.16 Financial Cycle

1994

Q1

1994

Q4

1995

Q3

1996

Q2

1997

Q1

1997

Q4

1998

Q3

1999

Q2

2000

Q1

2000

Q4

2001

Q3

2002

Q2

2003

Q1

2003

Q4

2004

Q3

2005

Q2

2006

Q1

2006

Q4

2007

Q3

2008

Q2

2009

Q1

2009

Q4

2010

Q3

2011

Q2

2012

Q1

2012

Q4

2013

Q3

2014

Q2

2015

Q1

2015

Q4

2016

Q3

2017

Q2

0

0.02

(0.02)

(0.04)

(0.06)

(0.08)

(0.10)

0.04

0.06

0.08

0.101995Q2Q

2000Q2Q

2013Q3

Financial Cycle (lhs) Peak TroughKrisis

2005Q2Q

2009Q3Q2

Graph 1.17 Banking Lending Procyclicality

40

35

30

25

20

15

10

5

0

8(%)(%)

7

6

5

4

3

2

1

0

2001

Q3

2002

Q2

2003

Q1

2003

Q4

2004

Q3

2005

Q2

2006

Q1

2006

Q4

2007

Q3

2008

Q2

2009

Q1

2009

Q4

2010

Q3

2011

Q2

2012

Q1

2012

Q4

2013

Q3

2014

Q2

2015

Q1

2015

Q4

2016

Q3

2017

Q2

Credit (yoy)GDP (rhs)

Source: Bank IndonesiaSource: Bank Indonesia


12 BANK INDONESIA

Graph 1.18 Components of State Revenue in the First Semester of 2017

60.00

47.0

43.140.6

39.4

43.2

52.2

42.8

56,8

46.044.7

40.843.0

40.00

20.00

50.00

30.00

10.00

Tax Non-Tax Revenues Total Revenue and Grants

2014 20162015 2017*

%LKPP s.d Juni 2017

Source: Ministry of Finance, processedSource: Ministry of Finance, processed

Graph 1.19 Growth of State Revenue Components in the First Semester of 201725,0

20,0

15,0

10,0

5,0

0

-5,0

-10,0

-15,0

-20,0 Jan

Feb

Mar Ap

rM

ay Jun Jul

Aug

Sep

Oct

Nov

De

cJa

nFe

bM

ar Apr

May Jun Jul

Aug

Sep

Oct

Nov

De

cJa

nFe

bM

ar Apr

May Jun Jul

Aug

Sep

Oct

Nov

De

cJa

nFe

bM

ar Apr

May Jun

2014 2015 2016 2017

Non-Oil and Gas Tax Natural Resources Non-Tax RevenueOil and Gas TaxNon-Natural Resources Non-Tax Revenue

International Trade Tax GrantsTotal

*Preliminary realisation of Draft State Budget in 2017 (%)

has remained well below the 5% threshold. The high

level of NPL has influenced the lending decisions

of the banking industry, becoming more selective

and prudent. Consequently, lending procyclicality

demands vigilance considering that upon entering

an downswing, economic players still require the

support of bank loans to avoid deeper declines.

1.4.2 Limited Fiscal Space

The Government enjoyed broader fiscal space in

the first semester of 2017 due to limited spending

absorption coupled with increasing revenues. The

realisation of financial operations as of June 2017

recorded a deficit equivalent to 1.3% of GDP,

narrowing from 1.9% of GDP in June 2016 due to

more limited expenditure realisation in June 2017.

Meanwhile, revenues were observed to increase

slightly on the same period one year earlier but with

a lower ratio of tax revenue.

State revenues increased in the first semester of

2017. As of June 2017, state revenues had reached

43% of target, compared to 40.8% in the previous

year (Graph 1.18), with Non-Tax State Revenues

(PNBP) the main contributor as a result of revenues

from natural resources. Notwithstanding the gains

on the same period one year earlier, tax revenue

was shown to decline, with non-oil and gas taxes

cited as the main drag (Graph 1.19). Furthermore,

tax revenue from the retail sector and income tax

also declined, while VAT revenue was eroded by

domestic VAT and limited imports.

Government expenditure, including central

government spending and regional stimuli,

remained limited (Graph 1.20). As of June 2017,

state expenditure had only grown by 3.2%, yoy),

down from 11.1% (yoy) in the previous year. Central

government spending on procurement and capital

was restrained by efforts to maintain absorption on

target. After spiking in 2016, procurement spending

and capital spending was reined in during the first

half of 2017 due to greater government budget

allocation to infrastructure in line with the target.

Subsidies were throttled back by gradually cutting

electricity subsidies to 900VA subscribers throughout

2017. Regional subsidies were also rolled back,

which manifested in a smaller Profit Sharing Fund

(DBH) and negative growth of the physical Special

Allocation Fund (DAK). Such developments were in

13BANK INDONESIA





4 On 1st April 2017, the Government issued Minister of Finance Regulation No. 50/PMK.07/2017 concerning Regional Transfer and Village Fund (TKDD) Management to improve the allocation

and optimisation of TKKD utilisation.

Graph 1.20 Components of State Expenditure in the First Semester of 2017

sd Jun

2008

sd Jun

2009

sd Jun

2010

sd Jun

2011

sd Jun

2012

sd Jun

2013

sd Jun

2014

sd Jun

2015

sd Jun

2016

sd Jun

2017

500

200

400

100

600

300

Rp T

1. Personnel Expenditure 5. Subsidies2. Procurement 6. Grant Expenditure3. Capital Spending 7. Social Assistance4. Debt Obligations 8. Other Expenditure

Source: Ministry of Finance, processed

line with policy to change the transfer uptake for

infrastructure development to proposal-based4.

Broad fiscal space minimised the risks to the

financial system. Fiscal sustainability in the first half

of the year was maintained, as indicated by a fiscal

deficit of just 1.3% of GDP, down from 1.9% of

GDP in 2016. Furthermore, restrained government

expansion alleviated pressures on liquidity.

1.4.3 High-Risk Nonbank Corporate

ExternalDebt

External debt has increased in Indonesia as the

global and domestic economies have shown signs

of improvement. External debt stood at USD335.29

billion in the first semester of 2017, up 2.85% (yoy)

from USD317.78 billion at the end of 2016. In terms

of risk, the sensitivity of external debt in Indonesia

to currency risk tended to ease, as evidenced by

the lower external debt to GDP ratio, falling from

34.51% in the second semester of 2016 to 34.44%

in the reporting period.

External debt composition can be reviewed

from the perspective of loan type. Departing

from earlier conditions when the private sector

constantly dominated external debt rather than the

government or central bank, in the first semester

of 2017 it was the government that overtook

the other sectors to dominate the composition of

external debt, with a value of USD166.28 billion or

49.59% of the total. Such developments confirmed

a significant 11.40% bump on the USD154.88

billion recorded in the previous period. On the other

hand, the external debt of the central bank tracked

a fluctuating trend, falling from USD5.43 billion in

the first semester of 2016 to USD3.41 billion at the

end of 2016 and then increasing to USD4.00 billion

in the first semester of 2017.

The structure of private external debt is categorised

as bank and nonbank external debt. In the middle

of 2017, the share of private sector external debt

attributable to nonbank corporations accounted

for 82.35% of the total, while the banking industry

commanded a 17.65% share. Congruent with


14 BANK INDONESIA

35

25

20

15

10

120

100

80

60

40

20

140

Jan-

08M

ay-0

8Se

p-08

Jan-

09M

ay-0

9Se

p-09

Jan-

10M

ay-1

0Se

p-10

Jan-

11M

ay-1

1Se

p-11

Jan-

12M

ay-1

2Se

p-12

Jan-

13M

ay-1

3Se

p-13

Jan-

14M

ay-1

4Se

p-14

Jan-

15M

ay-1

5Se

p-15

Jan-

16M

ay-1

6Se

p-16

Jan-

17M

ay-1

7

160 40

30Nonbanks

Banks (rhs)

Private

140

120

100

80

60

40

20

160

Jan-

08Ap

r-08

Jul-0

8O

ct-0

8Ja

n-09

Apr-0

9Ju

l-09

Oct

-09

Jan-

10Ap

r-10

Jul-1

0O

ct-1

0Ja

n-11

Apr-1

1Ju

l-11

Oct

-11

Jan-

12Ap

r-12

Jul-1

2O

ct-1

2Ja

n-13

Apr-1

3Ju

l-13

Oct

-13

Jan-

14Ap

r-14

Jul-1

4O

ct-1

4Ja

n-15

Apr-1

5Ju

l-15

Oct

-15

Jan-

16Ap

r-16

Jul-1

6O

ct-1

6Ja

n-17

Apr-1

7

180

Government + Central Bank

Private

Government + Central Bank and Private

16

12

10

8

6

4

2

140

120

100

80

60

40

20

160

Jan-

08M

ay-0

8Se

p-08

Jan-

09M

ay-0

9Se

p-09

Jan-

10M

ay-1

0Se

p-10

Jan-

11M

ay-1

1Se

p-11

Jan-

12M

ay-1

2Se

p-12

Jan-

13M

ay-1

3Se

p-13

Jan-

14M

ay-1

4Se

p-14

Jan-

15M

ay-1

5Se

p-15

Jan-

16M

ay-1

6Se

p-16

Jan-

17M

ay-1

7

180 18

14

Pemerintah

Bank Sentral(Skala Kanan)

Government Central Bank

Graph 1.21 External Debt Composition based on Loan Type and External Debt to GDP

Source: External Debt Statistics, Bank Indonesia

Source: External Debt Statistics, Bank Indonesia Source: External Debt Statistics, Bank Indonesia

12

8

6

4

2

35

30

25

20

15

10

5

40

45 14

10

Mar

-12

Jun-

12

Sep-

12

Des-

12

Mar

-13

Jun-

13

Sep-

13

Des-

13

Mar

-14

Jun-

14

Sep-

14

Des-

14

Mar

-15

Jun-

15

Sep-

15

Des-

15

Mar

-16

Jun-

16

Sep-

16

Des-

16

Mar

-17

Jun-

17

34,44

4,99

External Debt to GDP

GDP Growth (%, yoy)

External Debt Growth (%, yoy)

2,85

Source: CEIC and External Debt Statistics, Bank Indonesia

USD Miliar

USD Miliar

USD Miliar

(%) (%)

improving economic dynamics and the investment

recovery, demand for funds also increased and,

therefore, private nonbank external debt expanded

4.51% from USD130.02 billion at the end of 2016

to USD135.88 billion in June 2017. On the other

hand, private sector bank external debt moderated

slightly from USD29.48 billion to USD29.13 billion

in the reporting period.

In terms of original maturity, private nonbank

external debt was dominated by long-term

obligations worth USD110.31 billion compared to

just USD25.58 billion of short-term external debt.

Concerning risk, as most private nonbank eternal

risk was long term, the risks were contained.

Nevertheless, monitoring the risks was necessary

because of the increase in outstanding external debt

during the reporting period.

The risks associated with corporate repayment

capacity accumulated, however, in line with global

and domestic economic growth as well as lacklustre

corporate performance despite posting moderate

gains. The emergent risks were confirmed by a

relatively high Tier-1 Debt Service Ratio (DSR) at

a level of 15.85% in the second quarter of 2017,

despite tracking a downward trend since the third

quarter of 2016, decreasing from 21.90% to

16.63% in the first quarter of 2017. The lower DSR

stemmed from additional new outstanding external

debt and lower principal payments. Compared to

conditions in the previous period, the private sector

was the main contributor to the declining Tier-1

DSR, falling from 13.6% to 8.99% in the reporting

period. In contrast, the public sector posted a subtle

increase in the Tier-1 DSR from 6.18% at the end of

2016 to 6.86% in June 2017.

15BANK INDONESIA





Despite a growing portion of non-financial

corporate external debt, total restructured external

debt decreased to USD30.66 billion in the reporting

period. Most restructured corporate external debt

had a negative tone due to deteriorating corporate

performance stemming from the declining

repayment capacity, weaker business outlook and

liquidity problems. Negative tone restructuring was

accomplished through reconditioning, capitalised

interest, debt-to-equity swaps, debt reductions,

rescheduling and other forms of external debt

restructuring. Such conditions demonstrated the

comparatively high risk of corporate external debt

that could spill over to the domestic banking sector.

Striving to mitigate corporate external debt risk,

Bank Indonesia has enforced a hedging ratio

applicable to all nonbank corporations indebted

with foreign loans. The hedging obligations aim to

alleviate the potential risks that could surface due to

global and domestic economic uncertainty.

Based on the Application of Prudential Principles

report (KPPK) published in the first semester of

2017 for external debt with a tenor of 0-3 months,

of the 2,418 reporting companies, 248 (10%) had

30

25

20

15

10

5

0

(%)

Q1 Q1 Q1 Q1Q2 Q2 Q2 Q2Q3 Q3 Q3Q4 Q4 Q4

2014 2015 2016 2017

15.85%

8.99%

6.86%

Total Tier DSR Public Sector Tier-1 DSR

Private Sector Tier-1 DSR

Graph 1.23 Debt Service Ratio (DSR)

50,000

150,000

250,000 70.00

30.00

50.00

10.00

(20.00)

60.00

20.00

(10.00)

40.00

-

(30.00)

100,000

200,000

(%)Miliar Dolar AS

Jun09

Jun10

Jun11

Jun12

Jun13

Jun14

Jun15

Jun16

Jun17

Dec09

Dec10

Dec11

Dec12

Dec13

Dec14

Dec15

Dec16

Graph 1.22 Private Nonbank External Debt by Original Maturity

Source: External Debt Statistics, Bank Indonesia Source: External Debt Statistics, Bank Indonesia

Short-Term Long-Term

Shoert-Term External Debt Growth (rhs)

Long-Term External Debt Growth (rhs)

failed to meet the requirements to hedge 25% of

their net foreign currency liabilities. For 3-6 months,

however, 161 reporting companies (7%) had failed

to meet the requirements.

1.4.4. Large Non-Resident Holdings in the

Domestic Financial Markets

Less volatile global economic shocks in the first half

of 2017, coupled with relatively stable domestic

economic dynamics, in particular the financial

markets, buoyed stock and SBN market growth

and improved performance. Non-resident investor

confidence in domestic assets remained high, thus

precipitating a net capital inflow drawn to the stock

and SBN markets. Increasing liquidity, financial

market deepening and domestic capital market

capitalisation bolstered non-resident investor

holdings.

The portion of non-resident investor holdings in the

stock and SBN markets spiked significantly in March

and April 2017 due to bullish sentiment after S&P’s

upgraded Indonesia’s sovereign credit rating to

Investment Grade, following other prominent rating

agencies that had previously affirmed investment

grade status, including Moody’s and Fitch Ratings.


16 BANK INDONESIA

Graph 1.24 Non-Resident Investor Holdings in SBN

271

324

461

559

666

771

1,182

671

749

903

1,107

550

Dec-12 Dec-13 Dec-14 Dec-15 Dec-16 Jun-17

2,500

2,000

1,500

1,000

5,00

Non-Residents Non-Residents Residents Residents

Source: Directorate General of Budget Financing and Risk Management (DJPPR), Ministry of Finance

Source: CEIC

Graph 1.25 Non-Resident Investor Holdings in Stocks

Jun-

13

Sep-

13

Des-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0

54.64%

45.36%

The move confirmed foreign investor confidence

in the national economic outlook. Nevertheless,

greater foreign participation in the domestic

financial markets also exacerbated the potential

risk of a sudden capital reversal and transaction

volatility.

In the SBN market, non-resident holdings accounted

for 39.47% of total SBN in circulation in June

2017, up from 37.55% at the end of 2016. The

net inflow drawn to the SBN market in the first

semester of 2017 totalled Rp31.33 trillion, which

precipitated a stronger yield on the benchmark 10-

year tenor, falling to a level of 7.02%. Additionally,

such conditions persisted into the middle of the

year, with the yield strengthening further to 6.79%

and the net inflow recorded at Rp14.40 trillion in

June 2017. Sentiment improved as uncertainty

surrounding the proposed FFR hike faded, which

prompted lower yields on all tenors.

Regarding the stock market, non-resident investor

holdings accounted for 54.64% of stock market

capitalisation value in June 2017, up slightly from

54.49% at the end of 2016 when non-resident

investors released domestic stocks on the back of

negative global sentiment. Notwithstanding the net

sell booked by foreign investors totalling Rp4.32

trillion, the domestic stock index continued to rally

to 5829.71 in the reporting period and to 5296.71

at the end of the previous period.

Contrasting the structure of the SBN and stock

markets, which were dominated by non-resident

investors, the SBI market was dominated by

domestic holdings, accounting for 79.56% in

the first semester of 2017, in particular due

to enforcement of a minimum holding period.

Nevertheless, the portion of domestic holdings

had declined from 98.50% in the previous

period. The minimum holding period, currently

set at one week, has had a relatively subdued

impact on foreign ownership in the SBI market.

17BANK INDONESIA






100%(%)

90%

50%

70%

30%

80%

40%

60%

20%

10%

0%

20.5

79.5

Mar

-13

Jun-

13

Sep-

13

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

Sep-

17

Dec-

17

Graph 1.26 Foreign and Domestic Holdings in Bank Indonesia Certificates (SBI)

Foreign Domestic

Source: Bloomberg Source: Bank Indonesia

Graph 1.27. The Development of Price and Volume of Stock Transactions

(20)

(25)

0 5000

4400(15)

5 5200

(10) 4600

4000

10 5400

(5) 4800

4200

15 5600

6000Rp T

20 5800

Foreign Net Buy/Sell of Stocks Foreign Net Buy/Sell of StocksJCI (rhs)

Dec-

12

Mar

-13

Jun-

13

Sep-

13

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

Graph 1.28 SBN Transaction Volume and Prices

-20

-30

20

6

-10

30

7

0

4

40

8

10

5

50Rp T (%)

9

10

10-Year Benchmark SBN Yield (rhs)

Dec-

12

Mar

-13

Jun-

13

Sep-

13

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17


18 BANK INDONESIA

Box 1.1 Bank Indonesia Systemic Risk Survey in the First Semester of 20175

As a macroprudential authority, Bank Indonesia

constantly strives to maintain financial system

stability through various efforts to mitigate

systemic risk. Several methods are available to

prevent risk, including the Systemic Risk Survey6.

When mitigating risk, identifying the sources of

the risks is a crucial preliminary step. The Systemic

Risk Survey complements Bank Indonesia’s efforts

to identifying sources of systemic risk in the

national financial system, which are divided into

two elements, namely identifying the sources of

shocks in the financial system as well as identifying

the vulnerabilities in the financial system because

systemic risk is believed to materialise when a

shock interacts with a vulnerability.7 In addition to

identifying the sources of systemic risk, the Survey

also garners public confidence in financial system

stability in Indonesia.

The Systemic Risk Survey was first conducted in 2015

and has been constantly developed since, with the

third survey published in the first semester of 2017.

Looking forward, the Survey will be conducted

regularly each semester, with the results published

in the Financial Stability Review (FSR). Seeking

to obtain comprehensive responses, the survey

reaches competent respondents with knowledge

and experience of the latest issues affecting

the financial system. Around 189 respondents

participated in the Survey conducted in March-April

2017, representing a 71.3% response rate, which

surpassed the target of 100 respondents.

Sources of Shocks in Indonesia’s Financial

System

This part of the Survey collates respondents’

opinions on possible shocks in the financial

system, coupled with the potential fallout over the

upcoming six months. The list of shocks included in

the questionnaire are also presented at the end of

this Box.

Based on a recapitulation of responses, a total of

seven shocks were brought to the attention of the

respondents due to a high probability of occurrence

and large potential impact on Indonesia’s financial

5 The results of the survey contained in this box are based on respondents’ responses and do not represent the views of Bank Indonesia.6 A general clarification of the Bank Indonesia Systemic Risk Survey was presented in the Financial Stability Review (FSR), No. 29, March 2017.7 Bank of Canada, 2014, Financial System Review, June 2014.

Box Table 1.1.1 Respondent Recapitulation

RespondentsSample Responses

Response RateTotal Share Total Share

Financial Institutions 101 38% 85 45% 84%

Corporations 49 18% 39 21% 80%

Economists and Bank Indonesia Financial Stability Research Forum (FRSK); 40 15% 25 13% 63%

Academia 24 9% 14 7% 58%

Professional Associations 26 10% 15 8% 58%

Research Institutes 18 7% 8 4% 44%

Media 5 2% 2 1% 40%

International Organisations 2 1% 1 1% 50%

TOTAL 265 100% 189 100% 71,3%


19BANK INDONESIA





system, namely the shocks that are contained in

the upper-right quadrant of Box Graph 1.1.1. The

shocks were global in nature, including: sluggish

global economic growth (1); global crude oil

prices (3); price volatility of major international

commodities (4); and international political and

economic issues (5); as well as domestic shocks,

such as: rising administered prices (6); rising volatile

foods prices (7); and changes to government fiscal

policy, such as the Tax Amnesty (8).

On average, nearly all shocks contained in the

questionnaire were categorised by the respondents

as shocks if they materialised and had a large impact

on the national financial system, excluding sectoral

policy changes (11) and domestic political issues

(12). The most significant impact, according to the

respondents, occurred if the shock affected a large

domestic bank (14) but with only a small chance

of materialising, the shock was considered a high

impact-low probability event.

In addition, several other types of shock were put

forward by the respondents through open questions,

including: below-target tax revenue; regional

conflict; corruption; and the impact of protracted

implementation of the National Legislation Program

(Prolegnas) in 2017 on draft bills that help shape

economic and financial activities as well as the

business community and industry.

Financial System Vulnerabilities in Indonesia

The respondents are expected to identify the

characteristics of vulnerabilities present in

Indonesia’s financial system, namely the severity and

attributes of the vulnerabilities. A list of sources of

vulnerabilities is also included in the questionnaire,

as presented at the end of this Box.

Nearly all sources of vulnerability presented in the

questionnaire were categorised by the respondents

as structural. Only vulnerabilities stemming from

lending procyclicality (7); FinTech innovation

8 The numbering in Box Graph 1.1.1 refers to the list of shocks presented at the end of Box 1.1.9 The numbering in Box Graph 1.1.2 refers to the list of vulnerabilities presented at the end of Box 1.1.

Box Graph 1.1.2 Characteristics of Vulnerabilities in Indonesia’s Financial System9

Alarming

9 118

16

312

10

2

13

14

8

15

7 4

6 5

17

11

Severity

Insignificant

Temporary Risk Characteristic Structural

Box Graph 1.1.1 Sources of Shocks in Indonesia’s Financial System8

High

57

6

1 4

3

28

9

10

11

12

13

1514

Probability of Occurrence

Low

Small Risk Impact Large


20 BANK INDONESIA

outpacing adequate regulation (8); overleveraged

corporations/non-financial companies (14); and

corporate liquidity problems (15) were assumed by

the respondents to be transient.

Based on a recapitulation of responses, a total of

eight vulnerabilities in the national financial system

were considered important by the respondents,

namely those that were structural in nature and

had an alarming level of severity, as appearing in

the upper-right quadrant of Box Graph 1.1.2. Such

vulnerabilities were sensitive to shocks and could

materialise into systemic risk with relatively rapidity

as follows: a large share and high volatility of foreign

funds in domestic investments (1); dominant private

external debt (2); loan concentration in certain

sectors or large borrowers (3); the proliferation of

shadow banking that is difficult to monitor (9); the

concentration of funding sources at large customers

(12); non-financial corporate dependence on

imported raw materials (16); shallow financial

markets (17); infrastructure loan disbursements

without adequate mitigation capacity (18). In

addition to the vulnerabilities included in the

questionnaire, the respondents also had the

opportunity to submit their own vulnerabilities

through open questions, which included: moral

hazard in the financial industry; less prudent credit

risk management; relatively broad margin spread in

the banking industry; loss loans and low investment

uptake.

Public Confidence in National Financial System

Stability

The final part of the Survey revealed that nearly all

respondents were upbeat in the short term, up to

6 months and >6 months. Only 1% of respondents

were not confident in national financial system

stability in the short term (up to six months) and

3% were not confident over the longer term (>6

months). Based on the recapitulation presented

in Box Graph 1.1.3, the respondents’ level of

confidence had declined for the period of >6

months, which was explained by the increasingly

difficult-to-predict nature of the economy over the

longer term.

21BANK INDONESIA





1. Subdued global economic growth;2. Greater frequency of FFR hikes than expected;3. Global crude oil price trend;4. Price volatility of major international commodities;5. International political and economic issues, including: a. Policies of the new US Administration (Trumponomics); b. General elections (changes of leadership) in

influential countries, such as France, Germany, Italy and the Netherlands;

c. Brexit issues; d. Economic policy in influential global powers;6. Rising administered prices (AP), including; a. Rising electricity rates; b. Rising fuel prices; c. Higher vehicle registration renewal fees;7. Rising volatile food (VF) prices;8. Changes in government policy relating to the fiscal sector, for

example the draft state budget, tax amnesty, etc.9. Weaker-than-expected domestic economic growth;10. Changes in policy and/or regulation concerning financial

institutions;11. Sectoral government policies, for example foreign property

ownership, restrictions on maize imports;12. Domestic political issues, such as local elections;13. Problems at large international banks;14. Problems at large domestic banks;15. Force majeure that affects the operation of the financial

system, for example problems in the payment system.

1. Large share and high volatility of foreign funds in domestic investments;

2. Dominant private external debt;3. Loan concentration in certain sectors or large borrowers;4. Constraints to value chain loan disbursements;5. Interconnectedness between the financial system and

government financial cycle;6. Interbank money market segmentation;7. Bank lending procyclicality;8. FinTech innovation outpacing adequate regulation;9. Proliferation of shadow banking that is difficult to monitor

and not adequately regulated;10. A banking sector dominated by several large banks;11. Banking sector interconnectedness;12. Concentration of funding sources amongst large customers;13. Bank funding problems;14. Overleveraged corporations/non-financial companies;15. Corporate liquidity problems;16. Non-financial corporate dependence on imported raw

materials;17. Shallow financial markets;18. Infrastructure loan disbursements without adequate

mitigation capacity.

Shocks Vulnerabilities

Very Unconfident1%

Unconfident1%

Confident66%

Confident77%

Unconfident3%

Very Confident20%

Very Unconfident0%

Very Confident32%

Up to 6 Months > 6 Months

Box Graph 1.1.3 Confidence in National Financial System Stability


22 BANK INDONESIA

Box 1.2 International Recognition of Successful Financial Sector Reforms in Indonesia according to FASP 2016/2017

Congruent with commitments as a member of the

G20, Indonesia again participated in the Financial

Sector Assessment Program (FSAP) in 2016/2017.

FSAP was first implemented in Indonesia in 2010

and represents a joint program of the International

Monetary Fund (IMF) and World Bank (WB) to

comprehensively assess financial sector stability and

performance, focusing on potential systemic risk

and interconnectedness between sectors.

Indonesia is committed to regular FSAP

implementation in order to support domestic

financial system stability and development.

FSAP implementation is voluntary in Indonesia

because Indonesia does not appear on the list of

countries with systemically important financial

systems. Nevertheless, Indonesia has committed

to regularly participate in the FSAP program

every five years, considering the various benefits

of FSAP implementation, including identifying

major vulnerabilities in the financial system and

recommendations to strengthen financial system

stability with a focus on enhancing the quality

and capacity of financial services sector regulation

and supervision, financial market deepening

and financial inclusion, as well as formulating an

appropriate and effective policy response to prevent

and resolve a crisis in the financial system.

Furthermore, publication of the FSAP results also

raises public confidence in the national economy.

The results of the FSAP in 2016/2017 were published

in an IMF report on 12th June 2017 (local time).

Simultaneously, the Government of the Republic of

Indonesia (Ministry of Finance), in conjunction with

domestic authorities/institutions, consisting of Bank

Indonesia, the Financial Services Authority (OJK) and

Deposit Insurance Corporation (LPS), disseminated a

joint press release on 13th June 2017 through their

respective channels. Publication and dissemination

of the FSAP results were expected to enhance public

understanding of financial services sector dynamics

in Indonesia, raise domestic and international public

confidence to draw investment to Indonesia and

facilitate the domestic financial services industry

to transact with external parties through potential

business development abroad.

The latest FSAP results pointed to solid macroeconomic

conditions in Indonesia, as reflected by a stable

financial system in the face of global financial system

volatility and domestic vulnerabilities. Moreover,

the national financial system remained solid despite

economic moderation, declining credit growth and

a corporate sector blighted by risk. Systemic risk

in the domestic financial system was deemed low

and stress tests showed that the banking system

was resilient to severe shocks, supported by a solid

capital base and high profitability. Vulnerabilities

in the corporate sector were mitigated despite a

build-up of debt risk in several sectors and offshore

funding risk. Consequently, the authorities were

requested to continue monitoring systemic risk and

remain vigilant of disruptions to financial stability.

23BANK INDONESIA





The achievements were supported by financial sector

reforms in Indonesia through various efforts actively

pursued by the authorities to strengthen financial

sector oversight, crisis management, financial

market deepening and financial inclusion. The

salient accomplishments in the domestic financial

sector include strengthening integrated financial

sector supervision through the establishment of

the Financial Services Authority (OJK) in 2011;

revising the crisis management and resolution

framework through promulgation of the Financial


Act in 2016, which became the foundation of the

Financial System Stability Committee and provided

the Deposit Insurance Corporation (LPS) broader

jurisdiction over resolution measures; implementing

Basel III by OJK; developing analysis tools to assess

systemic risk; implementing various macroprudential

policy instruments as well as reforming the liquidity

management framework by Bank Indonesia.

Sound economic performance and solid financial

system stability in Indonesia were also inextricably

linked to Bank Indonesia’s roles of intervention on

the foreign exchange and bond markets, effective

monetary policy in response to inflationary and

BOP pressures as well as macroprudential policy to

overcome credit growth and property sector prices.

Furthermore, macroprudential policy was considered

effective in terms of various BI accomplishments,

including: (i) promulgation of macroprudential

policy guidelines; (ii) organisational restructuring;

(iii) development of analysis tools to assess systemic

risk; (iv) implementation of macroprudential policy

instruments directly under the control of Bank

Indonesia through BI regulations, such as the loan-

to-value (LTV) ratio and RR-loan to funding ratio

(RR-LFR). In addition, corporate hedging regulations

issued by Bank Indonesia effectively reduced the

rapid pace of corporate external debt growth.

To enhance financial sector resilience as well

as support financial market deepening and

financial inclusion, FSAP recommended that the

authorities continue their ongoing processes while

strengthening the mandates and legal protection

of the financial system authorities, as well as

strengthening financial sector oversight, improving

the safety net and continuing financial market

deepening and financial inclusion efforts.

• Strengthen the mandates through amendments

to the BI Act and OJK Act with a focus on

financial stability rather than development.

An amendment to the BI Act is also required

to provide a clear macroprudential policy

mandate to Bank Indonesia, with a focus on

systemic risk coupled with data access to the

nonbank sector. Furthermore, the mandate of

the Deposit Insurance Corporation (LPS) should

be refocused on maintaining financial stability,

the sustainability of critical functions, deposit

guarantees and minimising the resolution

costs. In addition, a clear division of duties and


24 BANK INDONESIA

responsibilities would help to reduce duplicity

and increase inter-authority cooperation.

• Legal protection of the financial system

authorities. Legal protection of employees and

officers from the financial system authorities in

terms of supervision and crisis management is

required in line with international standards.

• Strengthen financial sector oversight. The

Financial Services Authority (OJK) must

strengthen integrated supervision across

sectors, oversight of financial conglomerates

in terms of governance and risk management

as well as reduce the silo structure of the OJK

organisation.

• Safety nets. The recommendations included

refining the role of the Financial System Stability

Committee to focus as a coordination forum,

limit the president’s role to the use of public

funds in order to avoid diluting the roles of

the Deposit Insurance Corporation (LPS) and

Financial System Stability Committee, as well

as refine the emergency liquidity assistance

framework (the Short-Term Liquidity Facility

(PLJP) in Indonesia) to ensure effective

implementation during crisis conditions, namely

in relation to the criteria for banks to receive

PLJP as well as Government guarantees. Public

funds for resolution purposes will be used on

limited cases with consideration of systemic

stability and complemented with adequate

safeguards.

Moving forward, Bank Indonesia will continue to

strengthen cooperation with the relevant authorities

to actively monitor the progress of the various

recommendations in the areas of financial stability

financial safety nets, financial market deepening

and financial inclusion and risk-based supervision

in the area of AML/CFT, particularly the Transfer

of Nonbank Funds and supervision of Nonbank

Money Changers. In addition, Bank Indonesia will

also prepare an update of the follow-up actions to

be monitored through implementation of Article

VI Consultation annually and monitoring the peer

review conducted by the Financial Stability Board

(FSB) two years after FSAP implementation.

25BANK INDONESIA





Box 1.3 Tax Amnesty Realisation

10 Contained in Act No. 11 concerning the Tax Amnesty, dated 28th June 2016, the objects of the Tax Amnesty were taxable liabilities that were undeclared or partially declared

by the taxpayers according to the latest income tax returns. The undeclared or partially declared taxable liabilities were calculated upon request of the Tax Amnesty applicant.

The scope of the Tax Amnesty excluded asset gains attributable to revaluations. The applicant was required to pay a relatively small fee based on the calculation of undeclared or

partially declared taxable liabilities.11 The tariffs on declared assets abroad and not repatriated was set at 4% for the period from 1st July – 30th September 2016, 6% from 1st October – 31st September 2016 and 10%

from 1st January 2017 – 31st March 2017.12 The tariffs on domestic declared assets or offshore assets to be repatriated were 50% lower than the tariffs on declared assets abroad and not repatriated for each respective

period.

The Government has implemented a Tax Amnesty

program in order to optimise potential tax revenue.

The Tax Amnesty was applied from 1st July 2016

until 31st March 201710. In general, the Tax Amnesty

targeted undeclared or partially declared taxable

liabilities according to the latest income tax return.

The declared assets could be held domestically

or offshore. On the undeclared obligations, the

taxpayer would pay a relatively small fee11.The

tariffs on declared assets at home and repatriated

assets were lower than assets held offshore12.

The Tax Amnesty program was a success. The Tax

Amnesty was implemented in three phases, namely

from July – September 2016, October – December

2016 and from January – March 2017. The total

funds generated by the Tax Amnesty reached

Rp135.3 trillion (Box Graph 1.3.1), which boosted

tax revenue in 2016 and 2017, particularly non-oil

and gas income tax. Meanwhile, the value of assets

declared totalled Rp4,882 trillion, of which Rp147.7

was repatriated (Box Graph 1.3.2). Total revenue far

exceed that generated by the Sunset Policy initiated

in 2008, which supplemented tax revenue to the

tune of just Rp7.5 trillion. The funds generated and

assets declared as part of this Tax Amnesty were

the highest of any similar program implemented

anywhere in the world.

The Tax Amnesty could potentially improve tax

performance. The Tax Amnesty directly boosted

tax revenue through the fees paid. In addition, tax

revenue has also increased in the period after the

Tax Amnesty in the form of Article 29 concerning

Individual Income Tax payments from taxpayers

who submitted an income tax nil return from 2014-

2016, with the negligible value of just Rp1.0 trillion

at the end of the first semester of 2017. On the

other hand, there was also an increase recorded

in the Final Income Tax payments on Dividends

(paid to individuals), which increased 65.8% from

Rp0.79 trillion in January – April 2016 to Rp1.32

trillion in January – April 2017. The positive post-TA

developments will help the government attain its

target ratio of tax revenue to GDP in the 2017 state

budget, set at 10.8% of GDP (Box Graph 1.3.3).

The TA program also elevated other economic

variables. The Tax Amnesty successfully attracted

residents’ funds placed in offshore assets, which

increased domestic liquidity, improved Indonesia’s

International Investment Position (IIP) and supported

rupiah exchange rate stability. The largest group of

repatriated assets was cash and cash equivalents

(Rp87.9 trillion), followed by receivables and

inventory (Rp25.9 trillion) as well as investments and

securities (Rp21.3 trillion). This was also reflected in


26 BANK INDONESIA

the transfer of Overseas Current Accounts (OCA)

to Nostro accounts, sales of securities and offshore

asset divestment throughout 2016. The transfer of

OCA to Nostro accounts peaked in September –

December 2016, along with the inflow of foreign

exchange to rupiah. Inflow transactions of foreign

exchange converted to rupiah spiked in September –

December 2016, which not only bolstered domestic

liquidity but also improved Indonesia’s International

Investment Position (IIP) in the second half of

2016. In addition, the increased supply of foreign

exchange also fed through to rupiah appreciation.

Box Graph 1.3.1 Tax Amnesty Fees

135.3trillion

19.4 trillionTax Debt Payment for Tax Amnesty Participation

Cessation of Initial Evidence 1.7 trillion

Ransom Payment114.2 trillion

Box Graph 1.3.2 Declared Assets through the Tax Amnesty

4,882.2trillion

1,036.7 trillionDeclared Offshore

Repatriated146.7trillion

Declared Onshore3,698.7 trillion

Tax Revenue

Rp, T % PDB11.5

10.5

11.2

11.411.3

10.910.7

10.3

10.8

1,400.0

1,600.0

1,200.0

1,000.0

800.0

600.0

400.0

200.0

2009

Tax Ratio

2010 2011 2012 2013 2014 2015 2016

11.6

11.4

11.2

11.0

10.8

10.6

10.4

10.2

10.0

9.8

9.6

2017

APBN-P

Box Graph 1.3.3 Ratio of Tax to GDP (%)

27BANK INDONESIA





The process of making golek puppets using detailed engraving. The process requires adept engraving

skills to produce the desired results. In terms of financial system stability, the engraving technique may be

construed as the ability to manage inflows to the financial markets, primarily foreign capital inflows, which

can significantly affect conditions in the overall financial system.

In general, the domestic financial markets remained relatively stable in the first half

of 2017, with improvements stemming from maintained macroeconomic conditions in

Indonesia against a backdrop of mixed domestic and global economic dynamics. The

favourable perception of investors concerning domestic macroeconomic conditions

became positive sentiment driving financing from the capital market, primarily boosted by

financing from the bond market, medium-term notes (MTN) and Negotiable Certificates

of Deposit (NCD), as the banks reported slower credit growth. Bullish sentiment also

drew non-resident capital inflows to the domestic financial markets. Nevertheless,

volatility in the rupiah interbank money market, foreign exchange market, stock market

as well as government and corporate bond markets eased, indicating less risk in the

domestic financial markets.

Moving forward, the risk of a sudden capital reversal demands vigilance. The direction

of the US economic recovery, policy to unwind the Federal Reserve’s balance sheet and

end of the low interest rate era, including the potential nuclear threat from North Korea,

will influence global financial market sentiment. At home, investors will tend to focus

on economic growth resilience and fiscal performance. In addition, subdued corporate

expansion in several sectors, coupled with relatively high non-performing loans (NPL),

could potentially undermine corporate repayment capacity.

The Islamic financial sector also performed solidly, with the Islamic Stock Index continuing

to rally, the share of government sukuk expanding as a source of state budget financing,

and the ongoing development of Islamic mutual funds. Furthermore, the social financial

sector also recorded gains as zakat and waqf funds continued to increase.

THE FINANCIAL MARKETS

02


30 BANK INDONESIA

Money Market

Risk was contained in the money market as interest rates and volatility declined.

Interbank rate down to4.30%

Interbank Money Market Repo Market

Interbank rate volatility down to33.68%

Average daily interbank money market transaction volume up to Rp8.11 trillion

Average daily interest rate down to 4.95% - 5.44%

Average daily transaction volume up toRp7,524 trillion

Rupiah exchange rate down to Rp13,368/USD

Volatility down to 2.39%

NDF spread down to -0.85%

Foreign Exchange Market

Risks tended to ease in the foreign exchange market, reflected by low volatility and a relatively stable risk premium.

Risk also eased in the stock market, indicated by a JCI rally and lower volatility.

Risk was observed to decline in the SBN and corporate bond markets, accompanied by lower yields and less volatility.

IDMA index up to 103.64

10-year benchmark yield down to6.80%

10-year yield (A) down to 10.49%

Volatility of 10-year benchmark tenor down to 4.90%

Volatility down to4.27%

Net foreign capital inflow increased to Rp104.74 trilion

Net foreign capital inflow up to Rp1,229 tirilion

Bond Market

Corporate BondsVolatility up to8.5%

Net foreign capital outflow up toRp18.24 trillion

JCI up to 5,829.7

Stock Market

Jakarta Islamic Index (JII) up to

749.6

Jakarta Islamic Index (JII)

volatility down to 13.05

Indonesia Sharia Stock Index (ISSI) down to

15.42%

Market share of Islamic mutual funds

to conventional investment funds up

to 4.73%

Islamic Financial Market

THE DOMESTIC FINANCIAL MARKETS WERE MAINTAINEDIN LINE WITH GLOBAL ECONOMIC GROWTHTHAT EXCEEDED PREVIOUS EXPECTATIONS

Tradeable Government

Securities (SBN)

The Islamic financial market performed well in terms of Islamic stocks, Islamic mutual funds, sukuk and ZIS funds.





31BANK INDONESIA

semester of 2017. Furthermore, the number of

issuers of IPOs and rights issues also increased,

climbing from 25 to 37 issuers, dominated by the

mining sector. The promising domestic economic

outlook after the upgraded sovereign credit rating

outlook was affirmed in the first semester of 2017

boosted corporate interest in IPOs, rights issues and

corporate bonds. In addition, the outlook for exports

from Indonesia was also predicted to improve in line

with faster global economic growth and, therefore,

increasing world trade volume (WTV).

The stock market gains were mirrored in the bond

market. In the first half of the year, issuances of

corporate bonds and sukuk totalled Rp82.27 trillion,

up 37.86% on the previous period (Rp59.68 trillion).

The number of issuers also increased, expanding

Against a backdrop of consolidated bank lending,

economic financing from the financial markets

increased significantly during the first semester of

2017, primarily originating from a surge in corporate

bond and sukuk issuances as well as through initial

public offerings (IPO) and rights issues. In addition,

financing from finance companies has also been

recovering since the first half of 2016, driven by the

trade sector and household consumption.

In the stock market, IPOs and rights issues increased

significantly from Rp37.92 trillion in the second

semester of 2016 to Rp57.55 trillion in the first

2.1. Role of the Financial Markets as a Source of Economic Financing

Table 2.1. Bank and Nonbank Financing (Rp, trillions)

Source: Financial Services Authority (OJK) and Indonesian Central Securities Depository (KSEI) reports

Source: Financial Services Authority (OJK), Indonesia Stock Exchange, processed

Keterangan2014 2015 2016 2017

Sem I Sem III Sem I Sem II Sem I Sem II Sem I

A. Bank Loans 175.29 206.15 153.74 230.08 110.17 208.89 114.18

B. Nonbank Financing 64.78 50.06 67.64 45.96 106.42 112.20 158.60

B1. Capital Market 51.88 44.78 63.95 52.58 97.78 97.60 139.82

- IPOs and Rights Issues in the Stock Market 26.35 21.67 18.59 34.94 41.28 37.92 57.55

- Corporate Bonds and Sukuk 25.53 23.11 45.36 17.65 56.51 59.68 82.27

B2. Finance Companies 12.90 5.27 3.69 -6.63 8.64 14.61 18.77

TOTAL 240.07 256.20 221.38 276.04 216.59 321.10 272.77

Jan

Feb

Mar Ap

rM

ay Jun Jul

Aug

Sept Oct

Nov De

cJa

nFe

bM

ar Apr

May Jun Jul

Aug

Sept Oct

Nov De

cJa

nFe

bM

ar Apr

May Jun

2015

100Rp Trillion

90

80

70

60

50

40

30

20

10

0

2016 2017

Right IssuesBondsIPO

Graph 2.1. IPO and Right Issue Volume on the Stock Market

32 BANK INDONESIA


from 41 to 54, dominated by the financial sector and

infrastructure. Competitive corporate bond pricing,

particularly for those rated AAA to A, compared to

bank lending, especially in the long term, encouraged

the corporate sector to supplement financing

through corporate bonds. Several corporations also

used bond financing as an alternative to external

debt as global interest rates began to rise.

The upward market trend of Negotiable Certificates

of Deposit (NCD) persisted in the first semester

of 2017. This instrument was most attractive to

bank issuers as an alternative source of short-term

funding of less than one year. Outstanding NCD

grew 12.01% from Rp19.90 trillion in the second

semester of 2016 to Rp22.29 trillion in the reporting

period.

14

%

13

12

11

10

9

8

71 2 3 4

Tenor

5 6 7 8 9 10

Average interest rates on Investment Loans (June 2016) = 11.47%

Rating BBB (Jun’17)Rating A (Jun’17) Rating AAA (Jun’17)

Graph 2.2.Comparison of Corporate Bond Yield Curve and Average Interest Rates on Investment Loans and

Working Capital Loans

Source: Bank Indonesia and CEIC

Source: CEIC

Source: Financial Services Authority (OJK), Bank Indonesia and Bloomberg, processed

Source: Indonesian Central Securities Depository (KSEI), processed

60

NCD NCD

Rp Trillion

MTN MTN

50

40

30

20

10

0

Jan-

15

Feb-

15

Mar

-15

Apr-1

5 M

ay-1

5 Ju

n-15

Ju

l-15

Aug-

15

Sep-

15

Oct

-15

Nov

-15

Dec-

15

Jan-

16

Feb-

16

Mar

-16

Apr-1

6 M

ay-1

6 Ju

n-16

Ju

l-16

Aug-

16

Sep-

16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7 M

ay-1

7 Ju

n-17

Graph 2.4 Value of Outstanding MTN and NCD

45

40

35

30

25

20

15

10

5

0

Jan-

15

Feb-

15

Mar

-15

Apr-1

5 M

ay-1

5 Ju

n-15

Ju

l-15

Aug-

15

Sep-

15

Oct

-15

Nov

-15

Dec-

15

Jan-

16

Feb-

16

Mar

-16

Apr-1

6 M

ay-1

6 Ju

n-16

Ju

l-16

Aug-

16

Sep-

16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7 M

ay-1

7 Ju

n-17

Graph 2.3 Bond Issuance Value

Corporate Bonds (Rp T) Lending Rate on Investment Loans (%)

Average Yield of 5-Year Corporate Bonds (%)

7

Rp Trillion

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

1

2017 2018 2019

1 23 3 45 5 67 89 9 1011 11 12

0.5

0

Graph 2.5 Outstanding MTN and NCD by Maturity

33BANK INDONESIA





Congruent with Negotiable Certificates of Deposit

(NCD), market growth of medium-term notes

(MTN) also accelerated significantly. Outstanding

MTN grew by 25.23% on the position recorded in

the second semester of 2016 to Rp32.18 trillion.

Most MTN were used as working capital (business

expansion) and for refinancing purposes.

The surge of funding through NCD and MTN

issuances stemmed from simpler requirements and

no mandatory minimum rating, which streamlined

the process of issuing both instruments. Funding

through NCD is already considered sustainable due

to the broad investor base thanks to a Bank Indonesia

regulation that standardised NCD instruments.

Sumber : KSEI

Jan

Jan

Jan

Mar

Mar

Mar

May

May

MayJu

l

Jul

Sept

Sept

Nov

Nov

0

1

2015 2016 2017

2

3

4

5

6

7RP Trillion

Graph 2.6. Nominal Value of MTN and NCD Issuances

NCDMTN

Table 2.2 Sources of Funds by Bank Total

Description2014 2015 2016 2017

Sem I Sem II Sem I Sem II Sem I Sem II Sem I

Fund Accumulation

I. Domestic

Borrowing from Rupiah Interbank Money Market

81 76 76 86 85 96 65

Borrowing from Foreign Exchange Interbank Money Market

47 39 40 33 31 38 32

Repo to Bank Indonesia/Lending Facility 1 7 19 9 12 9 9

Repo by Banks 17 16 18 20 10 22 23

Bond Markets 2 3 6 1 9 10 4

- Bonds 1 2 1 1 - 2 -

- Continuous Bonds 1 1 4 - 7 7 4

- Sukuk - - 1 - 2 1 -

Stock Market 3 3 - 4 6 7 2

- IPO 1 1 - 1 1 - -

- Rights Issues 2 2 1 3 5 7 2

II. International

Bonds (USD) - - - - - - -

Fund Distribution

I. Domestic

Lending to Rupiah Interbank Money Market

94 99 98 100 98 103 95

Lending to Foreign Exchange Interbank Money Market

45 42 39 31 37 45 43

Deposit Facility 107 134 98 114 100 98 94

Term Deposit - - - - - 31 -

Bank Indonesia Certificates of Deposit (SDBI)

50 76 79 74 81 71 85

Bank Indonesia Certificates (SBI) + SBIS 98 108 75 74 86 91 82

Reverse Repo SUN 36 59 37 17 25 41 49

Tradeable Government Securities (SBN) 91 87 84 95 101 108 108

Source: Bank Indonesia, Financial Services Authority (OJK)

34 BANK INDONESIA


Against a backdrop of consolidated bank lending,

bonds issued by the banking sector also declined in

the first half of the year. During the first semester,

only four banks issued bonds, totalling Rp15.1

trillion, down from 10 banks issuing bonds worth

Rp19.3 trillion in the previous semester. The market

share of bonds issued by the banking industry

accounted for 18.4% of the total in the first

semester of 2017. In addition to the bond market,

banks also supplemented funds through initial

public offerings (IPO) and rights issues on the stock

market, amounting to Rp3.7 trillion, up slightly

on the value issued in the previous period despite

fewer issuers.

Table 2.3 Sources of Bank Funds by Volume

Description2014 2015 2016 2017

Sem I Sem II Sem I Sem II Sem I Sem II Sem I

Fund Accumulation

I, Domestic

PUAB

- Interbank Money Market 1,325 1,388 1,426 1,439 1,537 1,370 1,448

- Volume of Borrowing 11.1 11.1 11.6 11.7 12.4 11.1 12.5

- Average Daily Volume of Rupiah Borrowing

359.4 533.7 429.2 240.2 386.1 274.1 313.0

Repo to Bank Indonesia/Lending Facility

0.1 2.4 11.0 5.8 2.6 2.7 1.4

Average Daily Repo by Banks 0.5 0.6 0.7 0.6 0.4 1.1 1.2

Bond Markets 5.0 2.0 11.4 0.5 17.7 19.3 15.1

- Bonds 1.0 1.3 1.5 0.5 - 1.0 -

- Continuous Bonds 4.0 0.7 9.4 - 16.4 17.3 15.1

- Sukuk - - 0.5 - 1.3 1.0 -

Stock Market 1.5 2.1 0.6 1.0 8.0 3.5 3.7

- IPO 0.1 0.1 - 0.1 0.6 - -

- Rights Issues 1.5 2.0 0.6 0.9 7.5 3.5 3.7

II, International

Bonds (USD) - - - - - - -

Fund Distribution

I, Domestic

Interbank Money Market

- Average Daily Volume of Rupiah Lending

11.1 11.1 11.6 11.7 12.4 11.1 12.5

- Average Daily Volume of USD Lending

359.4 533.7 429.2 240.2 386.1 274.1 313.0

Deposit Facility 125.3 98.5 127.2 112.3 134.6 104.5 165.4

Term Deposit - - - - - 23.2 -

Bank Indonesia Certificates of Deposit (SDBI)

23.3 102.3 62.4 39.9 66.5 47.0 166.0

Bank Indonesia Certificates (SBI) + SBIS

98.6 87.0 72.7 31.1 78.8 103.9 46.5

Reverse Repo SUN 74.4 88.6 64.1 5.7 11.0 23.6 23.5

Tradeable Government Securities (SBN)

338.0 374.0 346.7 350.0 361.5 399.5 395.1

Rp Trillion

Source: Bank Indonesia, Financial Services Authority (OJK)

1 Bank Indonesia Regulation (PBI) No. 19/2/PBI/2017, dated 16th March 2017, concerning Negotiable Certificates of Deposit (NCD) Transactions on the Monet Market

35BANK INDONESIA





In general, risks in the global and domestic financial

markets were stable in the first semester of 2017,

with a tendency to ease. In terms of the externalities,

the risks were contained by global economic growth

and maintained investor sentiment. The release

of economic growth data for the United States,

Europe and China exceeded previous expectations,

which edged up world trade volume (WTV). Such

developments were also supported by easing

political tensions between the US, China, Russia and

North Korea as well as the trade war between the US

and China that did not materialise. Meanwhile, the

monetary policy stance adopted in various advanced

economies, including the European Central Bank

(ECB), Bank of Japan (BOJ) and Bank of England

(BOE), was in line with expectations and relatively

accommodative to the markets, which prevented

shocks emerging from the subsequent portfolio

rebalancing. At home, however, bullish sentiment

was driven by robust national economic growth, a

surplus trade balance, controlled inflation, a stable

2.2. Financial Market Dynamics and Risk

reference rate, rupiah appreciation and affirmation

that S&P’s had upgraded Indonesia’s sovereign

credit rating to investment grade.

The positive sentiment attracted foreign capital

inflows to the domestic financial markets. During

the reporting period, inflow stood at Rp122.98

trillion, drawn to stock market instruments and

tradeable government securities (SBN), the highest

level on record since the first semester of 2014.

The composition of capital inflow to the stock

and SBN markets stood at Rp18.24 trillion and

Rp104.74 trillion respectively, which prompted

rupiah appreciation against the USD from Rp13,473

at the end of December 2016 to Rp13,348/USD at

the end of June 2017. Furthermore, volatility in the

rupiah interbank money market, foreign exchange

market, stock market as well as government and

corporate bond markets also decreased, which was

indicative of less risk in domestic financial markets.

Moving forward, the risk of a sudden capital

reversal still demands vigilance. The direction of the

US economic recovery, policy to unwind the Fed’s

balance sheet and the end of the low interest rate

Rupiah Interbank Money Market

Exchange Rate

Mutual Funds

SBN Market

CorporateBond Market

*) Further from the centre indicates higher risk

Sem I 2017Sem II 2016Sem I 2016Sem II 2015

Stock Market

Graph 2.7. Financial Markets Volatility Graph 2.8 Non-Resident Capital Flows to Stocks, SBN and SBI

150

50

-50

100

0

SBI

2011 2013

Sem I Sem I Sem I Sem ISem II Sem II Sem II

2015 20162012 2014 2017

SBN Stocks

-100

RP Trillion

Source: Bloomberg, processed Source: Bloomberg, Bank Indonesia and Ministry of Finance

36 BANK INDONESIA


era by the Federal Reserve, Bank of England, Bank

of Canada and Reserve Bank of Australia along

with the potential escalation of the nuclear issue

in North Korea will influence global sentiment. In

addition, restrained corporate expansion in several

sectors, coupled with the relatively high level of non-

performing loans (NPL), could undermine corporate

repayment capacity.

2.2.1. Money Market

Risk in the uncollateralised and collateralised money

markets was contained in the first semester of 2017.

Interbank rate volatility declined, while transaction

volume in the interbank money and repo markets

increased. Congruent with the lower interbank

rate, repo rates were also observed to fall.

2.2.1.1. Interbank Money Market (PUAB)

Risk in the rupiah interbank money market tended

to ease during the first semester of 2017, indicated

by lower interest rates and volatility. The weighted

average O/N rupiah interbank rate reduced from

4.54% in the second semester of 2016 to 4.30% in

the reporting period. Consistent with the lower O/N

interbank rate, the weighted average interest rate

of all tenors also decreased, falling from 4.87% to

4.53%. Likewise, compared to the same period one

year earlier, the weighted average O/N interbank

rate in the first semester of 2016 stood at 5.08%

and 5.30% for all tenors.

Interbank money market transaction volume has

increased, especially overnight transactions. The

average daily O/N rupiah interbank money market

transaction volume increased from Rp6.66 trillion in

the second semester of 2016 to Rp8.11 trillion in the

first semester of 2017. Similarly, the average daily

non-overnight interbank money market transaction

volume also increased, rising from Rp4.34 trillion to

Rp4.42 trillion in the same period. The gains were

consistent with cyclical trends for Eid-ul-Fitr and

the start of the new academic year, which trigger a

seasonal and transient spike in demand for liquidity,

which the banks meet through the interbank money

market.

The transaction trends in the interbank money

market did not change during the reporting

10

% %

5

4.5

4

3.5

3

2

2.5

1

0.5

0

2.5

9

8

7

6

5

4

3

2

Jun-

11

Oct

-11

Feb-

12

Feb-

13

Feb-

14

Feb-

15

Feb-

16

Feb-

17

Jun-

12

Jun-

13

Jun-

14

Jun-

15

Jun-

16

Jun-

17

Oct

-12

Oct

-13

Oct

-14

Oct

-15

Oct

-16

Min-Max Spread (rhs) Highest Borrowing Interest Rate (%)Lowest Borrowing Interest Rate (%)

PUAB ON

Graph 2.9 Rupiah O/N Interbank Rate

Weighted Average Interest Rate (%)

140%

Rupiah Interbank Money Market Volatility

Weighted Average Borrowing Rate (%)

120%

100%

80%

60%

40%

20%

0%

Jul-1

5

Aug-

15

Sep-

15

Oct

-15

Nov

-15

Dec-

15

Jan-

16

Feb-

16

Mar

-16

Apr-1

6

May

-16

Jun-

16

Jul-1

6

Aug-

16

Sep-

16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7

May

-17

Jun-

17

7.5

6.0

7.0

5.5

6.5

5.0

4.5

3.5

3.0

4.0

Graph 2.10 O/N Interbank Rate Volatility


37BANK INDONESIA





semester, with BUKU 3 banks remaining dominant.

Nevertheless, BUKU 2 banks became more active on

the interbank money market as suppliers to satiate

demand from BUKU 3 banks. The growth of BUKU

4 banks did not spur any change in behaviour as an

aggregate. In terms of market share, BUKU 3 banks

continued to dominate interbank money market

transactions, accounting for 50.73% of the total

transactions and 45.59% of the total frequency.

Developments in the rupiah interbank money market

during the first semester of 2017 were not mirrored

in the foreign exchange interbank money market.

The weighted average daily foreign exchange

O/N interbank rate and the average daily foreign

exchange interbank rate for all tenors increased

in the first half of the year by 0.84% and 0.86%

respectively, accelerating from 0.37% and 0.39%

in the second semester of 2016. The rising foreign

exchange interbank rate was, however, influenced

more by Bank Indonesia raising the interest rate on

foreign exchange monetary operations in response

to the Federal Reserve hiking its policy rate and not

due to inadequate liquidity. This was substantiated

2 One bank changed status from a BUKU 3 bank to a BUKU 4 bank.




Apr

Jun

Aug

Oct

Dec

Feb

Apr

Jun

Aug

Oct

Dec

Feb

Apr

Jun

Aug

Oct

Dec

Feb

Apr

Jun

Aug

Oct

Dec

Feb

Apr

Jun

2014 2015 2016 2017

100

200

300

400

500

600USD Million%

1.20

Average Daily Non-O/N Transaction Volume (rhs)

Average Daily O/N Transaction Volume (rhs)

Weighted Average O/N Interbank Rate

Weighted Average of All Interest Rates

1.00

0.80

0.60

0.40

0.20

Graph 2.13 Foreign Exchange Interbank Money Market Performance

-150

50

-100

100

-50

150RP Trillion

0

20152014

BUKU 4 BUKU 3 BUKU 2 BUKU 1

2016 2017

Jul

Jul

Jul

Jun

Jun

Jun

May

May

MayAp

r

Apr

Apr

Mar

Mar

Mar

Feb

Feb

Feb

Jan

Jan

Jan

Aug

Aug

Aug

Sep

Sep

Sep

Oct

Oct

Oct

Nov

Nov

NovDe

c

Dec

Dec

Graph 2.12 Rupiah Interbank Money Market Transaction Trends

0.81.40

1.20

1.00

0.80

0.60

0.40

0.20

0.00

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0

Jul-1

1

Sep-

11

Dec-

11

Mar

-12

Jul-1

2

Sep-

12

Dec-

12

Mar

-13

Jul-1

3

Sep-

13

Dec-

13

Mar

-14

Jul-1

4

Sep-

14

Dec-

14

Mar

-15

Jul-1

5

Sep-

15

Dec-

15

Mar

-16

Jul-1

6

Sep-

16

Dec-

16

Mar

-17

Jul-1

7

Min-Max Spread (rhs) Weighted Average Interbank Rate

Highest Borrowing Interest Rate (%)

Graph 2.14 Foreign Exchange O/N Interbank Rate


Graph 2.11 Rupiah Interbank Money Market Performance

6.012

7.0 14

8.0 18

5.010

4.08

3.0

42.0

2

-

1.0

-

%RP Trillion

Average Daily Non-O/N Volume (rhs)Weighted Average O/N RateWeighted Average Interest Rate

Average Daily O/N Volume (rhs)

Jan

Jan

Jan

Jan

Feb

Feb

Feb

Feb

Mar

Mar

Mar

MarAp

r

Apr

Apr

Apr

Apr

May

May

May

May

MayJun

Jun

Jun

Jun

JunJul

Jul

Jul

Jul

Aug

Aug

Aug

Aug

Sep

Sep

Sep

Sep

Oct

Oct

Oct

Oct

Nov

Nov

Nov

NovDe

c

Dec

Dec

Dec

20142013 2015 2016 2017

38 BANK INDONESIA


by a narrower max-min spread, lower volatility and

higher transaction volume. In the first semester of

2017, average spread narrowed considerably from

16.57bps to 4.39bps and volatility halved from

207.77% to 110.27%.

Foreign exchange interbank money market

transaction volume, O/N and non-O/N, increased.

In the first semester of 2017, the average daily

O/N transaction volume in the foreign exchange

interbank money market climbed from USD245.70

million to USD264.84 million. Meanwhile, the

average daily non-O/N transaction volume in the

foreign exchange interbank money market soared

from USD29.61 million to USD51.76 million. Based

on historical trends, no changes in bank behaviour

were observed. BUKU 4 banks have remained

borrowers since 2015, while BUKU 3 banks have

remained lenders.

2.2.1.2. Interbank Repo Market3

Risk in the interbank repo market tended to ease

during the first half of 2017, as reflected by a

declining average daily interbank repo rate for all

tenors, decreasing from 5.30-5.87% to 4.95%-

5.44%, emulating Bank Indonesia’s reference

rate. In addition, interest rate spread on the repo

market also narrowed, indicating less risk and

greater efficiency. Moreover, the spread was also

lower than the interest rate spread in the interbank

9%

8%

7%

6%

5%

4%

3%

2.0

1.2

1.8

1.0

1.6

0.8

1.4

0.6

0.4

0.2

Volume Interest Rate (rhs)

0.0

Jun-

15

Jul-1

5

Aug-

15

Sep-

15

Oct

-15

Nov

-15

Dec-

15

Jan-

16

Feb-

16

Mar

-16

Apr-1

6

May

-16

Jun-

16

Jul-1

6

Aug-

16

Sep-

16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7

May

-17

Jun-

17

Rp Trillion

Graph 2.17. Interbank Repo Transactions


700% 1.20

500%0.80

300%

0.40

100%

0.00

800% 1.40

600%1.00

400%0.60

200%

0.20

0%

Jun-

15

Jul-1

5

Aug-

15

Sep-

15

Oct

-15

Nov

-15

Dec-

15

Jan-

16

Feb-

16

Mar

-16

Apr-1

6

May

-16

Jun-

16

Jul-1

6

Aug-

16

Sep-

16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7

May

-17

Jun-

17

Graph 2.16 Foreign Exchange Interbank Money Market Transaction Behaviour

Graph 2.15 Foreign Exchange Interbank Rate Volatility

0

-3

3

-2

4

-1

5

-5

1

-4

2

USD Billion

USD Interbank Money Market Volatility

Weighted Average Lending Rate (rhs)

Jan

Jan

Jan

Feb

Feb

Feb

Mar

Mar

MarAp

r

Apr

Apr

May

May

MayJun

Jun

JunJul

Jul

Jul

Aug

Aug

Aug

Sep

Sep

Sep

Oct

Oct

Oct

Nov

Nov

NovDe

c

Dec

Dec

2014 20172015 2016

BUKU 3 BUKU 2 BUKU 1BUKU 4

Source: Bank Indonesia Source: Bank Indonesia

39BANK INDONESIA





3 A repurchase agreement (Repo) is a contract sell and then repurchase the security on a determined date at a determined price. In general, the Repo market consists of the interbank repo

market and repo to Bank Indonesia through the Lending Facility (LF).

money market (all tenors). Meanwhile, the average

daily transaction volume of all tenors increased from

Rp6,262 billion in the second semester of 2016 to

Rp7,524 billion in the reporting period.

2.2.2. Foreign Exchange Market

Congruent with the influx of non-resident capital

during the first half of the year, risk in the foreign

exchange market tended to moderate. Average

rupiah exchange rate volatility against the USD fell

from 6.81% in the second semester of 2016 to just

2.39% in the first semester of 2017. Additionally,

the rupiah strengthened against the USD from

Rp13,473 at the end of the second semester of 2016

to Rp13,348/USD at the end of the first semester

of 2017. Rupiah appreciation was predicated on

90 16,000

Volatility Exchange Rate (rhs)

15,000

14,000

13,000

12,000

11,000

10,000

9,000

8,000

7,000

70

50

30

10

80

60

40

20

-

Jun-

11

Sep-

11

Dec-

11

Mar

-12

Jun-

12

Sep-

12

Dec-

12

Mar

-13

Jun-

13

Sep-

13

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17Graph 2.18 Rupiah Exchange Rate Performance

Source: Blomberg, processed

Source: Bloomberg, processedSource: Bloomberg, processed

700

500

300

100

600

400

200

0

-100

-200

-300

-400

15,500

14,500

13,500

12,500

11,500

15,000

14,000

13,000

12,000

11,000

NDF-FWD 18 Spread Average Daily 20D Spread

NDF 1B (rhs)

Jun-

15

Jul-1

5

Aug-

15

Sep-

15

Oct

-15

Nov

-15

Dec-

15

Jan-

16

Feb-

16

Mar

-16

Apr-1

6

May

-16

Jun-

16

Jul-1

6

Aug-

16

Sep-

16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7

May

-17

Jun-

17

Graph 2.19 Rupiah Volatility

30 10 % 2017

5

-

25

15

5

-

20

10

Dec-

08M

ar-0

9 Ju

n-09

Se

p-09

De

c-09

M

ar-1

0 Ju

n-10

Se

p-10

Dec-

10

Mar

-11

Jun-

11

Sep-

11

Dec-

11M

ar-1

2Ju

n-12

Se

p-12

Dec-

12M

ar-1

3 Ju

n-13

Se

p-13

De

c-13

Mar

-14

Jun-

14

Sep-

14

Dec-

14M

ar-1

5 Ju

n-15

Sep-

15

Dec-

15

Mar

-16

Jun-

16Se

p-16

Dec-

16M

ar-1

7Ju

n-17

4-Ju

l 29

-Jul

23-A

ug

17-S

ep

12-O

ct

6-N

ov

1-De

c 26

-Dec

20

-Jan

14-F

eb

11-M

ar

5-Ap

r 30

-Apr

25

-Ma

19-Ju

n

Graph 2.20 Foreign Exchange Market Risk Premium

external and internal factors, including better-

than-expected global economic performance and

affirmation of S&P’s upgrading Indonesia’s credit

rating to investment grade.

Less risk on the foreign exchange market was also

evident from the risk perception of non-resident

investors concerning the rupiah exchange rate,

as reflected in the NDF-FWD spread. In the first

semester of 2017, the spread of NDF transactions to

1-month domestic forwards declined from 0.14%

to -0.85% in line with broad depreciation of most

regional currencies.

Derivative transactions increased and the choice of

instruments to mitigate currency risk also increased.

40 BANK INDONESIA


The share of non-spot transactions, including swaps,

forwards and options, expanded from 34.82% to

40.41%. Swap transactions were the main driver

of the increase despite spot transactions remaining

dominant with a 59.59% share, declining from

65.18% in the previous period. The surge of derivative

transactions was symptomatic of financial market

deepening and also provided alternative instruments

for market players to manage currency risk.

2.2.3. Bond Market

2.2.3.1. SBN Market

The positive perception of investors, coupled with

foreign capital inflows, was the main impetus of

the SBN market. A deluge of non-resident capital

inflow expanded foreign investor SBN holdings to

Rp770.5 trillion, accounting for 39.47% of total

tradeable government securities (SBN) in circulation.

The increase of non-resident holdings eroded

domestic investor holdings, particularly of the

banking sector, insurance companies and pension

funds. At the end of the first semester of 2017,

the banking industry commanded a 20.45% share

of total SBN in circulation, down from 22.53% in

the previous semester. Likewise, the share of SBN

held by institutional investors from the nonbank

financial industry, including insurance companies

and pension funds, shrank to 13.02% and 4.56%

respectively of the total. Despite smaller holdings as

a percentage, the value of SBN held by insurance

companies and pension funds increased. Such

developments were explained by an OJK Regulation

(POJK) that required the nonbank financial industry

to fulfil a certain percentage of total investment

Source: Bloomberg

Source: Ministry of Finance


Table 2.4 A Comparison of Average NDF Spreads in Neighbouring Countries

Yield (%)

Negara2015 2016 2017

Sem I Sem II Sem I Sem II Sem I

Thailand (0.77) (2.03) (3.17) (3.23) (2.83)

Malaysia 0.18 (1.26) (1.82) (0.07) (0.01)

Philippines (0.09) 1.30 0.97 2.43 1.14

India (0.84) (0.68) (0.46) (0.71) (0.92)

Indonesia 2.36 2.91 (0.33) 0.14 (0.85)

80

Jul

Sep

Sep

Sep

Sep

Nov

Nov

Nov

NovJan

Jan

Jan

Jan

Mar

Mar

Mar

Mar

May

May

May JunJul

Jul

Jul

USD Billion

OPTIONFORWARDSWAPSPOT

50

70

40

20

60

30

10

20142013 2015 2016 2017

0

Graph 2.21 Composition of the Domestic Foreign Exchange Market

Table 2.5. Composition of SBN Holdings (%)

Holder

2016 2017 ∆ Sem I-II

Sem - I Sem - II Sem - I

Nominal (Rp T) ShareTotal(Rp, trillions) Share Total

(Rp, trillions) Share Total(Rp, trillions) Share

Banks 361.54 21.95% 399.46 22.53% 399.19 20.45% (0.27) -0.07%

Central Bank 150.13 9.12% 134.25 7.57% 175.89 9.01% 41.64 31.02%

Mutual Funds 76.44 4.64% 85.66 4.83% 91.56 4.69% 5.91 6.89%

Insurance Companies

214.47 13.02% 238.24 13.44% 254.21 13.02% 15.97 6.70%

Foreign 643.99 39.10% 665.81 37.55% 770.55 39.47% 104.74 15.73%

Pension Funds 64.67 3.93% 87.28 4.92% 89.11 4.56% 1.83 2.10%

Individuals 48.90 2.97% 57.75 3.26% 60.49 3.10% 2.74 4.75%

Others 86.72 5.27% 104.80 5.91% 111.23 5.70% 6.43 6.13%

41BANK INDONESIA





2000RP Trillion RP Trillion

1500

1000

500

0

Dec-

12

Jun-

13

Dec-

13

Jun-

14

Dec-

14

Jun-

15

Dec-

15

Jun-

16

Dec-

16

Jun-

17

Central BankForeignBank

Pension FundsMutual FundsSecurities Companies

Insurance CompaniesOthers

Graph 2.22. Composition of SBN Holdings

120

SBN IDMA (rhs)

80

40

Sem I Sem I Sem I Sem I Sem II Sem II Sem II

100

60

20

2014 20162015 2017

0

106

100

104

98

102

96

94

92

90

88

Graph 2.23 Net Foreign Flows to SBN and IDMA

Source: Bank IndonesiaSource: Ministry of Finance

Source: Bloomberg, processed

9.0

%

8.0

7.0

6.0

8.5

7.5

6.5

Jun-16 Jun-17 Dec-16

5.5

5.01 3 5 7 9 11 13 16 202 4 6 8 10 12 15 18 30

Graph 2.24 SBN Yield Curve Graph 2.25. Rebased SBN Yield by Tenor

Source: Bloomberg

50

%

Long Term Medium Term Short Term

30

40

20

5

45

25

10

35

15

0

Aug-

13

Oct

-13

Dec-

13

Feb-

14

Feb-

15

Feb-

16

Feb-

17

Apr-1

4

Apr-1

5

Apr-1

6

Apr-1

7

Jun-

14

Jun-

15

Jun-

16

Jun-

17

Aug-

14

Aug-

15

Aug-

16

Oct

-14

Oct

-15

Oct

-16

Dec-

14

Dec-

15

Dec-

16

Graph 2.26. SBN Yield Volatility by Tenor

Source: CEIC

35%

SBN TurnoverCorporate Bond Turnover

25%

15%

5%

30%

20%

10%

0%

Feb-

10M

ay-1

0Au

g-10

Nov

-10

Feb-

11M

ay-1

1Au

g-11

Nov

-11

Feb-

12M

ay-1

2Au

g-12

Nov

-12

Feb-

13M

ay-1

3Au

g-13

Nov

-13

Feb-

14M

ay-1

4Au

g-14

Nov

-14

Feb-

15M

ay-1

5Au

g-15

Nov

-15

Feb-

16M

ay-1

6Au

g-16

Nov

-16

Feb-

17M

ay-1

7Graph 2.27 Transaction Turnover of SBN and Corporate Bonds

Tenor


Aug-

13

Oct

-13

Dec-

13

Feb-

14

Feb-

15

Feb-

16

Feb-

17

Apr-1

4

Apr-1

5

Apr-1

6

Apr-1

7

Jun-

14

Jun-

15

Jun-

16

Jun-

17

Aug-

14

Aug-

15

Aug-

16

Oct

-14

Oct

-15

Oct

-16

Dec-

14

Dec-

15

Dec-

16

220

8,54%

8,27%

7,85%180

140

Long Term: 11-30 years

Medium Term: 6-10 years

Short Term: 1-5 years100

200

160

120

80

60

rebased 1/1/2013

Long Term Medium TermShort Term

42 BANK INDONESIA


Source: CEIC, processed

in SBN in order to expand the investor base and

stimulate trade in the secondary market.

Strong demand for SBN, particularly from non-

resident investors, significantly pushed up prices. In

the first semester of 2017, the IDMA index, as a proxy

of SBN prices, jumped 4.59% from 99.09 to 103.64.

The benchmark 10-year SBN yield fell 111.7bps to

6.80%. The lower yields were accompanied by

less average volatility, decreasing from 10.38% in

the second semester of 2016 to 4.90% in the first

semester of 2017. In general, yields for all tenors

experienced declines, in particular the medium-term

tenors (6-10 years). Lower yields and volatility in the

SBN market during the first semester of 2017 were

echoed in other neighbouring countries. Although

investment risk in SBN eased, the future potential

risk of a sudden capital reversal demands vigilance.

The SBN to GDP ratio has continued to rise but

remains below other neighbouring countries. The

current SBN to GDP ratio is comparatively low

35%

15%

25%

5%

30%

10%

20%

0%

Mar

-12

Jun-

12

Sep-

12

Dec-

12

Mar

-13

Jun-

13

Sep-

13

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Graph 2.28. SBN to GDP Ratio

Indonesia ThailandMalaysia Philippines

Graph 2.29 Rebased 10-Year Benchmark Yields in Emerging Markets

Table 2.6 Regional 10-Year SBN Yields


INDO INDI THAI MALY FILIP

Dec-15 8.75 7.86 2.25 3.89 4.27

Jan-16 8.18 7.74 1.99 3.62 3.96

Feb-16 7.91 7.85 1.75 3.63 3.84

Mar-16 7.37 7.76 1.46 3.56 3.70

Apr-16 7.37 7.57 1.59 3.65 3.54

May-16 7.51 7.58 2.08 3.66 3.48

Jun-16 7.26 7.49 1.74 3.43 3.33

Jul-16 6.72 7.15 1.73 3.26 2.87

Aug-16 6.77 7.06 1.83 3.20 3.01

Sep-16 6.79 6.88 1.79 3.28 3.16

Oct-16 6.93 6.77 1.87 3.37 3.56

Nov-16 7.92 6.24 2.02 4.33 4.22

Dec-16 7.50 6.62 2.14 3.72 4.27

Jan-17 7.32 6.53 2.15 3.63 3.91

Feb-17 7.26 6.86 2.07 3.72 4.04

Mar-17 6.84 6.78 2.05 3.85 4.30

Apr-17 6.70 6.95 2.00 3.72 4.28

May-17 6.69 6.85 1.99 3.64 4.06

Jun-17 6.65 6.69 1.84 3.72 4.06

Table 2.7 Regional 10-Year SBN Yield Volatility


INDO INDI THAI MALY FILIP

Dec-15 15.45 3.47 8.57 13.14 44.29

Jan-16 12.20 2.57 24.13 12.62 20.61

Feb-16 7.56 5.66 41.71 11.86 31.95

Mar-16 14.42 4.57 21.01 8.37 26.02

Apr-16 6.76 6.62 31.36 10.86 20.09

May-16 8.13 1.81 45.47 28.62 11.25

Jun-16 9.79 2.69 46.81 7.38 22.05

Jul-16 12.50 6.49 21.88 25.72 65.48

Aug-16 10.21 3.20 16.27 10.27 32.05

Sep-16 9.24 6.43 23.47 11.97 13.50

Oct-16 9.00 2.54 23.89 14.82 17.27

Nov-16 29.95 14.95 22.90 46.69 18.69

Dec-16 21.04 14.98 20.98 33.67 21.26

Jan-17 8.84 5.07 17.12 13.29 95.10

Feb-17 4.60 14.51 10.46 10.23 29.65

Mar-17 8.49 10.85 11.59 11.71 16.43

Apr-17 7.57 7.46 11.23 5.66 6.78

May-17 8.75 4.59 9.75 10.10 9.97

Jun-17 2.54 8.94 20.38 9.20 3.50

Source: Bloomberg

150

70

110

30

Indonesia ThailandIndia Malaysia Philippines

130

50

90

Feb-

15

Feb-

16

Feb-

17

Aprl-

15

Aprl-

16

Aprl-

17

Jun-

15

Jun-

16

Jun-

17

Aug-

15

Aug-

16

Oct

-15

Oct

-16

Dec-

15

Dec-

16

rebased yield 1/1/2014

28%27%

14.9%17%

43BANK INDONESIA





5

3

4

2

1

0

Sem I

2014 2015 2016 2017

Net Flow Foreign Holdings of Outstanding Corporate Bonds (rhs)

2013

Sem I Sem I Sem ISem II Sem II Sem II

(1)

(2)

(3)

(4)

(5)

25RP Trillion

15

20

10

5

0

Graph 2.30. Net Foreign Flows and Foreign Holdings of Corporate Bonds

Source: Financial Services Authority (OJK) reports, processed Source: CEIC, processed

Table 2.8 Corporate Bond Holdings

Holder

2016 2017

Sem I Sem II Sem I

Total % Total % Total %

Corporations 9.39 3.60% 7.89 2.60% 8.19 2.51%

Individuals 6.54 2.51% 8.96 2.96% 9.96 3.05%

Mutual Funds 63.82 24.45% 78.72 25.99% 94.06 28.80%

Securities 0.84 0.32% 0.42 0.14% 0.83 0.26%

Insurance 41.58 15.93% 55.22 18.23% 58.85 18.02%

Pension Funds 68.80 26.36% 71.16 23.49% 72.89 22.31%

Financial Corporations 56.68 21.72% 65.38 21.58% 66.02 20.21%

Foundations 3.55 1.36% 3.76 1.24% 3.77 1.15%

Others 9.80 3.76% 11.42 3.77% 12.06 3.69%

TOTAL 261.00 302.92 326.64

RP Trillion

despite a surge of government financing through

SBN instruments. In March 2017, the SBN to GDP

ratio in Indonesia had reached 14.9%, up from

14.3% in the second semester of 2016. In the

region, the Philippines posted the highest SBN to

GDP ratio, followed by Thailand and Malaysia.

2.2.3.2. Corporate Bond Market

Congruent with less risk in the SBN market, risk in

the corporate bond market was also contained, with

lower yields and volatility. In the first semester of

2017, corporate bond yields of all ratings declined

on the previous period. In addition to rising prices,

stronger domestic corporate sector performance

also edged down yields. Consequently, corporate

bond volatility for all tenors averaged 4.27%, down

from 7.89%.

Departing from SBN trends, non-resident holdings

of corporate bonds actually declined. Outstanding

corporate bonds at the end of the first semester of 2017

increased by Rp23.72 trillion to a total of Rp326.64

trillion. Nevertheless, foreign holdings increased by

just Rp1.23 trillion, therefore the share dropped from

6.68% to 6.30% in the reporting period.

Domestic investors continued to dominate

corporate bond holdings. Three big institutional

groups, namely mutual funds, pension funds and

financial corporations, dominated corporate bond

holdings, increasing by 19.49%, 2.43% and 0.98%

respectively on the second semester of 2016. In terms

of accumulating funds, Indonesia’s upgraded credit

rating along with stable interest rates and exchange

rates prompted the financial sector to issue bonds

on a large scale in the pursuit of relatively cheap

funds. The surge of corporate bond issuances in the

first semester of 2017 was dominated by issuers

from the financial and infrastructure sectors.

2.2.4. Stock Market

Imitating bond market developments, milder risk

pressures were observed in the stock market, as

demonstrated by a rally on the Jakarta Composite

Index (JCI) and lower volatility compared to

conditions in the second semester of 2016 as an

aggregate and by sector. At the end of the first

semester of 2017, the JCI had rallied 10.06% to

5,829.7 on the position at the end of the previous

period. Various other countries in the region also

enjoyed stronger stock prices, including Thailand,

Malaysia and the Philippines. In addition to global

growth that surpassed previous expectations, the

rising profits of individual issuers also pushed up

stock prices. Furthermore, the resultant positive

sentiment lowered volatility in the reporting period.

44 BANK INDONESIA


15%

14

13

12

11

10

9

8

7

6

25

Short Term Long TermMedium Term

%

15

5

20

10

-

1 53 72 64 8 9 10

AAA Jun’16 AAA Jun’17 A Jun’16A Jun’17 BBB Jun’16 BBB Jun’17

Graph 2.31. Corporate Bond Yield Curve

Dec-

15

Feb-

16

Feb-

17

Apr-1

6

Apr-1

7

Jun-

16

Jun-

17

Aug-

16

Oct

-16

Dec-

16

Graph 2.32. Corporate Bond Yield Volatility by Tenor

Source: CEIC Source: Bloomberg, processed

180

Property

Rp Trillion

ConsumptionMiscellaneous IndustryMiningTrade

InfrastructureFinancialBasic IndustryAgriculture

60

140

20

100

160

40

120

0

Sem

II

2009 20132011 20152010 20142012 2016 2017

Sem

II

Sem

II

Sem

II

Sem

II

Sem

II

Sem

II

Sem

II

Sem

II

Sem

I

Sem

I

Sem

I

Sem

I

Sem

I

Sem

I

Sem

I

Sem

I

Sem

I

80

Graph 2.33 Corporate Bond Issuances by Economic Sector

Source: Financial Services Authority (OJK) reports, processed

By sector, stock price volatility was higher in the

miscellaneous industry and mining sectors than the

other sectors during the first half of the year. High stock

price volatility in the miscellaneous industry sector was

attributed to the volatility of Astra International stock

prices that accounted for 83% of total capitalisation

in the sector. Meanwhile, volatility in the mining

sector was caused by coal issuers as commodity prices

declined.

Daily transaction volume in the stock market was

relatively stable. The average daily transaction volume

stood at Rp7.74 trillion in the first semester of 2017,

down slightly on the Rp7.81 trillion registered in the

second semester of 2016. On the other hand, the

turnover ratio increased at the end of the first semester

of 2017, indicating that trade liquidity in the stock

market was maintained in the period.

Blue chip stocks were the backbone of the JCI rally in

the first half of 2017, with the LQ45 index climbing

10.51% from 884.62 in the second semester of 2016

to 974.08 in the first semester of 2017. By sector,

miscellaneous industry, consumption, the banking

sector and infrastructure were the main drivers of

the LQ45 index, consisting of Astra International,

HM Sampoerna, Unilever, BRI and Telkom, which

command a 49.57% share of LQ45 capitalisation.

45BANK INDONESIA






Source: Bloomberg, processed Source: Bloomberg


150rebased

130

110

140

120

100

90

80

Indonesia MalaysiaThailand Philippines

Jun-

14

Jun-

15

Jun-

16

Jun-

17

Mar

-14

Mar

-15

Mar

-16

Mar

-17

May

-14

May

-15

May

-16

Jun-

17

Jul-1

4

Sep-

14

Sep-

15

Sep-

16

Nov

-14

Nov

-15

Nov

-16

Jul-1

5

Jul-1

6

Graph 2.34 Stock Price Index Developments


Indonesia Dow JonesMSCI Euro MSCI Asia

45

35

25

15

5

40

30

20

10

0

Jan-

14

Jan-

15

Jan-

16

Jan-

17

Mar

-14

Mar

-15

Mar

-16

Mar

-17

May

-14

May

-15

May

-16

May

-17

Jun-

17

Jul-1

4

Jul-1

5

Jul-1

6

Sep-

14

Sep-

15

Sep-

16

Nov

-15

Nov

-15

Nov

-16

Graph 2.35 Stock Price Volatility

113

108

103

98

93

88

Aug-

11

Nov

-11

Feb-

12

Feb-

13

Feb-

14

Feb-

15

Feb-

16

Feb-

17

May

-12

May

-13

May

-14

May

-15

May

-16

Jun-

17

Aug-

12

Aug-

13

Aug-

14

Aug-

15

Aug-

16

Nov

-12

Nov

-13

Nov

-14

Nov

-15

Nov

-16

IndiaIndonesia PhilippinesThailand

Graph 2.36 Foreign Capital Flows to Regional Stock Markets

50 6,500

5,500

4,500

3,500

2,500

6,000

5,000

4,000

3,000

2,000Sem I

2017201620152014201320122011

Stocks

Rp (T)

%

JCI (rhs)

Sem ISem ISem I Sem IISem IISem II

30

10

40

20

0

-10

-20

-30

Graph 2.37 Foreign Net Buy/Sell in the Stock Market and JCI

35

25

15

30

20

10

5

Indonesia Thailand Malaysia Philippines Singapura

0

Jun-

15

Jul-1

5

Aug-

15

Sep-

15

Oct

-15

Nov

-15

Dec-

15

Jan-

16

Feb-

16

Mar

-16

Apr-1

6

May

-16

Jun-

16

Jul-1

6

Aug-

16

Sep-

16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7

May

-17

Jun-

17

Graph 2.38 Comparison of Regional Indexes

46 BANK INDONESIA


Source: Financial Services Authority (OJK)


Source: Bloomberg, processed Source: Bloomberg, processed

Table 2.9 Sectoral Index Volatility (Semester Average)

Sector2014 2015 2016 2017

Sem I Sem II Sem I Sem II Sem I Sem II Sem II

JCI 14.56 10.79 11.41 19.53 11.84 13.84 8.84

Financial 19.51 13.52 14.00 25.38 15.76 15.16 11.85

Agriculture 18.50 16.38 21.78 24.57 19.82 14.42 13.09

Basic Industry 21.21 16.17 16.22 31.85 16.79 17.65 12.60

Consumption 15.13 11.82 17.76 22.71 18.33 20.26 12.38

Property 21.55 17.75 17.13 21.71 13.66 16.23 12.59

Mining 15.95 15.49 13.25 18.09 18.95 21.92 15.62

Infrastructure 16.72 12.33 12.20 19.55 16.60 18.19 13.65

Trade 11.94 11.90 12.51 16.01 11.28 12.87 11.82

Miscellaneous Industry 24.02 19.42 22.73 36.11 27.93 27.64 20.46

0.25% 10

6

8

4

9

5

7

3210

0.15%

0.05%

0.20%

0.10%

0.00%Transaction Turnover

Turnover = daily transaction value/stock market capitalisation

Daily Transaction Volume (rhs)

Nov

-10

Feb-

11M

ay-1

1Au

g-11

Nov

-11

Feb-

12M

ay-1

2Au

g-12

Nov

-12

Feb-

13M

ay-1

3Au

g-13

Nov

-13

Feb-

14M

ay-1

4Au

g-14

Nov

-14

Feb-

15M

ay-1

5Au

g-15

Nov

-15

Feb-

16M

ay-1

6Au

g-16

Nov

-16

Feb-

17M

ay-1

7Ju

n-17

Rp T

Graph 2.39 Stock Market Turnover

7.000 80%

60%

70%

50%

75%

55%

65%

45%

40%

5.000

3.000

250 rebased 100: Jan’10

Spread (rhs) EBITDA (rebased) IHSG (rebased)

150

200

100

50

0

6.000

4.000

2.000

1.000

0

2005

2009

2013

2007

2011

2015

2006

2010

2014

2008

2012

2016

2017

Rp T

JCI Cap LQ45 Cap LQ45 Share (rhs)

Graph 2.40 JCI and LQ45 Capitalisation

80

60

40

20

0

70

50

30

10

-10

Feb-

10

Jun-

10

Oct

-10

Feb-

11

Jun-

11

Oct

-11

Feb-

12

Jun-

12

Oct

-12

Feb-

13

Jun-

13

Oct

-13

Feb-

14

Jun-

14

Oct

-14

Feb-

15

Jun-

15

Oct

-15

Feb-

16

Jun-

16

Oct

-16

Feb-

17

Jun-

17

Graph 2.41 EBITDA and JCI Performance

4 Mutual funds are an investment vehicle and management style made up of a pool of moneys collected from a group of investors for the purpose of investing in a mutual fund unit.

Those five issuers alone enjoyed gains averaging

19.71% in the first half of 2017, accompanied by

stronger performance at other issuers, as indicated

by increases in EBITDA.

2.2.5. Mutual Funds4

The performance of mutual funds has continued to

improve on the back of stronger underlying asset

prices in the stock and SBN markets. In the first

semester of 2017, the net asset value (NAV) grew

15.7%, up from 7.0% in the previous period. In

terms of value and share, fixed-income and protected

funds were the main drivers of net asset value in the

reporting period. Fixed-income and protected funds

posted growth of 20.87% and 12.26% respectively

in the first half of the year, accounting for 47.42%

of total mutual funds. Furthermore, NAV volatility

in the three main markets was also observed to

47BANK INDONESIA





Source: Financial Services Authority (OJK) reports




450

Total Mutual Funds (rhs) NAV(Rp, trillions)

Units in Circulation (millions)

350

250

150

50

400

300

200

100

0

1800

1000

1400

600

1600

800

1200

400

200

0

Jun

Jun

Jun

Jun

Aug

Aug

Aug

Oct

Oct

Oct

Dec

Dec

Dec

Feb

Feb

Feb

Apr

Apr

2015 2016 2017

Apr

Graph 2.42. The Performance of Mutual Funds

450Rp T

250

350

150

50

400

200

300

100

0

Juli

Juli

Juli

Juli

Sept

Sept

Sept

Sept

Nov

Nov

Nov

NovJan

Jan

Jan

Jan

Mar

Mar

2014

Equity Money Market Mixed Fixed Protected Other Funds

20162015 2017

Mar

Mar

May

May

May

Juni

Graph 2.43 NAV of Mutual Funds by Fund Type

45

Fixed Income Funds Mixed Funds Equity Funds

25

35

15

5

40

20

30

10

0

Jun-

15

Jul-1

5

Aug-

15

Sep-

15

Oct

-15

Nov

-15

Dec-

15

Jan-

16

Feb-

16

Mar

-16

Apr-1

6

May

-16

Jun-

16

Jul-1

6

Aug-

16

Sep-

16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7

May

-17

Jun-

17

Graph 2.44 NAV Volatility of Mutual Funds by Fund Type

40%

NAVUnits in Circulation Total Mutual Funds JCIIDMA

20%

30%

0%

20%

-10%

-20%

-30%

Jan

Jan

Jan

Jan

Jan

Mar

Mar

Mar

Mar

Mar

May

May

May

May

MayJuly

July

July

July

Sept

Sept

Sept

Sept

Nov

Nov

Nov

Nov

2013 2014 2015 2016 2017

Graph 2.45 Growth of Mutual Funds (yoy)

decline. The most volatile funds were mixed funds

and equity funds.

All fund types experienced stronger returns in

the reporting period, which is presented in the

risk profile quadrant, where most funds were in a

position of excess return in June 2017 (red dots)

compared to the respective positions in December

2016 (green dots). In terms of risk, mutual fund

volatility for stocks and bonds also declined in the

first semester of 2017 in line with less risk in the

underlying assets.

The growth of closed-end and open-ended funds

reached 12.26% and 16.80% respectively, up from

20.60% and 5.45%. Robust growth stemmed from

keen investor interest due to low risk because the

risks of the underlying assets were contained.

48 BANK INDONESIA


2.0

1.0

0.0

-1.0

-2.0

-3.0

-4.0

-5.0

30

20

10

0

-10

-20

-30

-40-1.5

Dec’16

Dec’16

Jun’16

Jun’16

Jun’17

Jun’17

-1.0 0.0 1.0-0.5 0.5 1.5 2.0

Excess

Return

Equity Funds Fixed Income Funds

Mixed Funds Money Market Funds

-0.5 -0.3 -0.1 0.1 0.3 0.5

Excess

Return

Dec’16

Jun’16

Jun’17

10

5

0

-5

-10

-15

-2.5 -1.5 -0.5 0.5 1.5 2.5

Excess

Return

Dec’16

Jun’16

Jun’17

25

15

5

-

(5)

(10)

(15)

(20)

(25)-3 -2 -1 0 1 2 3

20

10

Excess

Return

Jan

Jan

Jan

May

May

MaySep

Sep

Mar

Mar

MarJu

l

Jul

Nov

Nov

300Rp T

Rp T

220

140

260

180

100

Open Ended Closed End (rhs)

280

200

120

240

160

140

20

180

60

100

200

80

120

-

160

40

Graph 2.47 NAV of Open-Ended and Closed-End Mutual Funds



Graph 2.46 Risk Profile of Mutual Fund Products

49BANK INDONESIA





2.3.1. Islamic Capital Market

Congruous with capital market conditions in

general, the Islamic capital market also performed

well in the first half of the year. According to the

market capitalisation value of the Indonesia Sharia

Stock Index (ISSI), outstanding government and

corporate sukuk as well as Islamic mutual funds

achieved positive growth. Vibrant Islamic capital

market instruments reflected the expanding role

of the Islamic financial sector as an alternative

national source of financing to the conventional

financial sector. As of June 2017, the capitalisation

2.3. Islamic Financial Market Dynamics and Risks

Source: Bloomberg and OJK Stock Statistics

Source: Bloomberg and OJK Stock Statistics

3,500% %

Rp T

rillio

n

3,497

503

16 18

15

32

42

79

2,500

1,500

0

2,500

1,500

500

Indonesia Sharia Stock Index (ISSI)

Capitalisation


Capitalisation

Outstanding Government Sukuk


Outstanding Corporate Sukuk


NAV of Islamic Mutual Funds


-

90

Jun-17 (%yoy)Jun-17 Dec-16 (%yoy)Dec-16

50

70

30

80

40

60

20

10

-

Graph 2.48 Accumulated Funds in the Islamic Capital Market

Graph 2.49 Average Growth of Islamic Capital Market

3,500

Rp T

rillio

n

Rp T

rillio

n

4,000 20

12

16

8

2

18

10

4

14

6

0

2017

503

16

18

3,491

20162015

2,500

1,500

0

3,000

2,000

1,000

Outstanding Sukuk NegaraOutstanding Government Sukuk NAV of Islamic Mutual Funds (rhs)Indonesia Sharia Stock Index (ISSI) Capitalisation

Graph 2.50 Islamic Capital Market Developments

Jul

Aug

Sep

Oct

Nov De

c

Jan

Feb

Mar Ap

r

Mei

Jun Jul

Aug

Sep

Oct

Nov De

c

Jan

Feb

Mar Ap

r

Mei

Jun

value of Islamic stocks had reached Rp3,497 trillion.

Moreover, outstanding government and corporate

sukuk were recorded at Rp503 trillion and Rp15.8

trillion respectively. Meanwhile, the NAV of

outstanding Islamic mutual funds also increased,

amounting to Rp17.7 trillion in the reporting period.

Of the Islamic financial market instruments available,

Islamic mutual funds posted the strongest gains in

the first half of 2017, namely 78.9%, which was

consistent with the growth of government and

corporate sukuk, exceeding 30%, thereby creating

more Islamic mutual fund portfolio choices in

accordance with the risk appetite of the respective

investors. As of June 2017, outstanding corporate

sukuk growth had accelerated from 23.7% (yoy)

50 BANK INDONESIA


60% 54.68%

16.86%

4.82% 4.73%

20%

40%

0%

50%

10%

30%

Jun-17 Dec-16

Graph 2.51 Islamic Capital Market Share

Source: Bloomberg

350

400

250

150

0

300

200

100

2010 20132011 2014 20162012 2015 2017

Sem I Sem ISem I Sem I Sem ISem I Sem I Sem ISem II Sem IISem II Sem II Sem IISem II Sem II

Graph 2.52 Islamic Securities List Table 2.10 Distribution of the Islamic Securities List

Source: Bloomberg

Period

SecuritiesTotal

SecuritiesListed Public Not Listed IPO

2014 Sem I 301 4 12 5 322

Sem II 314 4 13 3 334

2015 Sem I 313 4 13 4 334

Sem II 315 4 12 4 335

2016 Sem I 307 4 10 0 321

Sem II 332 4 9 0 345

2017 Sem I 335 4 12 0 351

Source: Islamic Securities List, Financial Services Authority (OJK)

to 42.07% (yoy), with the total increasing from

Rp12.25 trillion in December 2016 to Rp15.79

trillion.

In terms of the instruments, the share of the Islamic

capital market has been leading other Islamic financial

market instruments. The contribution of Islamic stock

market capitalisation to the national total has reached

54.68%. Meanwhile, the market share of government

sukuk to new government debt securities accounted

for 16.86% and is continuing to expand. On the other

hand, the share of corporate sukuk to new corporate

bonds has reached 4.82% and the NAV contribution

of Islamic mutual funds to new national mutual funds

accounted for 4.73%. The main challenge now faced

in terms of sukuk expansion is limited underlying.

2.3.2. Islamic Stock Market Performance

The performance of Islamic stock issuers in the

first half of 2017 improved in line with the robust

market capitalisation growth of the Indonesia

Sharia Stock Index (ISSI) at 54.68% (yoy), which has

remained stable since the first semester of 2016

at 56.17% (yoy) and then at 55.11% (yoy) in the

second semester of 2016. ISSI market capitalisation

increased to Rp3,491 trillion at the end of the

first semester of 2017, up from Rp3,170 trillion

in the previous period. Solid Islamic stock issuer


Capitalisation




51BANK INDONESIA







201720162015

3,500

5,500

6,500

4,000

6,000

7,000 6

4

1

5

2

3

0

2,500

4,500

3,000

5,000

2,000

Rp T

rillio

n

Thou

sand

JCI Capitalisation

ISSI Index (rhs) JCI Index (rhs)

ISSI Capitalisation

Graph 2.53. JCI and ISSI Comparison

20

40

0

10

-10

-20

30

ISSI JCI

201720162015

Graph 2.54 Market Capitalisation Growth (yoy)

Indeksi ISSI Indeks IHSG

22

12

17

7

-3

2

-8

-13 Dec-15 Dec-16Jun-16 Jun-17

Jul

Aug

Sep

Oct

Nov De

c

Jan

Feb

Mar Ap

r

May Jun Jul

Aug

Sep

Oct

Nov De

c

Jan

Feb

Mar Ap

r

May Jun

Jul

Aug

Sep

Oct

Nov De

c

Jan

Feb

Mar Ap

r

May Jun Jul

Aug

Sep

Oct

Nov De

c

Jan

Feb

Mar Ap

r

May Jun

%%

performance has contributed favourably towards

total JCI issuer performance, with Islamic stocks

now accounting for 54.68% of the total.

The number of corporate issuers registered on the

Islamic Securities List as of June 2017 totalled 351.

Of the total, three were bona fide Islamic entities

and 348 did not state whether their businesses

were managed based on sharia principles but they

did meet the criteria to issue Islamic stocks pursuant

to Regulation Number II.K.1 concerning the Criteria

and Publication of the Islamic Securities List.

The large portion of ISSI issuers in the JCI

precipitated co-movement between the two. At

the end of the first semester of 2017, ISSI stood at

185.22 points, climbing 13.1 points on the position

at the end of 2016. Meanwhile, ISSI volatility was

recorded at 10.35 points, down from 16.44 points

and, therefore, more stable. On the other hand,

the Jakarta Islamic Index (JII), as a composite of 30

highly liquid Islamic stocks, was more volatile than

the ISSI and JCI.

2.3.3. Islamic Mutual Funds

Net asset value (NAV) growth of Islamic mutual funds

outstripped conventional mutual funds throughout

the first semester of 2017. Nevertheless, the market

share (contribution) of Islamic mutual funds to the

national total remained relatively small at 4.73% but

expanding from 4.31% in the second semester of

2016.

52 BANK INDONESIA


1,20

ISSI JII

LQ45 JCI (rhs)

7

3

5

1

6

2

4

-

0,80

0,80

1,00

Thou

sand

Thou

sand

0,60

0,40

-

2017 20172016 20162015 2015

Jan

Feb

M

ar A

pr M

ay Ju

n Jul

Aug

Sep

Oct

Nov De

c

Jan

Feb

Mar

Apr

May

Jun Jul

Aug

Sep

Oct

Nov De

c

Jul

Aug

Sep

Oct

Nov De

c Jul

Aug

Sep

Oct

Nov De

c

Jan

Feb

Mar Ap

rM

ay Jun Jan

Feb

Mar

Apr

May

Jun

Graph 2.55 Islamic Stock Indexes

35

45

40

50

25

15

JCI Volatility ISSI Volatility JII Volatility

5

0

30

20

10

Graph 2.56. Stock Index Volatility

19,000

NAV of Islamic Mutual Funds NAV Share of Islamic Mutual Funds

6.00%

4.00%

1.00%

5.00%

2.00%

3.00%

0.00%

15,000

11,000

7,000

17,000

13,000

9,000

5,000

201720162015

Jul

Aug

Sep

Oct

Nov

Dec

Jan

Feb

Mar

Apr

May

Jun Jul

Aug

Sep

Oct

Nov

Dec

Jan

Feb

Mar

Apr

May

Jun

Graph 2.57 Net Asset Value of Islamic Mutual Funds

120

Islamic Mutual Funds Conventional Mutual Funds

80

80

20

-40

100

60

40

-20

0

201720162015

Jul

Aug

Sep

Oct

Nov

Dec

Jan

Feb

Mar

Apr

May

Jun Jul

Aug

Sep

Oct

Nov

Dec

Jan

Feb

Mar

Apr

May

Jun

Graph 2.58 NAV Growth of Islamic Mutual Funds

Source: Bloomberg, processedSource: Bloomberg, processed

Source: OJK Capital Market Statistics, processed

%

At the end of the first semester of 2017, the NAV of

Islamic equity funds continued to dominate Islamic

mutual funds with a net asset value of Rp9.7 trillion

or 54.74% of the total, followed by Islamic fixed

income and protected funds, accounting for 14.0%

and 11.68% respectively. Meanwhile, Islamic

indexed funds were least dominant, with a net

asset value of Rp170 billion and accounting for just

0.96% of total NAV.

2.3.4. Government Sukuk

The share of government sukuk to state budget

financing has continued to grow. Nevertheless,

issuances of government sukuk declined in

the reporting period in line with the dwindling

requirement to finance the 2017 state budget.

Consequently, issuances of government sukuk in

the first half of 2017 stood at Rp121.87 trillion,

down from Rp138.74 trillion in the same period

one year earlier. Notwithstanding the decline, the

share of government sukuk to government bonds

has increased year on year. At the first semester of

2017, the share of government sukuk had reached

30.85% of total government bonds, increasing from

27.60% in 2016, reflecting growing government

support for Islamic financial market deepening

as well as growing public awareness of sukuk

instruments.

53BANK INDONESIA





54.74%

7.28%

10.44%

14.90%

11.68%

0.96%

Equity

Mixed

Money Market

Fixed Income

Protected

Indexed

Graph 2.59 NAV of Islamic Mutual Funds by Fund Type

Rp B

illio

n

1,600

1,346

934

PBS SDNI SNI SPNS SPNSNT SR ST

144

Jun-2017Jun-2016Jun-2015

1,200

800

400

1,400

1,000

600

200

-

Graph 2.61 Sukuk Issuances by Type

5,000

4,000

3,000

2,000

1,500

4,500

3,500

2,500

2,500

500

2014

Sukuk SUN

2015 2016 Jun-17

1,91

4

3,40

1

1,90

1

4,55

0

991

878

145 137

0

Rp T

rillio

n

Graph 2.60 Issuances of Government Securities


Source: Directorate General of Budget Financing and Risk Management (DJPPR), Ministry of Finance, processed


In terms of sukuk issued by the government,

Project-Based Sukuk (PBS) were dominant in the

first semester of 2017, totalling Rp40.82 trillion,

followed by Global Sukuk (SNI), totalling Rp39.97

trillion. SNI are issued in the international market

denominated in USD with tenors of 5-10 years

and underlying assets in the form of State-Owned

Assets (BMN). Project-Based Sukuk (PBS) were

dominant, with underlying projects funded by the

state budget. Outstanding PBS reached Rp194

trillion, growing 55.05% (yoy).

In terms of maturity, long-term sukuk continued

to dominate outstanding government sukuk but

the short-term tenors began to increase. The value

of outstanding government sukuk with a tenor

of more than 10 years reached Rp193.3 trillion in

the first semester of 2017, rising from Rp159.7

trillion in the second semester of 2016. Meanwhile,

Islamic Treasury Bills (SPNS) also posted solid gains,

increasing from Rp9.28 trillion in the first semester

of 2016 to Rp25.05 trillion in the reporting period.

Based on ownership, the share of the banking

industry in terms of tradeable sukuk continued to

lead but had begun to decline. At the end of the

first semester of 2017, banking industry holdings

of government sukuk accounted for 46.38%,

54 BANK INDONESIA


Jan-

15Fe

b-15

Mar

-15

Apr-1

5M

ay-1

5Ju

n-15

Jul-1

5Au

g-15

Sept

-15

Oct

-15

Nov

-15

Dec-

15Ja

n-16

Feb-

16M

ar-1

6Ap

r-16

May

-16

Jun-

16Ju

l-16

Aug-

16Se

pt-1

6O

ct-1

6N

ov-1

6De

c-16

Jan-

17Fe

b-17

Mar

-17

Apr-1

7M

ay-1

7Ju

n-17

600 18%

10%

14%

6%

2%

16%

8%

12%

4%

0%

400

200

500

300

100

0

Value of Outstanding Islamic Government Securities

Share of Outstanding Value of Islamic Government Securities

RP T

rillio

n

Graph 2.62 Outstanding Government Sukuk

70.00%

30.00%

50.00%

10.00%

60.00%

20.00%

40.00%

0.0%

Jan-

15Fe

b-15

Mar

-15

Apr-1

5M

ay-1

5Ju

n-15

Jul-1

5Au

g-15

Sept

-15

Oct

-15

Nov

-15

Dec-

15Ja

n-16

Feb-

16M

ar-1

6Ap

r-16

May

-16

Jun-

16Ju

l-16

Aug-

16Se

pt-1

6O

ct-1

6N

ov-1

6De

c-16

Jan-

17Fe

b-17

Mar

-17

Apr-1

7M

ay-1

7Ju

n-17

Government Islamic Securities (SBSN) SUN

Graph 2.63 Growth of Outstanding SBN

Jan-

15Fe

b-15

Mar

-15

Apr-1

5M

ay-1

5Ju

n-15

Jul-1

5Au

g-15

Sept

-15

Oct

-15

Nov

-15

Dec-

15Ja

n-16

Feb-

16M

ar-1

6Ap

r-16

May

-16

Jun-

16Ju

l-16

Aug-

16Se

pt-1

6O

ct-1

6N

ov-1

6De

c-16

Jan-

17Fe

b-17

Mar

-17

Apr-1

7M

ay-1

7Ju

n-17

Jan-

15Fe

b-15

Mar

-15

Apr-1

5M

ay-1

5Ju

n-15

Jul-1

5Au

g-15

Sept

-15

Oct

-15

Nov

-15

Dec-

15Ja

n-16

Feb-

16M

ar-1

6Ap

r-16

May

-16

Jun-

16Ju

l-16

Aug-

16Se

pt-1

6O

ct-1

6N

ov-1

6De

c-16

Jan-

17Fe

b-17

Mar

-17

Apr-1

7M

ay-1

7Ju

n-17

100

80

60

40

20

0

IFR

%

PBS SDHI SNI

SPNS SPNSNT SR ST

Graph 2.64 Composition of Sukuk based on SBSN Series

<1 Year >10 Years

1-5 Years 5-10 Years

100

80

60

40

20

0

%

Graph 2.65 Composition of Sukuk based on Maturity





down from 50.28% in the second semester of

2016. Conventional banking industry holdings

of government sukuk stood at 36%, while the

insurance and Islamic banking industries accounted

for 18.9% and 9.6% respectively. Individual

holdings of government sukuk also increased as

issuances of retail sukuk flourished, reaching Rp24.4

trillion or representing 8.19% of the total tradeable

government sukuk.

2.3.5. Corporate Sukuk and Bonds

In the first semester of 2017, the total and value

of outstanding corporate sukuk increased. There

was a total of 69 corporate sukuk available with

an outstanding value of Rp15.17 trillion, as growth

accelerated from 23.74% (yoy) to 41.09% (yoy).

The market share of corporate sukuk increased

slightly to 4.3% from 3.8% in the previous period.

Mutual funds tended to dominate corporate sukuk

holdings, accounting for 39.97% of the total,

while individual holdings remained relatively stable

at Rp104.75 billion, accounting for 0.66% of

corporate sukuk in the reporting period.

2.3.6. Socioeconomic Sector

The annual accumulation and disbursement of

zakat, infak and sedekah (ZIS) funds experienced

gains but more so on the accumulation side, which

undermined the efficiency of ZIS funds by zakat fund

management organisations in the first semester of

2017. On one hand, greater accumulation of ZIS

funds was linked to improving management and

fund disbursement governance and transparency at

Amil Zakat Institutions and Nazhir Institutions.

The accumulation of ZIS funds grew 5.60% (ytd) in

the first semester of 2017, compared to 3.67% (ytd)

for disbursements. Such developments confirm that

55BANK INDONESIA





Jan-

15Fe

b-15

Mar

-15

Apr-1

5M

ay-1

5Ju

n-15

Jul-1

5Au

g-15

Sept

-15

Oct

-15

Nov

-15

Dec-

15Ja

n-16

Feb-

16M

ar-1

6Ap

r-16

May

-16

Jun-

16Ju

l-16

Aug-

16Se

pt-1

6O

ct-1

6N

ov-1

6De

c-16

Jan-

17Fe

b-17

Mar

-17

Apr-1

7M

ay-1

7Ju

n-17

Conventional Banks

%

Islamic Banks Insurance Pension FundsIndividual Mutual Funds Foreign Others

100

90

80

70

60

50

40

30

20

10

0

Graph 2.66 Holdings of Tradeable Government Islamic Securities (SBSN)

Jan-

16

Feb-

16

Mar

-16

Apr-1

6

May

-16

Jun-

16

Jul-1

6

Aug-

16

Sept

-16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7

May

-17

Jun-

17

80.00

60.00

40.00

20.00

10.00

%

Outstanding Corporate Sukuk Outstanding Corporate Bonds

Graph 2.67. Growth of Corporate Bonds and Sukuk

17.00

15.00

13.00

11.00

9.00

7.00

5.00

5.0%4.5%4.0%3.5%3.0%2.5%2.0%1.5%1.0%0.5%0.0%

Rp Trillion

Market Share of Outstanding Sukuk (rhs) Outstanding Corporate Sukuk

Jan-

15Fe

b-15

Mar

-15

Apr-1

5M

ay-1

5Ju

n-15

Jul-1

5Au

g-15

Sept

-15

Oct

-15

Nov

-15

Dec-

15Ja

n-16

Feb-

16M

ar-1

6Ap

r-16

May

-16

Jun-

16Ju

l-16

Aug-

16Se

pt-1

6O

ct-1

6N

ov-1

6De

c-16

Jan-

17Fe

b-17

Mar

-17

Apr-1

7M

ay-1

7Ju

n-17

Graph 2.68 Market Share of Corporate Sukuk

6,309.72

2,354.92

2,544.26

3,391.00

2.00

355.50 697.85104.75

25.00

Graph 2.69 Corporate Sukuk Holdings

3,767.59

12,064.008,216.01 9,974.40

834.97

58,867.58

94,337.80

72,885.91

66,586.47

Graph 2.70 Corporate Bond Holdings

Mutual Funds

Pension Funds

Securities

Financial Institutions

Insurance

Foundations

Others

Corporate

Individual



Source: OJK Capital Market Statistics, processed Source: OJK Capital Market Statistics, processed

public commitment to zakat and infak funds remains

high, but the gains are unbalanced by the inabilities

of zakat management organisations when disbursing

ZIS funds. The Allocation to Collection Ratio (ACR),

as a measure of ZIS fund management efficiency,

deteriorated slightly on the previous period, falling

from 60.6% to 59.5%. Nonetheless, the high ACR

also shows that ZIS fund management is still efficient.

Regionally, provinces in Western Indonesia continued

to dominate the accumulation and disbursement of

zakat funds in the first half of 2017, with more than

40% originating from West Java, Riau, East Java and

West Sumatra. On the other hand, disbursements

of zakat funds were dominated by the provinces of

West Java, Riau, West Sumatra, East Java and the

Riau Islands.

56 BANK INDONESIA


3,30

0

2,03

4

3,65

3

2,25

2

4,06

6

2,46

6

4,25

9

2,52

7

4,500

3,500

2,500

1,500

500

4,000

3,000

2,000

1,000

0

62%

61%

60%

59%

58%

57%

56%

55%Sem I 2017201620152014

Rp B

illio

n

Total Accumulation Total Disbursements ACR (rhs)

Graph 2.71 Accumulation and Disbursement of Zakat Funds

Accumulation Disbursement

Graph 2.72 Accumulation and Disbursement of Zakat Funds by Province

14.98%

16.54%

9.59%

8.28%

6.71%

43.90%48.49%

16.51%

10.29%

8.99%

8.60%

7.12%

East Java

Other Provinces

East Kalimantan

West Sumatra

West Java

Riau

West Sumatra

Other Provinces

East Java

Riau Islands

West Java

Riau

Source: National Amil Zakat Board (Baznas) Mustahik Information System (SIMBA), processed

Source: National Amil Zakat Board (Baznas) Mustahik Information System (SIMBA), processed

60.65%

59.34%

Moving forward, the social financial sector has a

bright outlook as zakat management institutions

continue to consolidate and integrate in pursuance

of Islamic principles, amanah, wellbeing, fairness,

legal assurance and accountability in order to

improve the effectiveness and efficiency of zakat

management services in accordance with Act No.

23 of 2011 concerning Zakat Management.





57BANK INDONESIA

Box 2.1. The National Financial Market Development Strategy (SN-PPK)

Indonesia’s financial markets have evolved through

several historical phases, including banking

deregulation in 1988, the Asian Financial Crisis in

1997, the Global Financial Crisis in 2007 as well as

the quantitative easing policy adopted by central

banks in advanced economies in 2008 that persists

to this day. Transitioning those phases has involved

several changes of direction and appetite for

financial market development, mirroring prevailing

economic dynamics and financial market risks.

Actual financial market development is inextricably

linked to economic growth. The existing literature

on economic growth discusses the premise of the

finance-led growth hypothesis, where financial

market development accelerates economic growth.

This argument is justified considering that the

financial markets function as the blood flow of the

economy, so efforts to stimulate financial market

development would surely precipitate stronger

economic growth. In this regard, the financial

markets function as a source of economic financing

and tools to regulate the efficient allocation of

resources.

In addition to the function of stimulating economic

growth, developing financial markets also play

a role in the effective transmission of the central

bank’s monetary policy. This role manifests through

the short-term interest rate structure (yield curve)

and exchange rates. A liquid and efficient money

market will create a responsive short-term interest

rate structure to the central bank’s monetary policy

stance and provide a feedback loop concerning

liquidity conditions in the money market. Meanwhile,

healthy supply-demand dynamics in the foreign

exchange market support exchange rate stability

and attainment of the inflation target.

Evolving financial markets also support financial

system stability, exhibited through a solid financial

market structure that can absorb the shocks

that emerge. A solid financial market structure

is achieved through a high transaction volume,

a broad investor base, diverse instruments and

reliable infrastructure.

Financial market evolution in Indonesia has been

characterised by rapid banking industry development,

followed by the capital market, insurance industry,

pension funds and other financial institutions. The

advantage of bank financing is the ability to better

mitigate the risks associated with asymmetric

information, considering that the banking industry

has the capacity to analyse and select quality

borrowers, thereby ensuring a more prudent credit

intermediation process. Nevertheless, problems can

arise when economic funding is too concentrated in

the banking industry. One problem is limited access

to funding for the borrowers and limited investment

alternatives for the lenders/investors. On the other

hand, bank capacity to lend is becoming restrained,

as evidenced by the rising loan-to-deposit ratio.

There is also the potential for certain high-risk sectors to

not receive funding due to a lack of alternative lenders

outside of the banking industry. In terms of the cost of

funds, the absence of alternative instruments outside

of the banking industry leads to a dearth of adequate

competition, which prompts a suboptimal cost of


58 BANK INDONESIA

funds. Such conditions imply constraints in Indonesia’s

financial markets in terms of funding sources, thus

necessitating alternative funding sources outside of

the banking sector, both short and long term.

Financial market development in Indonesia over the

past 10 years has been relatively stagnant. One problem

that has been identified is a lack of integrated financial

market development initiatives due to the cross-cutting

nature of the relevant authorities. In that context,

Bank Indonesia is responsible for the development

and supervision of the money market and foreign

exchange market, including the development of

instruments and all supporting elements. On the other

hand, the Indonesia Financial Services Authority (OJK)

has jurisdiction over the development and supervision

of all financial services institutions. Furthermore, the

Ministry of Finance is authorised to issue government

bonds and set tax policy, which also pertains to financial

institutions and services.

To overcome the cross-cutting, Bank Indonesia, the

Financial Services Authority (OJK) and Ministry of

Finance established the Financial Market Development

and Deepening Coordination Forum (FK-PPPK) in 2016,

which was an important first step in accelerating the

financial sector revitalisation process as one of financial

markets in the region with the most potential. The

Forum was also established in response to government

policy focused of infrastructure financing, which would

definitely require new sources of funding.

The Financial Market Development and Deepening

Coordination Forum advocated preparation of

a National Financial Market Development and

Deepening Strategy as a joint endeavour between

Bank Indonesia, the Financial Services Authority (OJK)

and Ministry of Finance. Through the national strategy,

the relevant authorities and stakeholders would

seek breakthroughs to accelerate financial market

deepening and development in terms of boosting

transaction volume and value, strengthening the

investor base and other market players, developing

diverse financial products, strengthening infrastructure

commensurate with technological advances, as well

as regulate and standardise optimal industries in line

with best practices.

Financial market deepening is hoped to be achieved

within eight years. According to the National Strategy,

the main targets will be accomplished through three

phases applied to the six respective financial markets

as follows:

1. Strengthening the Foundations – Phase 1 (207-

2019)

2. Acceleration – Phase 2 (2020-2022)

3. Deepening – Phase 3 (2023-2024)

The phases were designed to map the various

initiatives based on priority, while promoting initiative

continuity in each respective phase, thereby achieving

the main objectives. The National Financial Market

Development and Deepening Strategy is targeted

for completion in the first half of 2018, containing

a detailed work plan and strategic action plan for

each market. The uniform vision and united platform

contained in the comprehensive national strategy,

coupled with a measured work program, is expected

to establish deep, liquid and efficient financial markets

that support the national economy.





59BANK INDONESIA

7 Financial Market Ecosystem Elements

TARGETS

Sources ofEconomic Financing

and Risk Management

Fund Availability and Utilisation

Instruments

Intermediaries

Benchmark Rate and Standardisation Coordination and Education

KEY PERFORMANCE INDICATORS

Market Infrastructure Development

Market Infrastructure

Policy Coordination -Regulatory Harmonisation

Regulatory Framework

Money Market Foreign Exchange Market Bond Market Stock Market Islamic Financial

MarketStructured Product

Market

VISION :Create Deep, Liquid, Efficient,

Inclusive and Secure Financial Markets

MISSION : Financial Markets as Sources of National Development Financing

1 2 33 Pillars

6 Markets

Box Figure 2.1.1.Financial Market Development Framework

STRATEGIC ACTION PLAN


60 BANK INDONESIA

Box 2.2. Regulating Treasury Certification and Implementing a Market Code of Conduct

The Importance of Enhancing Integrity and the

Raising the Competence Standards of Financial

Market Professionals

Strengthening financial market credibility is a

crucial component of creating effective, efficient

and healthy financial markets. A credible financial

market creates trust through assurance and good

governance in every transactional aspect. Therefore,

strengthening credibility is one of the agenda items

of financial market development by Bank Indonesia.

One of Bank Indonesia’s programs in this area is to

enhance the competence and integrity of market

professionals through an initiative to create integrity

and competence standards for financial market

professionals, particularly in the money market,

foreign exchange market and derivatives market.

The domestic financial markets currently face a

suboptimal level of integrity. A BI survey of market

professionals conducted in 2016 revealed several

weaknesses, including the lack of a code of conduct

and internal guidelines at financial institutions

to implement a code of conduct as well as broad

competence gaps and few certified dealers.

The Association of Market Professionals responded

by publishing a Code of Conduct. The Indonesian

Foreign Exchange Market Committee (IFEMC)

and Associate Cambiste Internationale-Financial

Market Association Indonesia (ACI-FMA Indonesia)

published the first edition of the IFEMC Code of

Conduct (known as the Brown Book) in May 2014.

Facilitated by Bank Indonesia, the Brown Book was

refined through the adoption and inclusion of an

international code of conduct, namely the Model

Code of ACI FMA International, leading to the

second edition of the Brown Book published in

August 2016. The new standards were expected to

become a reference for the market professionals,

especially those in the money market, foreign

exchange market and derivatives market.

Several financial market professions are accredited

through certification, including the capital market

and banking industry, to support financial market

competence. In terms of the capital market industry,

the Financial Services Authority (OJK) currently

requires professionals to obtain four types of

certification, namely broker-dealer representatives,

underwriter representatives, investment manager

representatives and investment fund selling agent

representatives. On the other hand, there are

currently nine certificates in the banking industry,

including internal audit, wealth management,

treasury dealer, general banking, risk management,

compliance, credit, operations as well as funding

& services. Prevailing regulations only require bank

employees to obtain a risk management certificate

in accordance with their respective position at the

bank.

Bank Indonesia has already introduced competence

standards for the Treasury. Dealers in work units at

the Bank Indonesia Treasury are required to obtain

Treasury Certification pursuant to Bank Indonesia

Regulation (PBI) No. 19/5/PBI/2017, issued in April

2017. Enhanced competence through treasury

certification is vital because the competences

gained are not merely restricted to technical

activities but also encompass the code of conduct





61BANK INDONESIA

and understanding financial market regulations.

In practice, the requirement to hold a treasury

certificate is not just limited to treasury dealers in the

banking industry, but brokers in the money market

and foreign exchange market as well as securities

companies are also required to hold a treasury

certificate because such businesses also undertake

treasury activities, especially in the money market

and foreign exchange market.

Quality standards at certified institutions must be

maintained in line with the prevailing requirements.

The practices and curriculum of treasury certification

must be in accordance with the needs of the domestic

market professionals and refer to international

best practices. To that end, certified professional

institutions must be recognised and routinely

coordinate with the relevant authorities in order

to develop and refine the future curriculum and

practices in line with guidance from the authorities.

Emulating implementation in other countries, the

requirement for certified treasury professionals is

regulated either by the financial market authority or

the related financial market association. In addition,

professionals are also required to become a member

of a financial market or treasury association to enable

monitoring and enforcement of the code of conduct.

In practice, many uncertified professionals remain

working in treasury units. Based on a report

received by Bank Indonesia in 2017, a total of 671

treasury dealers were not certified professionals,

compared to 707 certified treasury professionals,

with 87 inactive certified treasury professionals. This

demonstrates the importance of Bank Indonesia

requiring treasury dealers to become certified

professionals and for Bank Indonesia to enhance

competence on an ongoing basis. In addition,

financial institutions engaged in treasury activities

are also required to implement internal guidelines

that apply the code of conduct to treasury activities.

Promulgation of Regulations concerning

Treasury Certification and the Market Code of

Conduct

In 2016, Bank Indonesia issued Bank Indonesia

Regulation (PBI) No. 18/11/2016 concerning the

Money Market, which required money market

professionals to apply prudential principles,

encompassing a minimum of transaction ethics and

the market code of conduct (MCOC), and required

treasury dealers to be certified by an institution

approved by Bank Indonesia. Then in 2017, Bank

Indonesia issued Bank Indonesia Regulation (PBI)

No. 19/5/PBI/2017 concerning Treasury Certification

and Market Code of Conduct Implementation, as

well as Board of Governors Regulation No. 19/5/

PADG/2017 concerning the Implementation of

Treasury Certification and the Market Code of

Conduct.

The salient provisions of the regulations are as

follows:

1. Ruang lingkup dari sertifikasi tresuri dan

penerapan kode etik pasar, yaitu berlaku bagi

direksi dan pegawai dari pelaku pasar yang

menjalankan kegiatan usaha:

a. Bank,

b. Brokerage,

c. Securities companies and parent companies,


62 BANK INDONESIA

d. Other institutions stipulated by Bank

Indonesia engaged in treasury activities

in the money market, foreign exchange

market and derivatives market.

2. Implementation of the market code of conduct

for treasury activities, which refers to the code

of conduct published by the corresponding

professional association/financial services

industry association/industry committee

and regulated through mandatory internal

procedures.

3. The directors and professionals of market

entities engaged in banking activities and

brokerages are required to become a member

of a treasury professional association.

4. Directors and professionals are required to

become certified treasury professionals in

accordance with the appropriate classification

of Treasury Certification, namely Treasury

Professional Competence Certificates as well

as Regulation and Market Code of Conduct

Competence Certificates.

5. The effective period of treasury certificates may

be extended through additional competence

training.

6. Professional Certification Institutions are

recognised by Bank Indonesia as a Treasury

Certification Institution that administrate data

concerning treasury certificate holders.

7. Mandatory reporting of market entities and

certification institutions to Bank Indonesia.

8. Indirect supervision and inspections by Bank

Indonesia of market entities and professional

certification institutions in relation to the

market code of conduct and certification

implementation.

The requirements for treasury certification will

become effective in 2019 for traders and in 2020

for sales professionals and sharia-compliant treasury

professionals. The regulations are expected to

increase the credibility and enhance the competence

of financial market professionals in Indonesia in line

with technological innovation and rapid instrument

development.

707

87

671

Uncertified Treasury Professionals

Active Certified Treasury Professionals

Box Graph 2.2.1 Certified Treasury Professionals

Non-Active Certified Treasury Professionals





63BANK INDONESIA

The head of the engraved golek puppet is fixed with sampeurt (a rod affixed to the head) and tuding (sticks

connected to the hands) operated by the puppeteer. Concerning financial system stability, the rod and sticks

signify the household and corporate sectors. Stable household and corporate sectors are like the stable rod

and sticks, thus maintaining financial system stability and improving the economy.

05

INFRASTRUKTURSISTEM KEUANGAN

05

In the first semester of 2017, the household sector was relatively stable and the risks

contained in line with improving economic conditions. Despite the national economy

building momentum, households were still less inclined to consume, thereby reducing

the household consumption to GDP ratio. Nevertheless, households remained upbeat

concerning the economic outlook and growth of household consumer loans accelerated,

while the Real Sales Index (RSI) and Consumer Confidence Index (CCI) increased

respectively. Consequently, the banking industry expected growing household optimism

to drive deposit and credit growth, while simultaneously maintaining loan quality in the

household sector.

Corporate sector performance has shown early indications of improvement but remains

constrained by externalities and internal developments. The tepid global economic

recovery has failed to stimulate demand but the prices of export commodities from

Indonesia have improved, which elevated the value of exports. Meanwhile, lacklustre

domestic economic performance was evidenced by slower growth of real consumption

despite seasonal momentum due to the holy fasting month of Ramadan and Eid-ul-

Fitr. Non-financial public corporations have posted gains in terms of profitability as net

profits soared on the back of efficiency improvements. Of concern, however, is the

growing share of external debt in the corporate sector, which has undermined corporate

repayment capacity. Fortunately, the dent in corporate repayment capacity has had no

significant impact on corporate credit risk, which remains below the threshold.

HOUSEHOLDS AND CORPORATIONS

03

66 BANK INDONESIA


Household performance was relatively stable and the corresponding risks contained

Non-Financial Corporate Sector posted Limited Gains

HOUSEHOLDS REMAIN STABLE,WHILE THE CORPORATE SECTOR POSTED LIMITED GAINS

Share of household consumption down to64.73%

ROA down to5.18%

ROE up to 10.65%

8.61%

14.63%

Share of household consumption up to 84.97%

Current Ratio down to1.38

TA/TL down to1.94

1.81%

5.91%

7.11%

DSR up to72.49%

DER up to106%

3.48%

Robust Household Consumption

Profitability

Growth of Household Loans up to

Deposit Growth down to

Household Ability to Save Declined

Liquidity and Profitability

Household NPL up to

Credit Growth down to

Growth of Household Deposits down to

Repayment Capacity

Gross NPL downto

67BANK INDONESIA

3.1.1. Sources of Vulnerability and Household

Sector Dynamics

National economic growth in Indonesia accelerated

from 4.94% in the second semester of 2016 to

5.01% in the first semester of 2017. Nevertheless,

households have not increased their consumption

commensurately. Growth of household

consumption stood at 4.95% in the reporting

period, which was below economic growth and

household consumption in the previous period at

4.99%. Consequently, the portion of household

consumption to GDP declined from 54.80% to

53.64% (Graph 3.1).

Despite less propensity to consume, households

were more upbeat on economic conditions, with

both the Real Sales Index (RSI) and Consumer

Confidence Index (CCI) increasing respectively. The

Retail Sales Survey conducted by Bank Indonesia at

the end of the second semester of 2016 confirmed

an RSI of 218.0, which increased in the subsequent

3.1. Household Sector

period to 232.4. In terms of growth, however, the

index decelerated from 10.5% to 6.3% over the

same period (Graph 3.2).

The Consumer Confidence Index (CCI) , which

describes consumers’ confidence in economic

conditions, increased from 115.4 in the second

semester of 2016 to 122.4 in the first semester of

2017. The CCI was edged up by both component

indexes, namely the Current Economic Condition

Index (CECI) and the Consumer Expectation Index

(CEI). The CECI describes consumer perception of

prevailing economic dynamics, which increased

from 102.9 to 113.7 (Graph 3.3), driven by current

incomes, job availability and conditions for buying

durable goods. Likewise, the CEI, which measures

consumer expectations of economic dynamics in

the next six months, also posted gains on expected

job availability and expected business conditions in

the next six months.

Concerning the upcoming three months,

households expected milder inflationary pressures,

primarily due to clothing and foodstuffs (Graph 3.4).

Proportion of Household Consumption to GDP

105%

45%

75%

15%

90%

30%

60%

0%I I III

2013 2017

II IIIII IV

6.0%

5.6%

5.2%

4.8%

4.4%

4.0%

Proportion of Non-Household Consumption to GDP

GDP Growth (rhs)Household Consumption Growth (rhs)

I I

20152014 2016

II IIIII III IIIIV IV IV

Graph 3.1 Contribution of Household Consumption to GDP

Source: BPS-Statistics Indonesia, 2017

1 The Real Sales Index (RSI) is used to gauge sources of demand-side inflationary pressures and reveal general retail sales and household consumption trends. The Survey is available from the

official Bank Indonesia website.2 The Consumer Confidence Index (CCI) is a simple average of the Current Economic Condition Index (CECI) and Consumer Expectation Index (CEI). The Survey is available from the official Bank

Indonesia website.

(yoy)Share (%)

5.01%

4.95%





68 BANK INDONESIA


For the next six months, however, Consumer Survey

respondents predicted a build-up of inflationary

pressures in line with the seasonal spike in demand

for goods and services during the Christmas and

New Year holidays (Graph 3.5).

3.1.2. Household Financial Conditions

The domestic economic improvements achieved

in the first half of 2017 have not significantly fed

through to the household sector, as corroborated

by the June 2017 edition of the Consumer Survey.

Household propensity to consume declined on

conditions in December 2016, falling from 70.44%

to 64.73% and from 70.63% in June 2016 (Graph

3.6). Meanwhile, households were more inclined

to repay loans and save, with the respective index

increasing from 15.47% and 19.81% in June 2016

to 12.33% and 19.81% in December 2016 (Graph

3.6). Less household consumption, coupled with

more loan repayments, exacerbated vulnerabilities

in the household sector.

Greater household spending on loan repayments

was reflected, amongst others, by an increase in

the number of households with a debt service ratio

(DSR) in the 20-30% range, namely from 12.62%

of total respondents in the second semester of

2016 to 20.01% in the first semester of 2017.

40

(%)

0

2020.6

4.0

1.5 -0.7

3.76.5

3.8

8.5

-9.4

22.3

8.5

13.616.3

6.34.3

6.3

-3.0

-20

Notes: *) Preliminary data

Monthly RSI Growth (mtm) Annual RSI Growth (yoy) Holy Fasting Month

30

-10

1 1 15 5 59 93 3 37 7 7*2 2 26 6 610 10

2015 2016 2017

11 1112 124 4 48 8

10

Graph 3.2 Real Sales Growth

Source: Retail Sales Survey, Bank Indonesia, June 2017

Graph 3.3 Consumer Confidence Index (CCI), Current Economic Condition Index (CECI), and Consumer Expectation Index (CEI)

Consumer Confidence Index (CCI)Current Economic Condition Index (CECI)

Consumer Expectation Index (CEI)

140.0

130.0

120.0

110.0

100.0

90.0

80.0

70.0

Quarterly Consumer Confidence Index (CCI)

Lower fuel prices

Lower prices of fuels, gasand electricity

110.8 111.6

4 5

(Index)

6 7 8 9 10 11 12 1 12 23 34 45 56 67 8 9 10 11 12

2015 2016 2017

Opti

misti

cO

ptim

istic

118.0124.0

125.9

122.4

Source: Consumer Survey (18 Cities), Bank Indonesia, June 2017

69BANK INDONESIA





The increase affected nearly all household groups,

except the middle-income earners and higher (Table

3.1).

On the other hand, the percentage of households

able to save more than 30% of their income

increased from 13.29% to 16.42%, while the

portion of households unable to save declined from

21.08% to 15.03% (Table 3.2).

3.1.3. Household Deposits in the Banking

Industry3

Household deposit growth moderated at the beginning

of 2017, declining to 7.11% (yoy) by the end of the first

semester from 7.18% (yoy) in the first semester of 2016

and from 8.92% (yoy) in the second semester of 2016.

Furthermore, household deposit growth was lower than

total deposit growth as reported by the banking industry

at 10.30% as well as non-household deposit growth

at 14.13% (Graph 3.7a). Slower growth of household

deposits was in line with the nominal growth of deposits

valued at ≤ Rp2 billion, which decelerated from 10.47%

in June 2016 to 6.59% in December 2016 and 6.01%

in June 2017 despite an increase recorded in the total

number of accounts (Graph 3.7b). Notwithstanding

the decline, household deposits continued to dominate

banking industry deposits, accounting for 53.07%,

down from 55.81% in the second semester of 2016.

By component, slower household deposit growth

primarily stemmed from demand deposits and

savings deposits, moderating from 23.10% and

10.79% to 10.62% and 7.56% respectively in the

first semester of 2017. Bucking the downward

(Index, weighted average of 18 cities)

3-Month Price Expectations Index (PEI) (rhs)Eid-ul-FitrQuarterly Inflation – BPS (rhs)

8.0

6.0

4.0

2.0

0.0

-2.0

-4.0140

150

160

170

180

190

200%

163.9

177.0

1 1 12 2 23 3 34 4 45 5 5 56 6 6 67 7 7 78 8 8 89 9 9 910 10 1011 11 1112 12 12

2014

2014

2015

2015

2016

2016

2017

2017

Graph 3.4 Three-Month Price Expectations Index (PEI)

Graph 3.5 Six-Month Price Expectations Index (PEI)

6-Month Price Expectations Index (PEI) (rhs)Eid-ul-FitrSemesterly Inflation – BPS (rhs)

167.5

166.5

150

160

170

180

190

200

(Index, weighted average of 18 cities)

12 12 12 1211 11 11 111 12 23 34 45 5 56 6 67 7 7 78 8 8 89 9 9 910 10 10 101 2 3 4 5 6

(%)

8.0

6.0

4.0

2.0

0.0

Source: Consumer Survey (18 Cities), Bank Indonesia, June 2017

3 Household deposits are calculated as a proxy of individual deposits.

70 BANK INDONESIA


Table 3.1 DSR Composition by Monthly Income

Semester II 2016

Income TotalDSR

0-10% 10%-20% 20%-30% >30%

Rp 1.40 - 2.79 million 8.78% 4.51% 1.71% 1.33% 1.23%

Rp 2.88 - 4.11 million 25.45% 16.25% 4.27% 2.89% 2.04%

Rp 4.50- 5.80 million 34.14% 21.57% 6.02% 3.90% 2.64%

Rp 6.20 - 7.61 million 21.57% 12.11% 4.51% 2.95% 2.01%

> Rp 7.61 million 10.06% 5.34% 2.11% 1.56% 1.05%

Total 100.00% 59.78% 18.63% 12.62% 8.97%

Semester I 2017

Income TotalDSR

0-10% 10%-20% 20%-30% >30%

Rp 1.50 - 3.00 million 25.42% 14.59% 4.27% 4.89% 1.66%

Rp 3.20 - 4.53 million 30.55% 16.45% 5.91% 5.62% 2.56%

Rp 4.77 - 6.15 million 21.33% 10.84% 4.42% 4.36% 1.69%

Rp 6.42 - 7.82 million 9.18% 3.94% 2.52% 1.87% 0.84%

> Rp 8.10 million 13.53% 5.80% 3.04% 3.25% 1.42%

Total 100.00% 51.63% 20.17% 20.01% 8.19%

Source: Consumer Survey (30 Cities), Bank Indonesia, December 2016 and June 2017, processed

Source: Consumer Survey (30 Cities), Bank Indonesia, June 2017, processed

Table 3.2 Composition of Savings by Monthly Income

Semester II 2016

Income TotalSaving

0-10% 10%-20% 20%-30% >30% Unable to Save

Rp 1.40 - 2.79 million 8.78% 3.01% 1.84% 1.17% 1.50% 1.27%

Rp 2.88 - 4.11 million 25.45% 6.36% 5.71% 3.49% 3.47% 6.42%

Rp 4.50- 5.80 million 34.14% 9.55% 8.41% 4.43% 3.78% 7.96%

Rp 6.20 - 7.61 million 21.57% 5.63% 5.74% 3.13% 2.98% 4.09%

> Rp 7.61 million 10.06% 2.85% 2.64% 1.67% 1.56% 1.34%

Total 100.00% 27.41% 24.34% 13.89% 13.29% 21.08%

Source: Consumer Survey (30 Cities), Bank Indonesia, December 2016 and June 2017, processed

Semester I 2017

Income TotalSaving

0-10% 10%-20% 20%-30% >30% Unable to Save

Rp 1.50 - 3.00 million 25.42% 5.67% 5.70% 5.07% 4.66% 4.32%

Rp 3.20 - 4.53 million 30.55% 7.00% 7.63% 5.98% 4.74% 5.19%

Rp 4.77- 6.15 million 21.33% 5.58% 5.47% 4.08% 3.40% 2.79%

Rp 6.42 - 7.82 million 9.18% 2.77% 2.46% 1.42% 1.32% 1.20%

> Rp 8.10 million 13.53% 3.99% 3.58% 2.13% 2.29% 1.53%

Total 100.00% 25.01% 24.85% 18.69% 16.42% 15.03%

June 2016

11,61%

17.76%

70.63%

11.61%

December 2016

Consumption Loan Repayments Savings

17.23%

70.44%

12.33%

June 2017

19.81%

64.73%

15.47%

Graph 3.6 Allocation of Household Spending

71BANK INDONESIA





trend, however, growth of term deposits accelerated

in the reporting period from 4.63% to 6.10% (yoy).

Nonetheless, the share of savings deposits to total

deposits remained dominant despite reducing

slightly from 53.17% to 53.14% (Graph 3.8).

3.1.4. Bank Loans Disbursed to the

Household Sector4

After moderating, the banking industry was more

inclined to lend to the household sector in the first

half of 2017, with growth accelerating from 8.32%

(yoy) in the second semester of 2016 to 8.61%

(yoy), thus exceeding total credit growth at 7.75%

(yoy). The share of household loans to total bank

credit was recorded at 44.84% in the first semester

of 2017, up slightly from 44.18% in the previous

semester (Graph 3.9). Most loans disbursed by the

100%Share (%)

HouseholdHousehold

Non-HouseholdNon-Household

80%

30%

50%

0%sem I 2014 sem I 2015 sem I 2016 sem I 2017sem II 2014 sem II 2015 sem II 2016

90%

60%

10%54.53 56.64 54.00 56.16 54.65 55.81 53.07

45.47 43.36 46.00 43.84 45.35 44.19 46.9370%

20%

40%

Graph 3.7a Composition and Growth of Deposits

20yoy (%)

15 14.51 13.06

11.56

6.357.18

8.927.11

13.6312.29 12.65

7.265.90

9.60 10.3012.61

11.3113.97

8.45

4.40

10.4714.13

5

10

-sem I

2014

Total

20162015 2017

sem I sem I sem Isem II sem II sem II

100%Share (%)

80%

50%

10%

90%

60%

20%

70%

30%40%

Savings Term Deposits Demand Deposits

sem I 2014 sem I 2016sem I 2015 sem I 2017sem II 2014 sem II 2016sem II 2015

RT RT RTRT RTRT RTNon-RT Non-RT Non-RTNon-RT Non-RTNon-RT Non-RT

52.55

3.91

41.24

6.21

44.86

5.94

42.10

6.27

45.82

41.94

52.27

5.78

43.6441.77

52.92

5.32

45.28

6.54

44.35

5.49

41.37

53.14

44.16

50.28

5.56

40.29

50.21

53.1750.09

4.63 5.45

51.17

5.19

50.28

3.90

44.76

48.9753.15

4.74

42.57

51.4851.23

banking industry to the household sector were used

for consumptive purposes (62.11%), followed by

working capital (27.36%) and investment (10.53%)

(Table 3.3).

Household loans used for consumptive purposes

(hereinafter referred to as household consumer loans)

accelerated from 6.99% in the second semester of

2016 to 9.56% (yoy) in the first semester of 2017,

driven predominantly by automotive loans, which

reversed the previous contraction of -2.01% posted

in the second semester of 2016 to record positive

growth of 4.32% in the first semester of 2017, as

well as multipurpose loans, increasing from 8.24%

to 10.23%. Despite the gains posted by automotive

loans and multipurpose loans, housing loans slowed

from 7.67% to 7.51% in the reporting period.

Source: Commercial Bank Reports, Bank Indonesia, June 2017, processed

4 In this section, household sector loans refer to individual productive and consumptive loans

72 BANK INDONESIA


100

Share(%)

90

60

30

80

50

20

70

40

10

sem I sem Isem I sem I sem Isem II

2013 2014 2015 2016 2017

sem IIsem II sem II0

6.79 6.43 6.21 5.94 6.27 5.78 5.32 6.54 5.49

38.46 38.62 41.24 42.57 44.76 41.94 41.77 40.29 41.37

54.75 54.95 52.55 51.48 48.97 52.27 52.92 53.17 53.14

Savings Term Deposits Demand Deposits

30 yoy (%)

20

10

0

25

15

5

-5

-10 sem I13

Savings Term Deposits Demand Deposits Total

sem I 15

sem I 14

sem I 16

sem II 13

sem II 15

sem II 14

sem II 16

sem I 17

10.627.567.116.10

Graph 3.8 Composition and Growth of Household Deposits

Graph 3.7b Value and Total of Deposit Accounts

100%Share (%) yoy (%)

80%

30%

50%

0%

sem I 2014 sem I 2015 sem I 2016 sem I 2017sem II 2014 sem II 2015 sem II 2016

90%

60%

10%

55.06% 55.02%

55.12%

56.00%

44.94% 44.98% 44.88% 44.00%

55.51% 55.82% 55.16%

44.18% 44.84%44.49%

7.92% 8.32% 8.61%

70%

20%

40%

14%

6%

10%

2%

12%

4%

8%

0%

Households Non-Households Household Sector Credit Growth (rhs)

Graph 3.9 Composition of Bank Loans

16

14

8

2

12

6

0

10

4

Juni’16 Juni’16

Rp≤2 billion Rp≤2 billionRp≥2 billion Rp≥2 billionTotal Total

Des’16 Des’16Juni’17 Juni’17

Nominal Growth (%) Growth of Deposit Accounts (%)

16

20(%)

(%)

14

18

8

2

12

6

0

10

4


Source: Distribution of Commercial Bank Deposits, Deposit Insurance Corporation (LPS), June 2017


73BANK INDONESIA





Table 3.3 Household Sector Credit by Loan Type



Source: Consumer Survey, Bank Indonesia, June 2017, processed

Loan

Jun-16 Des-16 Jun-17

Credit (Rp. T)

Share (%)

NPL (%)

Credit (Rp. T)

Share (%)

NPL (%)

Credit (Rp. T)

Share (%)

NPL (%)

1. Working Capital 512.87 27.66 4.21 526.43 27.22 3.54 551.01 27.36 4.06

2. Investment 211.13 11.39 5.01 217.24 11.23 4.21 212.15 10.53 4.33

3. Consumption 1,130.28 60.95 1.68 1,190.27 61.55 1.53 1,250.76 62.11 1.73

TOTAL 1,854.28 100.00 2.76 1,933.93 100.00 2.38 2,013.92 100.00 2.64

40

yoy (%)

20

0

30

10

-10

35

15

-5

25

5

-15

AutomotiveHousing TotalMultipurpose

Sep-

12

Sep-

13

Sep-

14

Sep-

15

Sep-

16

Dec-

12

Dec-

13

Dec-

14

Dec-

15

Dec-

16

Mar

-13

Mar

-14

Mar

-15

Mar

-16

Mar

-17

Jun-

13

Jun-

14

Jun-

15

Jun-

16

Jun-

17

10.239.567.514.32

Graph 3.10 Household Consumer Loan Developments by Component

1200

800

400

Household Loans Household NPL (rhs)

NPL (%)Rp (T)

1000

600

200

0

Sep-

13

Sep-

14

Sep-

15

Sep-

16

Dec-

13

Dec-

14

Dec-

15

Dec-

16

Mar

-13

Mar

-14

Mar

-15

Mar

-16

Mar

-17

Jun-

13

Jun-

14

Jun-

15

Jun-

16

Jun-

17

4.00

2.001,81

1.0053.00

1.00

3.50

1.50

2.50

0.500.00

Graph 3.11 Value and NPL of Household Consumer Loans

3.5NPL (%)

2.94

1.811.370.98

2.5

1.5

3.0

2.0

1.00.5

-

Sep-

13

Sep-

12

Sep-

14

Sep-

15

Sep-

16

Dec-

13

Dec-

12

Dec-

14

Dec-

15

Dec-

16

Mar

-13

Mar

-12

Mar

-14

Mar

-15

Mar

-16

Mar

-17

Jun-

13

Jun-

12

Jun-

14

Jun-

15

Jun-

16

Jun-

17

AutomotiveHousing TotalMultipurpose

Graph 3.12 Household Consumer NPL by Component

Graph 3.13 Household Consumer Loan Composition by Loan Type

Jun2017

Housing

Automotive

Household Equipment

Multipurpose

Other Loans

Jun2016

5.75%

4.74%

40.22%42.21%

42.47%

0.37%

12.46%

0.45% 11.87%

39.47%

74 BANK INDONESIA


3.2.1. Sources of Vulnerability in the

Corporate Sector

Internal and external developments influenced

corporate sector performance during the first half of

2017. Internally, corporate sector performance was

affected by suboptimal national economic growth in

the second quarter of 2017, subdued by slower growth

of real consumption as corporations were less inclined

to spend despite the momentum garnered from

Ramadan and Eid-ul-Fitr. The main external factors,

however, included global economic uncertainty, which

undermined the capacity of promising domestic

macroeconomic conditions to stimulate the real

sector, although the economies of the United States

and China, as major trading partners of Indonesia,

3.2. Corporate Sector

160

80

120

40

Coal Crude Oil Gas (rhs)

140

60

100

20

52.41 USD/short ton

44.30USD/bbl

7.94USD/

mmbtu

USD USD25

15

5

20

10

0

Jan-

07Ju

n-07

Nov

-07

Apr-0

8

Sep-

08

Feb-

09Ju

l-09

Dec-

09M

ay-1

0O

ct-1

0M

ar-1

1

Aug-

11

Jan-

12Ju

n-12

Nov

-12

Apr-1

3

Sep-

13Fe

b-14

Jul-1

4De

c-14

May

-15

Oct

-15

Mar

-16

Aug-

16

Jan-

17

Jun-

17

Graph 3.14 Commodity Prices

7.0

3.0

5.0

1.0

USD/kg

6.0

2.0

4.0

0.0

Rubber

2.00 USD/kg

625.93USD/metric ton

Crude Palm Oil (rhs)

1,400

600

1,000

200

1,200

400

800

0

Jan-

07Ju

n-07

Nov

-07

Apr-0

8

Sep-

08

Feb-

09Ju

l-09

Dec-

09M

ay-1

0O

ct-1

0M

ar-1

1

Aug-

11

Jan-

12Ju

n-12

Nov

-12

Apr-1

3

Sep-

13Fe

b-14

Jul-1

4De

c-14

May

-15

Oct

-15

Mar

-16

Aug-

16

Jan-

17

Jun-

17

USD/metric ton

12,000USD/metric ton

8,000

10,000

6,000

4,000

2,000

0

USD/metric ton35,000

25,000

30,000

20,000

10,000

0

15,000

5,000

19521.50USD/metric ton

5,740.52 USD/metric ton

1,624.33 USD/metric ton

Jan-

07

Jun-

07N

ov-0

7

Apr-0

8

Sep-

08

Feb-

09

Jul-0

9

Dec-

09

May

-10

Oct

-10

Mar

-11

Aug-

11

Jan-

12

Jun-

12

Nov

-12

Apr-1

3

Sep-

13

Feb-

14

Jul-1

4

Dec-

14

May

-15

Oct

-15

Mar

-16

Aug-

16

Jan-

17

Jun-

17

Copper Alumunium Lead (rhs)

tended to beat economic expectations. Furthermore,

lower commodity prices in the first semester of 2017

also eroded corporate performance.

The prices of several leading international

commodities, including oil and gas as well as non-oil

and gas commodities, tended to slide in the first half

of the year (Graph 3.14). Lower prices affected crude

oil, crude palm oil (CPO), rubber and gas as well as

metals such as nickel and lead. The global price of

crude oil continued to tumble despite OPEC’s pact

to cut production. Meanwhile, an abundant supply

of natural rubber, especially from China , prompted

lower rubber prices. In contrast, the prices of coal,

copper and aluminium increased on their respective

positions in December 2016. The coal price

strengthened on rising demand from China and the

United States as winter approached.

5 Tempo daily newspaper, 8th June 2017 (https://bisnis.tempo.co/read/882685/harga-karet-alami-penurunan-terpanjang-sejak-1975#xwoJMZda3kIH10iW.99)

Source: Bloomberg, IMF, processed

75BANK INDONESIA





6 Bisnis Indonesia, 17th July 2017, (http://market.bisnis.com/read/20170717/94/672217/semester-i2017-produksi-batu-bara-china-naik-5)

Accumulatively, exports increased on the previous

period and the same period one year earlier (Graph

3.15). Furthermore, the value of exports outstripped

the value of imports in the reporting period, with

the non-oil and gas sector cited as the main driver

of export value, especially the manufacturing

industry.

3.2.2. Corporate Performance

Corporate performance was influenced by business

sustainability and the scale of business activities.

According to the Business Survey conducted by Bank

Indonesia at the end of the first semester of 2017,

business activity expanded on conditions in the

second semester of 2016, with the corresponding

weighted net balance (WNB) increasing significantly

from 3.13% to 17.36% (Graph 3.16).

Businesses in nearly all economic sectors expanded

in the first half of 2017, particularly the trade,

hotels and restaurants (THR) sector as well as the

manufacturing industry, due to seasonal factors

that raised demand in the domestic market.

Nevertheless, the survey respondents predicted

business activity to moderate in the third quarter

of 2017, with the WNB dropping to 14.93%.

Corporate moderation was expected to originate

from the mining and quarrying sector, with a WNB

contraction of -3.15% reported. Furthermore, most

other sectors were also expected to experience a

downturn as the cyclical factors of Ramadan and

Eid-ul-Fitr faded, including the transportation and

communication sector as well as the hotels and

restaurants sector.

In relation to robust business growth, utilised

production capacity averaged 77.06% in the first

semester of 2017, up from 76.28% in the second

semester of 2016. Average utilised production

capacity in the first half of 2017 also exceeded that

recorded in the same period in 2013, at 72.62%,

and 2014, at 76.97%. The utilities sector (electricity,

gas and water supply) posted the highest level of

utilised production capacity in the reporting period

at 80.53%, contrasting the lowest of 75.04%

recorded in the mining and quarrying sector.

Graph 3.15 Indonesia’s Exports and Imports

45

13

55 15

40

12

5014

35

11

30

10

9

8

Exports ImportsRupiah Exchange Rate (rhs)

Mar

-12

Jun-

12

Sep-

12

Dec-

12

Mar

-13

Jun-

13

Sep-

13

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

Source: Bank Indonesia, processed

USD billion Rp Thousand

13,35

39,16

34,37

76 BANK INDONESIA


Graph 3.16 Predicted and Actual Business Expansion

5.0(%qtq) (%SBT)

1.0

3.0

-1.0

4.0

0.0

2.0

-2.0

-3.0

25.0

15.0

5.0

20.0

14.93

4.803.13

-0.34

-1.77

17.36

10.0

0.0I I I III II II IIIII III III III*

2015

GDP Growth (lhs)*Forecast

WNB Value (rhs)

2014 2016 2017

IV IV IV

Graph 3.17 Utilised Production Capacity

85(%)

75

65

80

70

60I I III II IIIII

2015

Total

Mining and Quarrying

Electricity, Gas and Water Supply (Utilities Sector)

Agriculture, Livestock, Forestry and Fisheries

Manufacturing Industry

2016 2017IIIIV IV

80.53

75.65

77.0

6

76.9

2

75.04

77.01

Table 3.4 Financial Performance Indicators of Non-Financial Corporations

Source: Corporate Financial Reports from the Indonesia Stock Exchange, Bloomberg, processedNote: Data as of Q2/217 and Q2/2017 (sample size of 325 non-financial corporations).

No, SectorROA ROE DER Current Ratio TA/TL Asset TO Inventory TO

2016 2017 2016 2017 2016 2017 2016 2017 2016 2017 2016 2017 2016 2017

1 Agriculture 2.73% 4.61% 5.71% 9.29% 1.06 0.97 1.18 1.22 1.94 2.03 0.58 0.63 7.34 7.58

2 Basic Industry and Chemicals 3.65% 3.20% 7.67% 6.49% 1.03 1.02 1.41 1.49 1.97 1.98 0.67 0.64 4.74 4.57

3 Consumer Goods 13.11% 12.31% 24.53% 21.91% 0.79 0.77 1.84 1.78 2.27 2.30 1.31 1.29 4.91 5.07

4 Infrastructure, Utilities and Transportation 4.96% 4.19% 13.04% 10.25% 1.45 1.45 0.96 0.96 1.69 1.69 0.51 0.52 77.58 62.74

5 Miscellaneous Industries 4.07% 4.75% 8.93% 10.35% 1.16 1.20 1.22 1.06 1.86 1.83 0.75 0.73 7.96 8.03

6 Mining 0.95% 4.97% 1.81% 9.20% 0.86 0.84 1.63 1.83 2.16 2.19 0.47 0.51 12.01 14.05

7 Property and Real Estate 5.49% 5.10% 10.90% 10.09% 0.95 1.00 1.68 1.62 2.05 2.00 0.34 0.33 2.15 2.12

8 Trade, Services and Investment 2.98% 4.02% 5.78% 7.95% 0.97 0.99 1.52 1.48 2.03 2.01 0.98 0.97 6.88 7.10

Agregat 4.77% 5.18% 10.08% 10.65% 1.05 1.06 1.41 1.38 1.95 1.94 0.70 0.69 6.47 6.46

Graph 3.18 Key Performance Indicators

12.0

Current Ratio

Inventory Turnover RAO

ROE

2016Q2

2016Q4

2017Q2

TA/TL

10.0

8.0

6.0

4.0

2.0

0.0

Source: Business Survey, Bank Indonesia, Semester-I 2017

Source: Corporate Financial Reports from the Indonesia Stock Exchange, Bloomberg, processedNote: A larger ratio, implying a larger area, indicates comparatively better performance.

77BANK INDONESIA





Congruent with business expansion, the aggregate

performance of public non-financial corporations

began to see limited improvements in the second

quarter of 2017, with corporate profitability

increasing but so too the share of debt, while

productivity declined. ROA and ROE increased in

the second quarter of 2017 compared to conditions

one year earlier, climbing from 4.77% and 10.08%

to 5.18% and 10.65% respectively. The profitability

gains stemmed primarily from higher net profits as

the corporate sector sought to enhance efficiency. In

contrast, corporate productivity declined slightly, as

evidenced by the moderate dip in inventory turnover

from 6.47 in June 2016 to 6.46 in June 2017 and the

decrease in asset turnover to a level of 0.69 (Table

3.4). The lower inventory turnover indicator was

due to corporations operating in the infrastructure,

utilities and transportation sectors, while five other

major sectors posted gains. Furthermore, nearly

all corporate sectors experienced a decline in asset

turnover.

On the other hand, the debt-to-equity ratio (DER)

increased slightly from 1.05 (Q2/2016) to 1.06

(Q1/2017), implying a decline in short-term and

long-term corporate repayment capacity. The

current ratio fell from 1.41 to 1.38, while total assets

to total liabilities narrowed from 1.95 (Q2/2016)

to 1.94 (Q2/2017). The property and real estate

sector posted the largest increase in the debt-to-

equity ratio (DER), consistent with the proliferation

of private sector construction developments and

government infrastructure projects.

Corporate repayment capacity was somewhat

restrained in first semester of 2017, confirmed by

the debt service ratio (DSR). The latest public data

pointed to a short-term debt service ratio (DSR) in

June 2017 of 72.49% (median), up from 71.45%

in June 2016. Despite the rising DSR, the share

of corporations with a DSR > 100% and negative

DSR decreased, namely from 57.39% to 55.99%.

Corporate interest repayment capacity improved,

with the interest coverage ratio (ICR) increasing

from 2.50 in the second quarter of 2016 to 2.84 in

the second quarter of 2017, in line with the share

of corporations with an ICR value < 1.5, indicating a

smaller proportion of corporations with debt at risk.

In general, the performance of firms operating in the

major commodity sectors, such as coal, crude palm

oil (CPO), rubber and metals, also improved through

corporate efforts to enhance efficiency coupled with

growing demand for such goods, as confirmed by

increases of profitability, productivity and repayment

capacity in the second quarter of 2017. Only firms

operating in the oil and gas sectors experienced

declines of ROA and ROE, triggered by global oil

price fluctuations despite OPEC’s efforts to reduce

production and global supply. In addition, the share

of corporate debt (DER) in the oil and gas sectors

increased, thus undermining repayment capacity,

which exacerbated vulnerabilities in the affected

sectors. Rising levels of debt demand vigilance

because declining profitability and productivity will

erode corporate repayment capacity (Table 3.5).

The potential risk of default in the corporate

sector eased on the same period one year earlier,

as reflected by the corresponding Altman Z-Score

using a data sample of the 308 largest non-financial

public companies covering all economic sectors. The

results showed that the percentage of distressed

corporations declined from 42.91% in the second

quarter of 2016 to 37.66% in the second quarter

of 2017 (Graph 3.22), following a trend that has

7 Debt at risk: Total corporate debt with an ICR < 1.5 / Total corporate debt.

78 BANK INDONESIA


Graph 3.19 Financial Performance of Public Non-Financial Corporations

12%

8%

10%

6%

4%

2%

0%

25%ROA ROE (rhs)

15%

5%

20%

10%

0%

Mar

-11

Mar

-14

Mar

-17

Sep-

13

Sep-

16

Sep-

12

Sep-

15

Mar

-12

Mar

-15

Dec-

11

Dec-

14

Jun-

11

Jun-

14

Jun-

17

Jun-

13

Jun-

16

Dec-

12

Dec-

15

1.0 Asset Turnover Inventory Turnover (rhs)

0.7

0.9

0.6

0.8

0.5

1.0

0.7

0.9

0.6

0.8

9.0

7.0

8.0

6.0

8.5

6.5

7.5

5.5

5.0

Mar

-11

Mar

-14

Mar

-17

Sep-

13

Sep-

16

Sep-

12

Sep-

15

Mar

-12

Mar

-15

Dec-

11

Dec-

14

Jun-

11

Jun-

14

Jun-

17

Jun-

13

Jun-

16

Dec-

12

Dec-

15

DER Current Ratio TA/TL (rhs)1.8

1.4

1.0

1.6

1.2

0.8

Mar

-11

Mar

-11

Mar

-11

Mar

-12

Mar

-12

Mar

-12

Mar

-13

Mar

-13

Mar

-13

Mar

-14

Mar

-14

Mar

-14

Mar

-15

Mar

-15

Mar

-15

Mar

-16

Mar

-16

Mar

-16

Mar

-17

Mar

-17

Mar

-17

Jun-

17

Sep-

11

Sep-

11

Sep-

11

Sep-

12

Sep-

12

Sep-

12

Sep-

13

Sep-

13

Sep-

13

Sep-

14

Sep-

14

Sep-

14

Sep-

15

Sep-

15

Sep-

15

Sep-

16

Sep-

16

Sep-

16

2.2

2.0

2.1

1.9

1.8

1.7

Graph 3.20 Non-Financial Corporate Repayment Capacity

10.0100%%

6.060

8.080

4.040

2.020

9.090

5.050

7.070

3.030

1.010

0.00,020112011 20132013 20122012 20142014 20152015 Mar-16Mar-16 Jun-16Jun-16 Sep-16Sep-16 Dec-16Dec-16 Mar-17Mar-17 Jun-17Jun-17

45

ICR (median)DSR (median) Debt at Risk (rhs)% of Corporations with ICR < 1.5 (rhs)

% of Corporations with DSR > 100 and Negative DSR (rhs)

25

50

35

70

15

30

40

20

40

30

60

1020

510

00

25.8138.68

23.58

5.1254.89 47.32 57.4567.52 68.24 67.77 71.45 73.49 67.40 71.58 72.49 5.73

3.90 3.482.69 2.47 2.50 2.60 2.60 2.86 2.84

24.08

42.86 31.81

24.52

45.34

39.6831.20

29.47

46.82

37.05

55.56

38.21

55.76

30.75

37.3857.39

32.9731.06

35.6856.1433.0256.29

25.57 24.87

33.7955.7533.18

55.59

23.90

33.51

Table 3.5 Financial Performance Indicators of Major Commodity-Based Corporations


SectorROA ROE DER Current Ratio TA/TL Asset TO Inventory TO

2016 2017 2016 2017 2016 2017 2016 2017 2016 2017 2016 2017 2016 2017

Coal 2.48% 9.79% 4.73% 17.72% 0.87 0.76 1.99 2.16 2.15 2.32 0.63 0.71 18.21 23.95

Crude Palm Oil (CPO) 2.05% 3.57% 4.60% 7.76% 1.21 1.14 0.89 0.89 1.82 1.88 0.52 0.58 7.61 7.91

Rubber 0.48% 1.86% 1.02% 4.03% 1.14 1.20 0.57 0.61 1.88 1.84 0.33 0.39 7.46 9.09

Oil and Gas -4.80% -8.27% -16.18% -33.39% 2.66 3.55 0.58 0.65 1.38 1.28 0.26 0.21 12.08 10.58

Metals -3.75% -1.61% -7.04% -2.92% 0.78 0.84 1.32 1.21 2.28 2.19 0.43 0.39 3.95 3.69



79BANK INDONESIA





2.5

1.5

0.5

2.0

1.0

0.0I II III IV

2012 2014 20162013 2015 2017

I II III IV I II III IV I II III IV I II III IV I II

Current Ratio40

20

30

10

35

15

25

5

0

I II III IV

2012 2014 20162013 2015 2017


Inventory Turnover

Graph 3.21 Financial Performance of Major Commodity-Based Corporations

20(%)

(%) (%)

(%)

10

15

5

0

-5

-10

-15I II III IV

2012 2014 20162013 2015 2017

ROA


4.5

2.5

3.5

1.5

0.5

4.0

2.0

3.0

1.0

0.0I II III IV

2012 2014 20162013 2015 2017


DER

Coal Crude Palm Oil (CPO) Rubber Oil and GasMetals

Source: Corporate Financial Reports from the Indonesia Stock Exchange, Bloomberg, processed

persisted since the first quarter of 2016. Furthermore,

the portion of distressed corporations was much

lower than during the 2008-2009 crisis period.

Meanwhile, the results of plotting the Altman

Z-Score against GDP showed that previous global

and domestic economic moderation has significantly

undermined corporate financial performance.

Notwithstanding the declines, corporate financial

performance began to rebound in the first half of

2017 in line with stronger economic growth, thus

reducing the share of distressed firms in Indonesia

(Graph 3.23) compared to conditions previously.

3.2.3. Bank Exposure to the Corporate Sector

Bank exposure to the corporate sector remained

dominant but eased as firms postponed business

expansion against the backdrop of an unstable

global economic recovery, particularly in Indonesia’s

leading trading partners, which spilled over to

influence the pace of domestic economic growth.

Less corporate expansion reduced demand for

new loans from the banking industry. In the first

semester of 2017, therefore, the portion of bank

loans extended to the corporate sector moderated

slightly from 48.43% to 47.57%. Most commercial

loans were disbursed by the dominant BUKU 4 and

BUKU 3 banks, accounting respectively for 50.85%

and 32.40% of the total, further corroborating

the orientation of such banks towards corporate

financing, while BUKU 2 and BUKU 1 banks tended

to focus on retail loans (Graph 3.24).

Growth of bank loans allocated to the corporate

sector slowed in the first semester of 2017, namely

80 BANK INDONESIA


Graph 3.24 Corporate Loans by BUKU Bank Group

100%Share % %

90%

60%

30%

80%

50%

20%

70%

40%

10%

0%

Mar

Mar

Mar

Mar

Mar

Mar

MarJun

2011

BUKU 1 BUKU 3 BUKU 4

Gross NPL (rhs)Credit Growth (yoy – rhs)

BUKU 2

2013 20152012 2014 2016 2017

Jun

Jun

Jun

Jun

Jun

Jun

Sep

Sep

Sep

Sep

Sep

Sep

Dec

Dec

Dec

Dec

Dec

Dec

35.0

35.0

35.0

35.05.93

3.48

30.0

30.0

30.0

30.0

Graph 3.22 Corporate Performance per the Altman Z-Score

55

Share % Share % PDB% (yoy)

35

43.8239.36 37.66

37.99

24.35

45

25

15

50

30

40

20

10

Mar

-07

Jun-

07

Sep-

07

Dec-

07

Mar

-08

Jun-

08

Sep-

08

Dec-

08

Mar

-09

Jun-

09

Sep-

09

Dec-

09

Mar

-10

Jun-

10

Sep-

10

Dec-

10

Mar

-11

Jun-

11

Sep-

11

Dec-

11

Mar

-12

Jun-

12

Sep-

12

Dec-

12

Mar

-13

Jun-

13

Sep-

13

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

Safe Zone Distress Zone Moderate Zone

Graph 3.23 Distressed Corporate Performance against GDP

35 5.5

5.01

37.66

45 6.5

25 4.5

50 7.0

30 5.0

40 6.0

20 4.0

Mar

-11

Jun-

11

Sep-

11

Dec-

11

Mar

-12

Jun-

12

Sep-

12

Dec-

12

Mar

-13

Jun-

13

Sep-

13

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

GDP (rhs) Share of Distressed Corporations

Source: Bloomberg, CEIC, June 2017, processed

from 9.40% (yoy) in the second semester of 2016

to 5.91% (yoy). The corporate credit slump was

more pronounced than the slowdown experienced

by loans extended to the manufacturing industry,

which decelerated from 7.86% to 7.75% over the

same period. The downswing was driven by the


sector, coupled with several other sectors (Table 3.6).

In addition, loans disbursed to the manufacturing

industry, as the dominant sector, accounting for

31.72% of the total, also declined. Conversely, the

mining sector and other sectors, which had posted

negative credit growth just last year, began to

show improvements in the first semester of 2017.

Considering that the dominant share of corporate

credit originates from the banking industry, slower

corporate credit growth will also affect the overall

achievement of the national credit growth target

for the banking industry in 2017.

As an aggregate, the quality of corporate loans has

tended to improve, as reflected by a decrease in the

gross NPL ratio from 3.62% in the second semester

of 2016 to 3.48% in the first semester of 2017.

The stronger NPL was primarily attributed to the


sector as well as the manufacturing industry.

Nevertheless, deteriorating NPL performance in

Source: Commercial Bank Reports, June 2017, processed

81BANK INDONESIA





Table 3.6 Corporate Loans by Economic Sector


No Economic Sector

Juni-16 Des-16 Jun-17

Outstanding Credit (Rp,

trillions)

Share (%)

Credit Growth yoy (%)

Gross NPL (%)


trillions)

Share (%)


Gross NPL (%)


trillions)

Share (%)


Gross NPL (%)

1 Manufacturing Industry 655.16 32.48 9.46 3.78 680.71 32.11 4.29 3.60 677.60 31.72 3.43 3.32

2 Trade, Hotels and Restaurants 430.01 21.32 13.14 3.61 447.05 21.09 8.53 4.47 448.50 20.99 4.30 4.30

3 Corporate Services 190.20 9.43 24.52 2.15 204.43 9.64 17.80 2.20 212.82 9.96 11.90 2.55

4 Agriculture 179.82 8.91 23.68 1.01 193.65 9.14 22.65 1.68 200.02 9.36 11.23 1.34

5 Construction 157.59 7.81 21.17 4.63 165.68 7.82 21.33 3.63 181.79 8.51 15.36 3.46

6 Transportation, Warehousing and Communications

151.52 7.51 1.52 5.60 143.69 6.78 (5.84) 5.07 146.52 6.86 (3.30) 4.38

7 Utilities (Electricity, Gas and Water Supply)

104.87 5.20 27.78 1.73 128.06 6.04 38.01 1.65 119.01 5.57 13.48 1.57

8 Mining 109.85 5.45 (14.92) 6.13 116.44 5.49 (5.29) 7.13 111.10 5.20 1.13 7.77

9 Social/Public Services 31.66 1.57 32.87 3.17 33.33 1.57 14.77 1.92 32.30 1.51 2.01 3.37

10 Other Sectors 6.52 0.32 (14.28) 4.99 6.63 0.31 (13.13) 0.61 6.75 0.32 3.47 1.20

Total 2,017.20 100.00 12.15 3.56 2,119.68 100.00 9.40 3.62 2,136.41 100.00 5.91 3.48

several other sectors requires close monitoring,

mainly the mining sector, which increased from

7.13% to 7.77% in the first semester of 2017 due

to lower and fluctuating mining commodity prices,

coupled with low demand for mining products,

which undermined performance in the sector.

Bank credit risk exposure to firms operating in

the five major export commodity sectors has

not improved, reflected by a deterioration in the

gross NPL ratio in line with subdued financial

performance in the affected sectors (Table 3.7).

Several commodities, particularly coal as well as

oil and gas, have a gross NPL ratio that is above

the 5% threshold, which has been accompanied

by declining credit growth. Nonetheless, credit

growth to the crude palm oil (CPO) and rubber

sectors has remained positive but the gross NPL

ratios of both sectors have failed to improve. The

rising NPL trend, as a proxy of credit risk, has

made the banks more selective when disbursing

loans to commodity-based sectors as part of the

ongoing consolidation process and also to avoid

spiralling NPL against a backdrop of price and

demand uncertainty surrounding international

commodities.

Table 3.7. Credit Based on Main Export Commodities


No Commodity

Outstanding Loans as of

June 2017 (Rp, trillions)

Share of Total Credit (%) Credit Growth yoy (%) Gross NPL Ratio (%)

Jun'16 Dec'16 Jun'17 Jun'16 Dec'16 Jun'17 Jun'16 Dec'16 Jun'17

1 Crude Palm Oil 275.53 5.84 6.12 6.13 20.82 13.11 13.23 1.10 1.40 1.42

2 Metal Products 105.71 2.20 2.34 2.35 10.14 15.21 15.13 2.38 2.58 3.69

3 Oil and Gas 85.83 2.25 2.25 1.91 (6.71) (8.05) (8.66) 5.93 6.04 7.59

4 Coal 36.71 1.00 0.91 0.82 (17.18) (14.38) (11.78) 8.31 10.30 11.63

5 Rubber 22.06 0.46 0.46 0.49 (2.10) 11.89 16.07 4.24 4.13 3.61

Total 525.83 11.75 12.08 11.71 7.60 6.31 7.37 3.00 3.27 3.69

82 BANK INDONESIA


Graph 3.25 Performance of Corporate Deposits

1,600

Corporate Third Party Funds (Rp T)

Corporate Deposits Corporate Deposit Growth (rhs)

yoy (%)

1,200

800

400

1,400

1,000

600

200

0

35

1,376

14.6315

25

5

30

10

20

-


Congruent with slower credit growth, bank deposits

originating from the corporate sector also moderated

in the first half of 2017, decelerating from 16.60%

(yoy) to 14.63% (yoy). A growing requirement in

the corporate sector to meet short-term obligations

has eroded corporate liquidity, as reflected by the

lower current ratio and higher debt service ratio (DSR)

compared to conditions in the previous period (Graph

3.19 and Graph 3.20).

At the end of the first semester of 2017, BUKU 4 and

BUKU 3 banks were the preferred destinations for

the corporate sector to place funds, commanding

shares of 44.37% and 37.71% of the total

respectively due to several factors, including the

transaction simplicity, security and convenience

offered by such large banks (Graph 3.26).

3.2.4. Private External Debt

External debt in Indonesia stood at USD335.29 billion

in June 2017, with a relatively balanced composition

between the public and private sectors (Graph 3.27).

Nevertheless, the growth of private external debt,

particularly in the financial sector, has tended to slow

since the end of 2014 due to economic moderation

and rupiah exchange rates. Rupiah volatility has the

potential to increase exposure to currency risk for

prospective borrowers, thus making the private sector

more reluctant to expand its external debt position.

Based on the components of private external debt,

as of June 2017, the external debt of nonbank

financial institutions contracted by -4.70% (yoy),

followed by banks (-2.28%, yoy) and non-financial

state-owned enterprises (-1.71%, yoy). Only non-

financial corporations had the appetite to increase

external debt, growing at 0.09% (Graph 3.28).

Declining external debt in the financial sector (banks

and the nonbank financial industry) was linked to

weak demand for loans/financing, primarily in a

foreign currency, therefore the financial institutions

(banks and nonbank financial industry) reduced

their offshore borrowings as a source of funds to

extend loans/financing. Meanwhile, the increase in

external debt at non-financial corporations was in

line with growing investment. The value of non-

financial corporate external debt in June 2017 had

reached USD126 billion (Graph 3.28). Despite the

increase, the total restructured value declined.

Restructured (restru) non-financial corporate

external debt can be grouped into two

83BANK INDONESIA





Graph 3.26 Corporate Deposits by BUKU Bank Group

Mar

-11

Jun-

11

Sep-

11

Dec-

11

Mar

-12

Jun-

12

Sep-

12

Dec-

12

Mar

-13

Jun-

13

Sep-

13

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

100%

Share (%)

90%

60%

30%

80%

50%

20%

70%

40%

10%

0%

BUKU 1 BUKU 2 BUKU 3 BUKU 4

44.37%

37.71%

15.56%

2.36%


characteristics, namely a positive tone or a negative

tone. Positive tone restructuring aims to improve

corporate business and performance, including: (i)

raising the ceiling; (ii) refinancing; (iii) rollover; and

(iv) creditor diversification. In contrast, negative

tone restructuring is undertaken due to declining

corporate performance, including repayment

constraints, a deteriorating business outlook or

inadequate liquidity. Negative tone restructuring

can be achieved through: (i) reconditioning; (ii)

capitalised interest; (iii) debt to equity swaps; (iv) debt

reduction; (v) rescheduling; and (vi) other external

debt restructuring. A negative tone restructuring

action could indicate a deterioration of corporate

performance that may affect repayment capacity on

the obligations to domestic or foreign banks.

The value of restructured external debt was

largest in the manufacturing industry at USD12.9

billion as of June 2017 (Table 3.8) due to the high

import content of raw materials that is typically

paid in USD, while the products are normally sold

on the domestic market in rupiah, thus creating

high currency mismatch risk.

Restructured external debt at non-financial

corporations has declined since January 2015

to USD30.66 billion as of June 2017 (869

corporations restructured external debt with a

negative tone). Consequently, restructuring has

become the rational choice to make principal

and interest payments on external debt more

efficient in line with domestic and global

economic moderation.

External debt restructuring by non-financial

corporations has tended to decline on the

position recorded in June 2016 for both negative

and positive tones. In terms of share, however,

as of June 2017 the share of negative tone

had increased and positive tone had decreased

compared to conditions in June 2016.

84 BANK INDONESIA


Graph 3.27 External Debt in Indonesia

100%Share (%)

90%

60%

30%

80%

50%

20%

70%

40%

10%

0%

3.47 1.97 2.19 2.45 1.95 3.64 3.48 5.45 5.86 7.82 8.53 7.95 7.22 7.17

37.57 38.42 40.65 40.45 42.21 38.93 37.91 41.91 44.16 45.75 47.24 46.16 42.84 42.04

58.96 59.61 57.17 57.10 55.84 57.42 58.60 52.64 49.97 46.43 44.23 45.89 49.94 50.79

2004 2009 20152006

Non-Financial State-Owned EnterpriseOther PrivateGovernment and Monetary Authority

2011 20172005 2010 20162007 20122008 20142013

Graph 3.28 Private External Debt Growth and Value

Dec-

05

Jun-

06

Dec-

06Ju

n-07

De

c-07

Jun-

08

Dec-

08Ju

n-09

De

c-09

Jun-

10De

c-10

Jun-

11

Dec-

11Ju

n-12

De

c-12

Jun-

13

Dec-

13Ju

n-14

Dec-

14Ju

n-15

De

c-15

Jun-

16De

c-16

Jun-

17

120% GrowthYoY (%)

40%

80%

0%

100%

20%

60%

-20%

-40%

-60%

Total Private External Debt

Nonbank Financial Institution

Nonbank Financial Institution

Non-Financial State-Owned Enterprise

Bank

Non-Financial Corporation

0.09%

-1.37%-1.71%-2.28%

-4.70%

BankNon-Financial State-Owned Enterprise

Total Private External Debt Non-Financial Corporation

35USD Billion USD Billion

15

25

5

30

10

20

-

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

20

Bank Nonbank Financial Institution Non-Financial State-Owned EnterprisePrivate (rhs)Corporate

-

80

40

100

120

140

160

180165

29

12624

10 60


Source: External Debt Statistics, Bank Indonesia, position as of June 2017, processed

8 Penentuan ULN restru dengan tone positif dan negatif merupakan hasil Focus Group Discussion (FGD) dengan korporasi yang memiliki ULN yang di resrukturisasi

Based on outstanding external debt at non-financial

corporations, negative tone restructuring was

dominated by reconditioning, with 476 facilities as

of June 2017. Reconditioning was achieved through

changes to the terms and conditions of the external

debt, including adjusting the total of the debt or

interest rate or through creditor diversification. In

several cases, reconditioning was undertaken if

new debt was offered with more attractive terms

and conditions, for instance a lower interest rate

or longer maturity period. Meanwhile, positive

tone restructuring was dominated by creditor

diversification, accounting for 118 facilities as of

June 2017 (Table 3.9).

As of June 2017, interest payments on positive and

negative tone restructured external debt declined

compared to conditions in the same period one

year earlier, falling to USD10.3 million and USD73.6

million respectively, which is consistent with the

decreasing principal payments on restructured

external debt, with positive tone declining to

USD0.92 billion and positive tone to USD0.04

billion (Graph 3.32).

To mitigate the risks, Bank Indonesia has issued

a regulation concerning the Application of

Prudential Principles in the Management of

Nonbank Corporate External Debt (PBI No.

16/21/PBI/2014). The regulation was issued to

encourage prudence at nonbank corporations

when managing the various risks associated

with external debt. Consequently, nonbank

corporations are required to satisfy a minimum

hedging ratio of 25% based on the negative

difference between foreign currency assets and

foreign currency liabilities that will mature within

three months as well as between three and six

85BANK INDONESIA





Graph 3.29 Restructured External Debt of Non-Financial Corporations

Jan-

14Fe

b-14

Mar

-14

Apr-1

4M

ay-1

4Ju

n-14

Jul-1

4Au

g-14

Sep-

14O

ct-1

4N

ov-1

4De

c-14

Jan-

15Fe

b-15

Mar

-15

Apr-1

5M

ay-1

5Ju

n-15

Jul-1

5Au

g-15

Sep-

15O

ct-1

5N

ov-1

5De

c-15

Jan-

16Fe

b-16

Mar

-16

Apr-1

6M

ay-1

6Ju

n-16

Jul-1

6Au

g-16

Sep-

16O

ct-1

6N

ov-1

6De

c-16

Jan-

17Fe

b-17

Mar

-17

Apr-1

7M

ay-1

7Ju

n-17

45.0

34,77

30,66

25.0

35.0

15.0

40.0

20.0

30.0

10.0

5.0

0.0

USD Billion


Table 3.8 Restructured External Debt by Economic Sector

No. Economic Sector

Non-Financial Corporate External Debt (USD, millions) *)

Non-Restructured

Restructured Total External

DebtPositive

ToneNegative

ToneTotal

Restructured

1. Manufacturing Industry 15,956 1,877 11,067 12,944 28,900

2. Utilities (Electricity, Gas and Water Supply) 18,809 104 2,578 2,682 21,491

3. Mining and Quarrying 16,991 212 4,131 4,344 21,335

4. Transportation and Communication 10,718 108 2,035 2,143 12,861

5. Trade, Hotels and Restaurants 5,196 623 1,316 1,939 7,135

6. Financial, Leasing and Corporate Services 4,535 514 1,874 2,388 6,923

7. Agriculture, Livestock, Forestry and Fisheries 3,366 559 2,138 2,697 6,063

8. Others Sector 998 13 672 684 1,683

9. Construction 740 206 170 376 1,115

10. Services 592 416 46 462 1,054

Total 77,901 4,632 26,027 30,659 108,559


months. In addition, nonbank corporations are

also required to fulfil a minimum foreign currency

liquidity ratio of 70%. Based on the Compliance

Report for Prudential Principles (KPPK), Bank

Indonesia calculates the foreign exchange liquidity

of all nonbank corporations holding external debt.

From the KPPK report, Bank Indonesia found that

of the 2,518 indebted nonbank corporations

reporting their foreign currency liquidity positions,

9.45% had failed to meet the liquidity or hedging

requirements for the upcoming three months and

6.67% had failed to meet the requirements for the

next 3-6 months. The data, therefore, indicates that

most indebted nonbank corporations have already

met the prudential principles to contain the risks

associated with external debt.

86 BANK INDONESIA


Graph 3.30 Outstanding Restructured External Debt (USD, millions)

Negative Tone

Positive Tone

40.0

USD Billion

30.0

20.0

26.85

7.92

10.0

10.0

6.0

2.0

8.0

4.0

0.0

Jan-

14

Feb-

14

Mar

-14

Apr-1

4

May

-14

Jun-

14

Jul-1

4

Aug-

14

Sep-

14

Oct

-14

Nov

-14

Dec-

14

Jan-

15

Feb-

15

Mar

-15

Apr-1

5

May

-15

Jun-

15

Jul-1

5

Aug-

15

Sep-

15

Oct

-15

Nov

-15

Dec-

15

Jan-

16

Feb-

16

Mar

-16

Apr-1

6

May

-16

Jun-

16

Jul-1

6

Aug-

16

Sep-

16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7

May

-17

Jun-

17

26.03

4.63

Graph 3.31 Share of Outstanding Restructured External Debt to Total Restructure External Debt (%)

Jun-17May-17Apr-17

Mar-17Feb-17Jan-17 Dec-16Nov-16Oct-16Sep-16Aug-16

Jul-16Jun-16

May-16Apr-16

Mar-16Feb-16Jan-16 Dec-15Nov-15Oct-15Sep-15Aug-15

Jul-15Jun-15

May-15Apr-15

Mar-15Feb-15Jan-15

15.11

Positive Tone Negative Tone

84.89

0% 20% 40% 60% 80% 100%



Table 3.9 Types of Positive and Negative Tone External Debt Restructuration

Restructuration Tone Type of Restructuration

External Debt Position, Non-Financial (USD,

millions)

Number of Facilities

Negative Tone

Reconditioning 10,812 476

Rescheduling 6,479 771

Other Restructuring 5,596 279

Capitalised Interest 3,593 66

Debt to Equity Swap 102 16

Debt Reduction 98 6

Positive Tone

Creditor Diversification 1,976 118

Refinancing 1,408 33

Raised Ceiling 630 33

Rollover 628 63

Total 31,323 1,861

Graph 3.32 Interest and Principal Payments on Positive and Negative Tone Restructured External Debt

35250Interest Payments(USD, millions)

Principal Payments(USD, billions)

150

200

100

50

0

15

25

5

30

10

20

-

Jan-

15Fe

b-15

Mar

-15

Apr-1

5M

ay-1

5Ju

n-15

Jul-1

5Au

g-15

Sep-

15O

ct-1

5N

ov-1

5De

c-15

Jan-

16Fe

b-16

Mar

-16

Apr-1

6M

ay-1

6Ju

n-16

Jul-1

6Au

g-16

Sep-

16O

ct-1

6N

ov-1

6De

c-16

Jan-

17Fe

b-17

Mar

-17

Apr-1

7M

ay-1

7Ju

n-17

73.61

10.3

Positive Tone (rhs) Negative Tone

Jan-

15

Mar

-15

May

-15

Jul-1

5

Sep-

15

Nov

-15

Dec-

15

Jan-

16

Mar

-16

Mei

-16

Jul-1

6

Sep-

16

Nov

-16

Jan-

17

Mar

-17

Mei

-17

0.92

0.04

3.50 3.50

1.501.50

2.50 2.50

0.5

0.5

3.00 3.00

1.001.00

2.002.00

0.0

0.0

-0.5


(USD miliar)

87BANK INDONESIA





Box 3.1. Steel Industry Performance in East Java9

Corporate performance in East Java deteriorated

slightly in the first half of 2017 due to externalities

and domestic developments, namely the uncertain

global geopolitical situation, which heightened the

risks associated with the leading export commodities

from East Java. In addition, public consumption has

remained relatively stagnant, while industry in the

region relies on imported goods, thereby restraining

the pace of economic growth in the province of

East Java.

The slowdown in East Java has been reflected by

declining productivity and profitability. Nevertheless,

corporate liquidity, solvency and repayment capacity

have continued to improve. Corporate performance

in East Java is favourable compared to the national

average in terms of profitability, productivity,

liquidity and long-term repayment capacity but

short-term repayment capacity remains behind the

national average.

By sector, the performance of the miscellaneous

industries as well as the basic industries and

chemical industry was suboptimal, reflected by

declining productivity and profitability, which

undermined repayment capacity. Furthermore,

weak performance was further corroborated by

slower credit growth in East Java, particularly

affecting loans to the base metals industry, plastics

industry, trade of construction materials sector

as well as multipurpose loans, housing loans and

automotive loans. Based on loan type, working

capital loans were the main drag on credit growth

along with consumer loans. Working capital loans

dominated, accounting for 53.6%, disbursed to

corporations (66.2%) as working capital loans

and consumer loans, with the majority (28.2%)

extended to individuals (99.2%).

The credit slump in the base metals industry of East

Java has persisted since 2014, as demonstrated

9 Source: Regional Financial Stability Report (KSKD) of East Java Province, 2017 (processed).

Consumer Loans


Investment Loans

Total Credit

% [yoy]

I II III IV I II III IV I II III IV I II III IV I III III IV

2012 2013 2014 2015 2016 2017

0

5

10

15

20

25

30

35

40

21.14

7.89

11.19

2.50

Box Graph 3.1.1 Bank Loans in East Java Box Graph 3.1.2 Trend and Share of Loan Disbursements by Sector

Kredit Korporasi (Share)


Trade30

40

50

60 0.99;58.86

0.99;23.89

70

20

10

-1.0 -0.5 0.0 0.5 1.0 1.5

0

Source: Commercial Bank Reports (processed)

(correlation with credit trend)

88 BANK INDONESIA


Source: BPS-Statistics Indonesia (processed)

Box Table 3.1.1 Trend and Share of Loan Disbursements by Sector

Type Borrower Sector Subsector Correlation Share

Working Capital Loans Corporate


Base Metals Iron and Steel 0.952 7.1

Articles of Plastic 0.973 5.1

Trade Trade of Construction Materials 0.970 9.0

Investment Loans Individual

Multipurpose 0.964 43.8

HousingHousing Loans for 22 – 70m2 0.990 15.0

Housing Loans for > 70m2 0.993 13.2

Automotive Cars 0.905 11.5

by declining exports. Nevertheless, exports began

to rebound in the third quarter of 2016, especially

consignments to India, United States, the Philippines,

Japan and Europe.

The performance of public non-financial

corporations operating in the iron and steel industry

is also representative of the base metals industry

in East Java, with PT Jaya Pari Steel Tbk (JPRS),

PT Steel Pipe Industry of Indonesia Tbk (ISSP),

PT Gunawan Dianjaya Steel Tbk (GDST) and PT

Betonjaya Manunggal Tbk (BTON) operating as the

main players. The performance of those four firms

has deteriorated since 2014, particularly in terms

of productivity and profitability. In the first quarter

of 2017, however, performance began to rebound

in line with the proliferation of government and

private infrastructure projects in Indonesia.

I II III IV I II III IV I I III IIIII IIIIV IV

2013

yoy (%)

yoy (%)

2014 2015 2016 2017

Credit Growth Industry Growth

7.9

(10.9)

35

30

25

20

15

10

5

0

-5

-10

-15

Box Graph 3.1.4 Iron and Steel ExportsBox Graph 3.1.3 Loans Disbursed operational to the Base Metals Industry

2014

-15.0

-83.7 -80.2-91.1 -93.0

-34.3

-1.6

-17.22.3 -6.4

10.624.7

-36.9

63.7

-2.5

-23.4-9.5

-14.4

-19.7-11.4

-2.3-13.1

-12.5

-18.4-28.7

-18.1

I I I III II IIIII III IIIIV IV IV

2015 20162014 2015 20162014 2015 20162014 2015 2016 2017

80

60

40

20

-

(20)

(40)

(60)

(80)

(100)

(120)

Export

Iron & Steel Growth Articles of Iron & Steel Growth


89BANK INDONESIA





Corporate performance in East Java moderated

slightly in the first quarter of 2017 due to external

and internal developments, namely the uncertain

global geopolitical situation, which heightened the

risks associated with the leading export commodities

from East Java. In addition, public consumption has

remained relatively stagnant, while industry in the

region relies on imported goods, thereby restraining

the pace of economic growth in the province of East

Java.

The slowdown in East Java has been reflected by

declining productivity and profitability. Nevertheless,

corporate liquidity, solvency and repayment capacity

have continued to improve. Corporate performance

in East Java is favourable compared to the national

average in terms of profitability, productivity,

liquidity and long-term repayment capacity but

short-term repayment capacity remains behind the

national average.

The metal industry in Indonesia continues to face

various constraints in the form of stiff competition

from cheaper imported products from China, non-SNI

(Indonesia National Standard) products and products

sold without VAT as well as the effect of lower global

steel prices and delayed high-rise building projects.

Ineffective controls on imports by the government

have led to an oversupply of steel that has depressed

base metal prices, including iron and steel.

Additionally, export sales are not optimal due to

the protectionist barriers erected in other countries

through import duties on steel and anti-dumping

regulations in China, United States, India, Thailand

and Australia. Such inauspicious circumstances have

been exacerbated further by weak demand from

Europe, Canada, United States, Australia, Malaysia

and Thailand as well as the economic embargo on

exports to Iran. The market share of steel exports

has also been eroded by additional competition

Box Graph 3.1.6 Productivity of the Steel Industry Box Graph 3.1.5 Profitability of the Steel Industry

I II III IV

I II III IV

I II III IV

I II III IV

I

I

I

I

II

II

III

III

IV

IV

2014

2014

15

1.2

101.0

5 0.8

0

0.4

0.6

-50.2

-10

-15

0.0

ROA (%)

(Asset Turnover)

2015

2015

2016

2016

2017

2017

ISSP ISSPBTON BTONIndustry (rhs) Industry (rhs)JPRS JPRSGOST GOST

7

6

5

3.98

0.73

1.400.57

(-2.32)

0.390.660.37

1.62

0.584

3

2

1

0

Source: Bloomberg (processed)

10 Liaisons and Focus Group Discussions (FGD) held at Bank Indonesia.

90 BANK INDONESIA



Box Graph 3.1.7 NPL of the Manufacturing Industry in East Java

I II III IV I II III IV I I III IIIII IIIIV IV

2013 2014 2015 2016 2017

7

6

5

4

3

2

1

0

-1

NPL (%)

Metals Fish Cigarettes Fertiliser Plastics

(%)

6.00

2.79

2.35

0.41

from other countries, including South Korea and

Japan, which has culminated in reduced production

capacity and inventory of the base metals industry

located in East Java.

Investment in the iron and steel base metals

industry has tracked a downward trend since 2014.

The investment projects have merely been for the

development of power substations to save electricity

costs, construction of new power substations to

reduce logistics costs and automation for greater

cost efficiency. In addition, higher operating costs

due to more expensive labour and energy (electricity)

costs as well as imported raw materials as a result

of the weak rupiah in 2014 have burdened the base

metals industry. Lower selling prices, combined with

higher operating costs have squeezed margins,

while less demand and automation have decimated

the labour force.

Credit risk in the iron and steel base metals industry

has also increased, with the NPL deteriorating from

3.32% in the fourth quarter of 2016 to 2.79%

in the first quarter of 2017. Such conditions have

forced the banks to become more prudent when

lending to the sector, as reflected by slower credit

growth in the industry, contracting from 0.4% in

the fourth quarter of 2016 to -10.9% in the first

quarter of 2017. Nevertheless, improving export

performance and the proliferation of government

infrastructure projects have increased the supply

and demand of credit in the base metals industry.

91BANK INDONESIA





92 BANK INDONESIA


Pandawa Lima are the five brothers as the protagonists of the Mahabharata narrative, namely

Yudhishthira, Bhima, Nakula, Sahadeva and Arjuna. Bhima was strong, unlike his four brothers. Pandawa

Lima may be interpreted as financial institutions. Bhima, representing strength, is the banking industry,

dominating the total assets of the financial system. Consequently, the banking industry contains the most

risk and can influence the other institutions. A strong banking industry is resilient, however, to the risks

originating from the global and domestic economies.

93BANK INDONESIA





05


05

In general, banking indicators were mixed in the first half of 2017. The banks responded

to milder pressures in the financial system as well as global and domestic economic

gains with prudence due to the looming threat of credit risk. Borrowers and prospective

borrowers were also cautious and tended to wait and see when addressing the latest

economic developments.

Total assets of the banking industry stood at Rp7,026.3 trillion, with growth accelerating

from 9.73% to 10.43% in the first semester of 2017. The additional assets stemmed

primarily from an increase in deposits, most of which were subsequently placed in

loans or securities. The banks expanded their securities portfolios due to a sluggish

intermediation function, which moderated as deposit growth slumped to 10.30% (yoy)

and credit growth to just 7.75% (yoy). The banking industry maintained adequate

liquidity, in part, due to the inflow of repatriated funds from the Tax Amnesty (as of

March 2017), expansion of the government accounts and slow credit growth. In general,

the banks also contained the risks in the banking system despite escalating credit risk,

which was amplified by investment loans and consumer loans. Consequently, the gross

NPL ratio deteriorated from 2.93% to 2.96%.

The Islamic banking industry continued to grow, driven by private deposits, especially

demand deposits and term deposits. The intermediation function accelerated and the

NPF ratio improved. Meanwhile, congruent with the overall credit slump, growth of

MSME loans also tended to slow, particularly affecting loans allocated to micro and

small enterprises. Furthermore, the downswing of MSME loans was accompanied by an

increase in the corresponding MSME credit risk.

The nonbank financial industry performed well in terms of financing and funding

on the back of finance companies and insurance companies. Nevertheless, the

interconnectedness between the banking and nonbank financial industries increased as

the banks lent more to finance companies and insurance firms placed more funds in the

banking industry.

BANKS AND NONBANK FINANCIAL INSTITUTIONS

04


94 BANK INDONESIA94 BANK INDONESIA

Capital Adequacy and Liquidity Indicators: BANKS

Banking Industry PerformanceRemained Solid

CONVENTIONAL BANKING PERFORMANCE WAS OBSERVED TO MODERATE, WHILE THE ISLAMIC BANKING INDUSTRY AND FINANCE COMPANIES IMPROVED

22.56%

5.90%

S I-20168.89%

S I-20163.24%

S I-201697.40%

S I-201682.80%

S I-20162.26%

S I-201620.35%

8.89% 2.93% 8.3%

97.40% 4.58%22.69%

9.60%

S II-20167.86%

S II-20162.93%

S II-201699.36%

S II-201682.85%

S II-20162.17%

S II-201620,93%

7.86% 1.24% 2.96% 8.4%

99.36% 4.15%22.52%

10.30%

S I-20177.37%

S I-20172.96%

S I-2017101.26%

S I-201779.48%

S I-20172.42%

S I-201721.15%

7.37% 1.41% 7.4%

101.26% 4.59%

CAR

Interest rate risk was contained, accompanied by a narrower intermediation spread. The banking industry maintained a long position on foreign exchange totalling Rp6.34 trillion. The risk of SBN price fluctuations was also mitigated as SBN yield and volatility declined.

Growth of bank loans moderated from 7.86% to 7.37% on low demand for new loans from the corporate sector.

Deposit growth in the banking industry accelerated from 9.60% to 10.30% in the reporting period, edged up by expansion of the government accounts and the inflow of funds from the Tax Amnesty.

The gross NPL ratio deteriorated from 2.93% to 2.96% in the reporting period. Likewise, the net NPL ratio deteriorated from 1.24% to 1.41%, with investment loans and consumer loans intensifying credit risk.

Growth of MSME loans slowed to 7.4% (yoy) in the reporting period due to muted demand for financing and escalating credit risk.

MSME NPL

S I-2016

S I-2016

5.9%

S I-2016 S II-2016 S I-2016

S I-2016 S I-2016S II-2016

S I-2016

9.60%

S I-2016 S II-2016

S II-2016 S II-2016S I-2017

S I-2017

10.30%

S I-2017 S I-2017 S I-2017

S I-2017 S I-2017

NCDAL

Deposits LoansMSME Loans

Non-Performing Loans

LIQUIDITY

EFFICIENCY PROFITABILITY

INTERMEDIATION

CREDIT RISK

Loans

NPL

AL/NCD

BOPO ROA

AL/Deposits

CIR NIM

Deposits

56.20 5.44%55.53 5.47%57.85 5.21%

S I-201622.29%

S II-201622.69%

S I-201722.52%CAR

CAPITAL





95BANK INDONESIA

Capital Adequacy and Intermediation Indicators: Sound

Nonbank financial industry performance improved during the first semester of 2017 but Financing Risk remained high

Islamic Banking Industry remained soliddespite the high Financing Risks

14.72%

13.05%

89.68%

4.96% 5.68%

872.0 T

105.9%

18.84%

12.19%

424.4 T

1.17% 0.81% 3.26%

82.71%

12.22%

0.73%

5.67%

155.74%

3.69%

1.69%

13.42%

3.59%

11.04%

15.95%

20.83%

86.26%

15.22% 4.42%

944.5 T

121.3%

22.04%

17.53%

442.7 T

4.29% 6.67% 3.47%

82.77%

11.02%

0.63%

4.59%

157.99%

3.21%

1.66%

21.70%

3.87%

12.01%

16.42%

25.14%

83.00%

17.31% 4.47%

1012 T

120.1%

21.82%

16.09%

462.3 T

6.11% 8.95%

82.24%

12.48%

1.10%

9.50%

147.31%

3.61%

1.67%

20.51%

3.83%

11.49%

CAR FDR

Financing from finance companies increased, primarily as multipurpose financing (accounting for 58.38% of the total) and investment financing (27.38% share)

Business risks in the insurance industry, specifically the gross claims to premiums ratio, decreased for all insurance types, with General Insurance and Reinsurance as the only exceptions.

Funding sources primarily originated from domestic loans, growing by 15.67% on lower lending rates in the banking industry. Meanwhile, finance companies reduced their reliance on external debt, which contracted by -11.22% (yoy)

Total assets of the insurance industry were dominated by life insurance. accounting for a 42.95% share of the total.

Financing risk at finance companies increased, mainly due to the Transportation sector in line with sluggish mining sector performance.

Asset Value

AL/Deposits

AL/NCD

Asset Value

Assets

BOPO EfficiencyRatio

Profitability - ROE

Profitability - ROA

Profitability - ROE

Profitability - ROE

Profitability - ROA

Liquidity - CR

Investment Volume

Profitability - ROA

Profitability - ROE

S I-2016

S I-2016

S I-2016

S I-2016 S I-2016

S I-2016

S I-2016

S I-2016

S I-2016

S I-2016

S I-2016 S I-2016 S II-2016

S I-2016

S I-2016

S I-2016

S I-2016

S I-2016

S I-2016

S I-2016

S I-2016

S I-2016

S I-2016

S II-2016

S II-2016

S II-2016

S II-2016 S II-2016

S II-2016

S II-2016

S II-2016

S II-2016

S II-2016

S II-2016 S II-2016 S I-2017

S II-2016

S II-2016

S II-2016

S II-2016

S II-2016

S II-2016

S II-2016

S II-2016

S II-2016

S II-2016

S I-2017

S I-2017

S I-2017

S I-2017 S I-2017

S I-2017

S I-2017

S I-2017

S I-2017

S I-2017

S I-2017 S I-2017

S I-2017

S I-2017

S I-2017

S I-2017

S I-2017

S I-2017

S I-2017

S I-2017

S I-2017

S I-2017

Funding

Deposits Financing NPF

Finance Companies

INSURANCE

Assets

Financing

Risks

Non-Performing Financing

96 BANK INDONESIA


4.1.1. Liquidity Risk

Liquidity in the banking industry increased on

the previous period. Nevertheless, bank liquidity

experienced a transient tightening towards the end

of the first semester of 2017 as currency flowed

out of the banking system to meet the seasonal

spike in demand during Eid-ul-Fitr. The banking

industry maintained liquidity above the threshold

through sound liquidity management during

periods of distress (April and June 2017). The

inflow of repatriated funds in the first quarter of

2018 from the successful Tax Amnesty helped the

banks to maintain liquidity along with expanding

government accounts and persistently sluggish

credit growth.

The resilience of bank liquidity was demonstrated by

the high ratio of liquid assets to non-core deposits

(NCD). The LA/NCD ratio reflects a bank’s ability to

meet its obligations in the form of potential deposit

withdrawals and also to support credit expansion.

In the first semester of 2017, the LA/NCD ratio

increased from 99.36% to 101.26%, well above

the 50% threshold. Furthermore, the high LA/NCD

ratio was consistent with the LA/deposits ratio,

which reached 21.15% in the second semester of

2017.

Based on the BUKU bank groups, the LA/NCD ratio

was reported to rise by BUKU 1, 2 and 3 banks,

contrasting the decline observed at BUKU 4 banks,

primarily affecting state-owned banks adhering to

4.1. Banking Sector Dynamics and Risks

the cyclical intermediation trend at the beginning

of each year, when credit growth tends to outstrip

deposit growth, which requires the affected banks

to dip into their liquidity buffers to bridge the

resultant gap.

M2 growth, as a measure of liquidity in the

economy, accelerated from 10.02% to 10.60% in

the reporting period in line with deposit growth and

expanding financial operations by the government.

On the other hand, narrow money (M1) growth

decelerated from 17.27% to 13.29% as currency

flowed out of the banking system to satiate seasonal

demand during Eid-ul-Fitr.

4.1.2. Intermediation Risk

In the first semester of 2017, the bank

intermediation function moderated slightly,

as evidenced by slower credit growth despite

stronger deposit growth. Weaker credit growth

was congruous with the holy fasting month of

Ramadan and Eid-ul-Fitr, which this year coincided

with the first semester. Nonetheless, slower credit

growth was merely an extension of the ongoing

trend since the previous year, driven by dwindling

demand for new loans from the corporate sector.

On the other hand, growing demand for financing

from the government to fund infrastructure

projects offset further declines in credit growth.

Such developments were also corroborated by a

survey of the lending standards1 index, which was

observed to increase, thus making borrowers more

reluctant to seek loans. Credit growth is expected

to rebound as economic activity ramps back up

after Eid-ul-Fitr and the banking industry opts to

ease its lending standards.

1 Lending standards are general policy guidelines for the disbursement of loans to prospective borrowers at a financial institution. Lending standards may differ between financial institutions

and regions. The Lending Standards Index measures how tight or loose the guidelines are in the banking industry.

97BANK INDONESIA





Graph 4.1 Bank Liquidity Ratios

90%

80%

100%

110%

75%

Mar

-13

Jun-

13

Sep-

13

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

95%

85%

105%

115%101.26%

21.15%

19%

17%

21%

23%

16%

20%

18%

22%

24%

LA/NCDLA/Deposits (rhs)

Graph 4.2 Liquid Assets of the Banking industry

50Dec’12 Dec’14Dec’13 Dec’15 Dec’16Jun’13 Jun’15Jun’14 Jun’16 Jun’17

200

0

70600

90 1,000

% Rp T

60400

80800

100 1,200

110 1,400

120 1,600

LA/NCD Liquid Assets (rhs)LA = Cash + Placements at Bank Indonesia + Excess Reserve – RRNCD = 30% of Demand Deposits + 30% of Savings Deposits + 10% of Term Deposits


Deposit Growth

Deposit growth in the banking industry accelerated

from 9.60% (yoy) to 10.30% (yoy) in the reporting

semester. The surge of deposits originated from the

Tax Amnesty through to March 2017, expansion of

the government accounts and the base effect from

the previous year2.

Based on currency, the growth of rupiah deposits

decelerated from 11.62% to 10.48%, while foreign

Table 4.1 LA/NCD by BUKU Bank Group Table 4.2 Growth of Liquid Assets

AL/NCD Ratio (%)

2014 2015 2016 2017

Dec Jun Dec Jun Dec Jun

BUKU 1 109.79 88.33 84.38 106.56 100.95 120.68

BUKU 2 92.81 89.64 92.95 101.61 110.34 124.41

BUKU 3 96.18 101.81 102.66 107.06 105.20 112.64

BUKU 4 103.23 88.11 88.89 90.94 93.28 89.31

Industry 99.83 92.50 93.44 97.40 99.36 101.26

Year

Penambahan AL (Rp T)Semester I 2017

LA Growth (Rp, trillions) yoy

2014 (0.94) 33.30

2015 (24.04) 126.12

2016 73.05 110.11

2017 54.84 136.40


Graph 4.3 Liquidity Growth in the Economy and Bank Liquidity Ratios

Graph 4.4 Government Net Expansion

250

Rp, trillions (ytd)

200

150

50

100

0

(50)

2013 2014 2015 2016 2017

135

69

157171194

Jan May SepMar Jul NovFeb Jun OctApr Aug Dec

25%

20%

15%

5%

10%

0% 0%

40%

80%

20%

60%

100%

120%

140%

99.36%

97.82%

10.02%

2012 2013

M2 (%yoy) M1 (%yoy) - (rhs) LA/NCD (%) – (rhs)

20152014 2016Mar Mar Mar Mar MarSep Sep Sep Sep SepJun Jun Jun Jun JunDec Dec Dec Dec Dec

2 The base effect implies higher annual growth (yoy) due to lower annual growth than normal in the same period one year earlier.

98 BANK INDONESIA


currency deposits, which have contracted since

March 2016, began to post positive growth in

January 2017, achieving 9.26% in the first semester

of 2017.

The structure of bank deposits was still dominated

by short-term deposits, creating mismatch risk

to bank financing, most of which is long term.

Furthermore, the dependence on core deposits and

expensive sources of funds remained despite bank

efforts to diversify the sources of funds and CASA.3

Nominally, most deposit growth was realised at BUKU

2 and 4 banks due to the impact of the Tax Amnesty

and expansion of government accounts. Total receipts

of repatriated funds from the Tax Amnesty in the first

semester of 2017 amounted to Rp17,887 billion,

most of which (72.83%) flowed through BUKU 4

banks. As a percentage, BUKU 1 banks reported

the strongest deposit growth, primarily because of

the base effect, namely negative deposit growth at

BUKU 1 banks last year.

In the first half of 2017, term deposits posted 10.32%

(yoy) growth, up from 6.46% in the previous period

and primarily affecting term deposits of over Rp2

billion, which accelerated from 8.53% to 14.18%.

Growth of term deposits valued at ≤ Rp2 billion also

sped up, increasing from 2.35% to 2.57% (yoy).

In contrast, both demand deposits and savings

deposits experienced slower growth, declining from

12.33% (yoy) to 11.23% (yoy) and from 11.16%

(yoy) to 9.56% (yoy) respectively.

Based on market share, term deposits and demand

deposits posted gains, while savings deposits

declined. The expanding share of term deposits

was primarily driven by those above Rp2 billion.

Furthermore, the latest data points to repatriated

fund placements in term deposits at 43.9%.

Based on depositor, the value of Local Government

deposits was the main contributor to deposit growth

in the first semester of 2017 because of dropped

funds from the Central Government. In addition to

Source: Indonesia Banking Statistics, OJK, processed

Graph 4.5 Deposit and Credit Growth (yoy)

15%

9.60% 10.30%

7.37%7.86%

5%

10%

0%

Sem II 2015 Sem II 2016Sem I 2016 Sem I 2017

Table 4.3 Loan-to-Deposit Ratio (LDR) by BUKU Bank Group

Description Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1Credit (Rp, trillions) 68.59 72.52 76.63 83.89Deposits (Rp, trillions) 74.58 88.85 81.04 106.65 LDR (%) 91.98 81.61 94.55 78.65

BUKU 2Credit (Rp, trillions) 601.41 621.14 646.73 666.30Deposits (Rp, trillions) 629.51 696.24 679.39 781.55LDR (%) 95.54 89.21 95.19 85.25

BUKU 3Credit (Rp, trillions) 1,436.51 1,453.55 1,476.83 1,492.68Deposits (Rp, trillions) 1,449.59 1,468.38 1,541.65 1,557.62LDR (%) 99.10 98.99 95.80 95.83

BUKU 4Credit (Rp, trillions) 1,951.38 2,021.09 2,177.01 2,248.51 Deposits (Rp, trillions) 2,259.57 2,321.20 2,534.68 2,599.83LDR (%) 86.36 87.07 85.89 86.49

IndustriCredit (Rp, trillions) 4,057.90 4,168.31 4,377.19 4,491.37Deposits (Rp, trillions) 4,413.24 4,574.67 4,836.76 5,045.65 LDR (%) 91.95 91.12 90.50 89.01

3 CASA stands for current account and saving account (demand deposits and savings deposits).

Deposits Credit

*) Banks are classified based on OJK BUKU groups as of June 2017

99BANK INDONESIA





the regional administrations, the deposits of private

non-financial institutions and private nonbank

financial institutions also edged up deposit growth.

Conversely, individual deposits and other private

deposits experienced declines.

Spatially, deposits posted growth in nearly all

regions of the Indonesian archipelago, except

in Papua and the Maluku Islands. In the first

semester of 2017, deposit accumulation was still

concentrated on the island of Java in line with

business activity and the circulation of money

that is centred on Java, especially in Jakarta as

the primary economic hub. The share of deposits

in Jakarta accounted for 49.69% of total bank

deposits.

40

MoreRigid

MoreLoose

Unchanged

20

30

10

0Investment

CreditWork Capital

CreditConsumption

CreditTotal

35

15

25

5

Survey in Q4/2016 Survey in Q1/2017 Survey in Q2/2017 Expectations in Q2/2017

Graph 4.6 Lending Standards


Graph 4.7 Deposit Growth (yoy)

Sem I

2014

Deposit Growth (yoy) Rupiah Deposit Growth (yoy)

Foreign Currency Deposit Growth (yoy)

2015 2016 2017

Sem I Sem ISem II Sem II

Aug

Sep

Oct

Nov De

cJa

nFe

bM

arAp

rM

ayJu

nJu

lAu

gSe

pO

ctN

ov Dec

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov De

cJa

nFe

bM

arAp

rM

ayJu

nJu

lAu

gSe

pO

ctN

ov Dec

Jan

Feb

Mar

Apr

May

Jun

Sem I

40%

20%

30%

10%

-10%

0%

-20%

Sem II

10.48%10.30%

9.26%

Table 4.4 Market Share of Deposits based on Maturity

Maturity Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

JW <= 1 Month 74.1% 72.6% 73.7% 73.3%

JW > 12 Month 2.1% 2.1% 2.1% 2.3%

JW 1-3 Month 14.6% 15.4% 14.6% 14.7%

JW 3-6 Month 5.4% 6.1% 5.5% 5.9%

JW 6-12 Month 3.8% 3.8% 4.1% 3.7%

Total 100% 100% 100% 100%


100 BANK INDONESIA


Graph 4.8 Market Share of Deposits based on Core Depositors/Non-Core Depositors

%

90.0%

100.0%

50.0%

70.0%

30.0%

80.0%

40.0%

60.0%75.6% 73.4% 75.7% 73.5%

24.4% 26.6% 24.3% 26.5%20.0%

10.0%

Sem II 2015 Sem I 2016 Sem II 2016 Sem I 20170.0%

Core Depositors Non-Core Depositors

Table 4.5 Deposit Growth by BUKU Bank Group (%, yoy)

BUKU Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017 Market Share as of Semester I 2017 (%)

BUKU 1 6.90 0.05 8.67 20.03 2.11

BUKU 2 6.31 3.91 7.92 12.25 15.49

BUKU 3 7.08 1.90 6.35 6.08 30.87

BUKU 4 7.66 9.50 12.18 12.00 51.53

Industry 7.26 5.90 9.60 10.30 100.00

Source: Indonesia Banking Statistics, OJK, processed



Table 4.6 Receipts of Tax Amnesty Funds by BUKU Bank Group

BUKU

As of December 2016 As of December 2017 Additional in 2017

Tax Amnesty Funds (Rp, billions) Tax Amnesty Funds (Rp, billions) Tax Amnesty Funds (Rp, billions)

Redemption Payments

Repatriated Funds Total Redemption

PaymentsRepatriated

Funds Total Redemption Payments

Repatriated Funds Total

BUKU 1 - - - - - - - - -

BUKU 2 4,521 7,985 12,506 4,556 8,030 12,586 34 45 80

BUKU 3 22,675 40,321 62,996 22,867 44,909 67,776 192 4,588 4,780

BUKU 4 68,154 50,181 118,335 69,340 62,022 131,362 1,186 11,841 13,027

Industri 95,350 98,487 193,836 96,762 114,962 211,724 1,412 16,475 17,887

Source: OJK

Credit Growth

Credit growth has continued to moderate. In the

reporting semester, bank loans expanded at 7.75%

(yoy), down from 7.87% (yoy) in the second semester

of 2016 in line with corporate reluctance to expand

in favour of efforts to enhance internal efficiency by

reducing new loan disbursements and investments.

Consequently, growth of investment loans also

slowed in the reporting period. On the supply side,

the banking industry was focused on consolidation of

non-performing loans (NPL) and was more selective

when disbursing new loans.

By currency, rupiah loans were responsible for the

weaker credit growth, decelerating from 9.15% (yoy)

in the second semester of 2016 to 7.59% (yoy) in the

reporting period. In contrast, foreign currency loans

enjoyed robust growth, increasing from just 0.59%

(yoy) to 8.74% (yoy), driven by loans extended to

leasing companies and crude palm oil (CPO) firms.

Based on loan type, the credit slump was blamed on

investment loans, primarily allocated to the electricity

sector and transportation industry in line with soft

commodity prices as well as the wait-and-see attitude

of business players to rising prices of coal and crude

palm oil (CPO). Conversely, consumer loans and

working capital loans enjoyed stronger growth.

Bank loan disbursements were still dominated by

productive loans, namely working capital loans,

accounting for 46.80% in the second semester of

2016 and first semester of 2017. Meanwhile, the

share of investment loans declined in the first semester

of 2017 to 25.10% as the share of consumer loans

increased to 28.08%.

By economic sector, weaker credit growth originated

primarily from the trade sector in line with a shift in

public consumption patterns, as consumers tended

101BANK INDONESIA





Graph 4.9 Deposit Growth by Type

40%

30%

50%

20%

10%

0%

-10%

-20%

Jan

Feb

Mar Ap

rM

ay Jun Jul

Aug

Sep

Oct

Nov De

cJa

nFe

bM

ar Apr

May Jun Jul

Aug

Sep

Oct

Nov De

cJa

nFe

bM

ar Apr

May Jun Jul

Aug

Sep

Oct

Nov De

cJa

nFe

bM

ar Apr

May Jun Jul

Aug

Sep

Oct

Nov De

cJa

nFe

bM

ar Apr

May Jun

Sem ISem I20142013 2015 2016 2017

Sem I Sem I

14.18%11.23%9.56%2.57%

Sem IISem II Sem II Sem I Sem II

Demand Deposits Savings Deposits

Term Deposits ≤ Rp2 billion Term Deposits > Rp2 billion

Graph 4.10 Composition of Bank Deposits

22.38% 23.44% 23.24% 23.64%

31.63% 31.02% 32.08% 30.81%

15.45% 15.16% 14.42% 14.10%

30.54% 30.38% 30.25% 31.45%

Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

Demand Deposits Savings Deposits

Term Deposits ≤ Rp2 billion Term Deposits > Rp2 billion


to delay spending and substitute goods for more

affordable items. The decline in trade business

volume subsequently triggered weaker demand for

new loans. Furthermore, the shifting consumption

patterns could ultimately undermine credit growth

in the manufacturing industry. Growth of new loans

disbursed to the manufacturing industry continued to

expand in the first half of the year but the risk remains

of a future slowdown.

Regionally, the deepest declines of credit growth in

the first half of 2017 were reported in Papua and the

Maluku Islands as well as Bali and Nusa Tenggara.

The slowdown persisted due to lacklustre recoveries

in regions dependent on mining commodities. In

contrast, credit growth accelerated on the islands

of Java and Kalimantan. Java dominated loan

disbursements and credit growth in the region,

originating from infrastructure-construction loans,

which, in turn, accelerated the growth of automotive

loans and consumer loans. Furthermore, the island of

Java commands a 69.90% share of total bank credit,

followed by Sumatra (14.66%) and Kalimantan

(5.91%).

In the first semester of 2017, credit growth at

BUKU 2, 3 and 4 banks decelerated compared

to conditions in the previous period, decreasing

from 7.53%, 2.81% and 11.56% (yoy) to 7.27%,

2.69% and 11.25% (yoy) respectively. Slower credit

growth at BUKU 2 and 3 banks was consistent

with limited competitiveness in terms of lending

Graph 4.11 Deposit Performance by Depositor Group

250

50

150

-50

-150

200

0

100

-100

-200

Sem I 2016 Sem II 2016 Sem I 2017

Central Government

Local Government

Private Individual

Private Nonbank Financial Institutions

Private Non-Financial Institutions

Other Private Deposits

Non-Residents

Rp T


102 BANK INDONESIA


Table 4.7 Deposit Share by Island


IslandDeposit Growth (%, yoy)

Deposit Share (%)Semester I 2017

Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

Java 7.48 6.27 10.70 10.82 77.28

Sumatra 4.79 3.05 7.81 10.88 11.35

Kalimantan 0.81 0.58 4.06 5.38 4.11

Sulawesi 17.87 14.07 3.32 4.42 3.03

Bali and Nusa Tenggara 10.09 7.87 5.02 13.32 2.76

Papua and Maluku Islands 8.38 6.13 3.32 2.20 1.46

to large corporations/conglomerates due to the

comparatively higher cost of funds. Meanwhile,

BUKU 4 banks were less inclined to lend because

of a focus on internal consolidation and the

management of existing loans.

Seeking to stimulate credit growth, banks from all

BUKU groups lowered lending rates in line with lower

deposit rates.

MSME Loans

In the first half of 2017, the value of MSME loans

stood at Rp888.5 trillion, with growth decelerating

to 7.4% (yoy) from 8.4% (yoy) in the second

semester of 2016 and 8.3% (yoy) in the same

period one year earlier. Slower MSME loan growth

was caused by weaker-than-expected economic

growth, limited demand for financing form the

banks’ customers and escalating credit risk. Despite

moderating MSME loan growth, the share of such

loans to total credit expanded from 19.4% in the

second semester of 2016 to 19.6% in the first

semester of 2017.

Loans disbursed to micro and small enterprises were

the main drag on MSME credit growth, decelerating

respectively from 10.9% (yoy) and 11.1% (yoy) to

6.7% (yoy) and 7.9% (yoy) in the reporting period.

Sluggish investment loan growth was the main

contributor to weaker MSME loan growth in the

reporting period, decreasing to 1.5% (yoy) from

6.3% (yoy) in the second semester of 2016 and

from 9.6% (yoy) in the first semester of 2016. In

Graph 4.12 Bank Credit Growth (yoy)

40%

20%

30%

10%

-10%

0%

-20%

Sem I20142013 2015 2016

Sem ISem IISem II Sem II

Jul

Aug

Sep

Oct

Nov De

cJa

nFe

bM

ar Apr

May Jun Jul

Aug

Sep

Oct

Nov De

cJa

nFe

bM

ar Apr

May Jun Jul

Aug

Sep

Oct

Nov De

cJa

nFe

bM

ar Apr

May Jun Jul

Aug

Sep

Oct

Nov De

cJa

nFe

bM

ar Apr

May Jun

Sem I Sem II

Deposit Growth (yoy) Rupiah Deposit Growth (yoy) Foreign Currency Deposit Growth (yoy)


2017Sem I

8.74%7.75%7.59%

103BANK INDONESIA






Graph 4.13 Credit Growth by Loan Type Graph 4.14 Credit Share by Loan Type



Investment Loans

Investment Loans

Consumer Loans

Consumer Loans

Sem I 2016 Sem I 2017Sem II 2016

7.30%

8.84%

12.03%

6.93%

8.76%8.64%

7.19%

9.87%

6.50%

Sem I 2017

contrast, working capital loans disbursed to micro,

small and medium enterprises accelerated in the

reporting period to 9.7% (yoy) from 9.2% (yoy) in

the second semester of 2016 and 7.8% (yoy) in the

first semester of 2016.

By sector, the wholesale and retail sector absorbed

most MSME loan growth in the reporting period,

accounting for 52.1% of total MSME credit.

Consequently, slower MSME loan growth was

primarily influenced by weaker MSME loan growth

in the wholesale and retail sector, decelerating to

5.7% (yoy) in the first semester of 2017 from 9.4%

(yoy) in the second semester of 2016 and 12.5%

(yoy) in the first semester of 2016, stemming from

other commodities, including non-foods, beverages

or tobacco, due to weaker public purchasing

power. In addition to tepid MSME loan growth

in the wholesale and retail sector, several other

sectors experienced negative growth, including

real estate. MSME loan growth to the real estate

sector contracted by -5.1% (yoy) in the first

semester of 2017, sliding from 5.7% (yoy) in the

second semester of 2016, primarily due to office

buildings as property developers opted to wait

and see if the government would ease restrictions,

thus repositioning themselves in line with current

demand.

Table 4.8 GDP growth by Economic Sector

Sector2014 2015 2016 2017Dec Jun Dec Jun Dec Jun

Agriculture 5.02 5.20 2.34 2.50 4.03 5.11

Mining (0.25) (1.53) (5.23) 1.18 0.95 0.78

Manufacturing Industry 4.66 4.14 4.52 4.65 3.94 3.88

Electricity Supply 4.89 1.24 0.58 6.86 3.99 (0.50)

Water Supply 4.81 6.20 7.92 4.75 2.51 4.03

Construction 6.83 5.68 6.98 5.93 4.57 6.46

Trade 5.57 2.64 2.53 4.12 3.75 4.36

Transportation and Warehousing 7.28 5.85 7.47 7.40 8.06 8.20

Hotels and Restaurants 6.40 3.51 5.09 5.32 4.57 4.88

Information and Communications 10.31 9.45 9.92 8.47 9.26 10.02

Financial Services 4.54 5.54 11.58 11.44 6.56 5.97

Real Estate 4.80 4.43 3.80 4.81 3.81 3.76

Corporate Services 10.13 7.50 7.88 7.85 6.89 7.47

Government Administration 0.03 5.50 3.84 4.53 1.95 0.09

Education Services 4.46 8.26 6.50 5.24 2.56 2.45

Health Services 8.20 8.43 5.09 5.76 4.29 6.75

Other Services 8.92 8.02 8.13 7.89 7.70 8.32

46.81%

25.10%

28.08%

46.81%

27.47%

25.71%

Sem II 2016

104 BANK INDONESIA


Graph 4.15 Credit Growth by Economic Sector (yoy)

Graph 4.16 Credit Growth by Economic Sector (Rp, trillions)

TradeOthers

Corporate Services

Electricity Supply TotalMining

40

30

20

10

-10

0

-20

3.43% 5.29%

-2.03%

21.58%

11.42% 12.05%14.86%

2.07%

14.36%7.75%9.01%

Social ServicesAgriculture

Construction

Transportation


TradeOthers

Corporate Services

Electricity SupplyMining

120

Rp. T

100

80

60

40

20

-20

0

-40

31.339.4

-3.6%

41.631.5

45.5

14.52.5

16.0

104.5

Sem I 2016 Sem II 2016 Sem I 2017

Sem I 2016 Sem II 2016 Sem I 2017

Social ServicesAgriculture

Construction

Transportation


Table 4.9 Market Share of Credit by Project Location


IslandCredit Growth (%, yoy) Credit Share

(%) Semester I 2017Credit Share

(%) Semester II 2016Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

Java 10.54 10.76 8.66 8.16 8.22 69.73 69.90

Sumatra 8.54 9.72 8.13 6.32 5.90 14.62 14.66

Kalimantan 7.44 3.16 5.19 4.48 7.93 6.04 5.91

Sulawesi 12.54 14.55 15.05 8.95 6.75 5.07 4.98

Bali and Nusa Tenggara 14.96 10.72 10.88 10.96 8.33 3.26 3.26

Papua and Maluku Islands 13.02 11.77 12.74 14.99 8.84 1.28 1.29

Against a backdrop of MSME loan moderation,

several sectors achieved solid MSME credit

growth, including the Agricultural Sector and the

Manufacturing Industry, to which MSME loans

expanded from 9.6% (yoy) and 10.7% (yoy) in the

second semester of 2016 to 14.3% (yoy) respectively

in the first semester of 2017. In the agricultural

sector, palm oil plantations were the main driver

of growth in line with a surge of crude palm oil

(CPO) exports. In the manufacturing industry,

however, the main driver of growth was business

expansion, as reflected by the expansionary Bank

Indonesia Business Survey – PMI (PMI-BIBS), which

increased from 50.91% in the second semester

of 2016 to 51.68% in the reporting period.

By region, the islands of Java and Sumatra continued

to dominate MSME disbursements, accounting for

%

105BANK INDONESIA





58.3% and 19.4% respectively. Such conditions

were supported by the availability of bank office

networks on both islands. Conversely, the MSME

credit share allocated to Kalimantan, Sulawesi, Bali

and Nusa Tenggara as well as Papua and Maluku

remained comparatively small.

People’s Business Loans (KUR)

The government has targeted People’s Business

Loan (KUR) disbursements in 2017 to reach Rp110

trillion through an interest rate subsidy earmarked

for Rp9 trillion in the 2017 State Budget. In the

first semester of 2017, KUR disbursements had

reached Rp45.1 trillion, or 41.03% of the target,

with a total of 2 million borrowers. KUR realisation

in the second quarter of 2017 was down on the

same period one year earlier at Rp54.8 trillion or

54.8% of the target in 2016. In addition to the

effect of weaker economic growth, lower KUR

realisation was also due to (i) fewer disbursements

of new KUR loans in February 2017; as well as (ii)

fewer KUR borrowers and the need to refine the

KUR scheme in line with the target of 40% of KUR

loans allocated to productive sectors (agriculture,

fisheries, industry and construction). In addition

to the approved banks, other financial institutions

began to disburse KUR loans in 2017, including

finance companies and cooperatives.

Table 4.10 Credit Growth by BUKU Bank Group (%, yoy)

BUKU Sem II 2015

Sem I 2016

Sem II 2016

Sem I 2017

Market Share as of Semester

I 2017 (%)

BUKU 1 10.03 11.07 11.72 15.68 1.87

BUKU 2 11.79 8.82 7.53 7.27 15.43

BUKU 3 6.13 3.20 2.81 2.69 32.64

BUKU 4 13.42 13.32 11.56 11.25 50.06

Industri 10.44 8.89 7.87 7.75 100.00

*) Banks are classified based on OJK BUKU groups as of June 2017*) Banks are classified based on OJK BUKU groups as of June 2017

Source: Source: Indonesia Banking Statistics, OJK, processed Source: Bank Indonesia

Graph 4.17Rupiah Lending Rates by BUKU Bank Group

17

16

15

14

13

12

10

11

Sem II Sem IISem II Sem IISem II

20132012 20152014 2016 2017

Sem I Sem ISem I Sem I Sem I

BUKU 4BUKU 2 BUKU 3BUKU 1

Source: Bank Indonesia, 2017

Graph 4.18 MSME Loan Performance

0

400

200

600

Trill

ion

Rp

10%

800

20%

100

500

5%

0%

300

700

15%

19.6%

7.4%

900 25%

Micro Enterprises Small EnterprisesMedium Enterprises MSME Credit Growth (rhs)MSME Credit Share (rhs)

Dec-

13

Feb-

14

Apr-1

4

Jun-

14

Aug-

14

Oct

-14

Dec-

14

Feb-

15

Apr-1

5

Jun-

15

Aug-

15

Oct

-15

Dec-

15

Feb-

16

Apr-1

6

Jun-

16

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-1

7

Jun-

17

415.2

266.3

207.0

106 BANK INDONESIA


By economic sector, the Trade and Agricultural sectors

on the island of Java absorbed most of the People’s

Business Loans (KUR). Compared to conditions

in the first quarter of 2017, the portion of KUR

disbursements to the Trade sector declined in the

second quarter of 2017, while the portion allocated

to the Agricultural, Fisheries and Construction sectors

as well as the Manufacturing Industry increased from

29.2% to 31.1% because the Government set a target

of 40% of KUR loans extended to productive sectors

(agriculture, fisheries, industry and construction).

Credit Risk

Credit risk in the banking industry increased slightly.

The gross NPL ratio, as a proxy of credit risk,

deteriorated from 2.93% to 2.96%. Nevertheless,

the gross NPL ratio had improved from 3.05% in

the same period one year earlier, which proves that

ongoing consolidation in the banking industry has

been a success.

By loan type, investment loans and consumer loans

were than main contributors to increasing credit risk,

with the respective gross NPL ratios deteriorating

from 3.21% and 1.53% to 3.37% and 1.72%.

Conversely, the gross NPL ratio of working capital

loans improved from 3.59% to 3.49%. The higher

gross NPL ratio associated with investment loans

was in line with slower credit growth, decreasing

from 8.64% (yoy) to 6.50% (yoy). Meanwhile, the

deteriorating gross NPL ratio of consumer loans was

induced by housing loans, with the gross NPL ratio

increasing from 2.54% to 2.94%. In contrast, the

gross NPL ratio of working capital loans improved in

line with stronger credit growth, accelerating from

6.93% (yoy) to 7.19% (yoy) in the reporting period.

By economic sector, the main contributors to the

deteriorating NPL ratios in the banking industry

during the first half of 2017 were the trade and

construction sectors, with the value of gross non-

performing loans (NPL) recorded at Rp2.66 trillion

and Rp0.90 trillion respectively. Besides, the mining

sector recorded the highest level of gross NPL in the

reporting semester at 7.84%.

The increasing level of non-performing loans (NPL)

in the trade sector primarily originated from the

trade of construction materials as well as food,

beverages and tobacco in line with weaker-than-

expected gains in public purchasing power.

Consistent with cyclical trends over the past few

years, the coal subsector was the main contributor

to high non-performing loans (NPL) in the mining

sector during the first semester of 2017 as a result

of soft demand and prices. Furthermore, oil and gas

mining services also contributed to the high gross

NPL ratio in the mining sector due to low oil process.

Accordingly, the gross NPL ratios of the coal mining

subsector as well as the oil and gas mining services

subsector deteriorated respectively from 11.09%

and 14.78% to 12.92% and 19.08% in the first

semester of 2017.

Spatially, banks in all regions of Indonesia reported

an increase in their gross NPL ratios, with the

island of Java as the only exception. Regions reliant

on mining commodities as a source of income

experienced the largest increases in the gross NPL

ratio, most significantly in Kalimantan. In contrast,

the gross NPL ratio for Java improved as credit

growth accelerated on the island.

107BANK INDONESIA





Graph 4.19 MSME Credit Growth in 6 Economic Sectors

10%

-10%

30%

yoy

50%

-20%

20%

0

40%

60%

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

Agriculture Manufacturing Industry Construction Social ServicesTrade Real Estate

14.3%14.3%9.9%6.4%5.7%-5.1%

Source: Commercial Bank Reports, 2017, processed

On a semesterly basis, all BUKU bank groups

reported deteriorating NPL ratios in the reporting

period, except BUKU 3 banks. BUKU 2 banks

confirmed the largest increase in the gross NPL ratio

and, consequently, the highest gross NPL ratio of

all BUKU bank groups, which is consistent with the

lack of competitiveness of BUKU 2 banks to extend

loans to large prosperous corporations due to

relatively high lending rates.

Restructured Loans

In the first semester of 2017, restructured loans

totalled Rp248.36 trillion, up Rp3.83 trillion on

the previous period. Consequently, the share of

restructured loans to total credit nearly doubled

from 2.54% to 5.53%. Meanwhile, the share of

special mention (level 2) restructured loans to total

credit increased from 1.65% to 1.83% in the first

semester of 2017.

A significant spike in restructured loans occurred at

the end of 2015 through to the end of 2016, which

was associated with promulgation of OJK Regulation

(POJK) No. 11/POJK.03/2015 concerning Prudential

Principles for Commercial Banks to Stimulate the

National Economy on 24th August 2015. After

that period, the pace of restructured loans began

to ease. Prior to enforcement of the OJK regulation

there were three assessment pillars for the quality of

restructured loans valued at more than Rp1 billion,

Table 4.11 MSME Credit Growth and Share by BUKU Bank Group

Source: Bank Indonesia, Monthly Commercial Bank Reports, 2017, processed

BUKUMSME Loan Growth (yoy) MSME Credit Share (yoy)0

Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 10.85 -0.60 -1.94 -44.36 -49.02 5.68 5.14 5.15 2.64 2.44

BUKU 2 -3.78 -11.09 -10.40 12.25 11.13 15.87 13.70 13.13 14.18 13.59

BUKU 3 -2.29 6.40 3.73 2.69 -1.92 27.57 28.26 26.42 26.77 24.12

BUKU 4 16.12 16.41 17.71 15.60 16.23 50.87 52.89 55.30 56.40 59.85

108 BANK INDONESIA


namely repayment capacity, borrower performance

and business outlook. With the introduction of the

new OJK regulation, however, the assessment of

restructured loan quality was merely based on the

principal/interest repayments for loans valued at

up to Rp5 billion or a maximum of Rp20 billion for

MSME loans disbursed by banks satisfying specific

criteria. The OJK regulation was effective for two

years, ending on 24th August 2017.

In the first semester of 2017, the growth of

restructured loans decelerated in line with slower

rising non-performing loans (NPL). Weaker growth

of restructured loans also stemmed from the banks

resolving most of their non-performing loans (NPL)

and becoming more selective when disbursing new

loans. The end of the effective period of the OJK

regulation is not expected to significantly influence

the quality of bank loans because the banking

industry has been prudent by only restructuring

recoverable loans.

MSME and KUR Credit Risk

A build-up of MSME credit risk was reported in the

first semester of 2017, as indicated by the increase

in the gross NPL ratio from 4.15% in the second

semester of 2016 to 4.59%, which is relatively

high compared to the previous semester and same

period one year earlier because the performance

of MSME borrowers has not seen any significant

improvements despite early signs of lower NPL in

the first half of 2017.

Source: KUR Committee, Coordinating Ministry for Economic Affairs, 2017, processed

Graph 4.20 KUR Realisation against Target, 2015-2017

0

40%

20%

60%

80%

10%

2015 2016 2017

50%

54.8%

41.0%

75.9%

30%

70%

90%

100%

% Capalan thd target


Graph 4.21. Market Share of People’s Business Loans (KUR)

Agriculture, Hunting and Forestry

Fisheries


Trade

Construction

Services

Source: KUR Committee, Coordinating Ministry for Economic Affairs, 2017, processed

58.6%

66.3%

0.0%

0.0%

12.2%

11.0%17.4%

22.3%

1.2%1.9%

5.0%

4.1%

Semester II 2016

Semester I 2017

109BANK INDONESIA





The banking industry confirmed that the highest

gross NPL ratio affected outstanding MSME loans

extended to medium enterprises (5.46%), followed

by small enterprises (4.79%) and micro enterprises

(2.59%). Based on bank group, however, the highest

gross NPL ratios on MSME loans were reported by

BUKU 2 banks (7.56%), followed by BUKU 3 banks

(5.19%), BUKU 1 banks (4.64%) and BUKU 4 banks

(3.67%).

The deteriorating quality of MSME loans in the

first half of 2017 affected nearly all economic

sectors, including the Mining and Quarrying sector

(14.42%) and the Accommodation sector (5.95%).

Conversely, the gross NPL ratio for loans allocated

to the Agricultural sector improved to 3.85% in the

reporting period.

Based on the latest data from the commercial bank

reports, the NPL ratio on People’s Business Loans (KUR)

improved to 2.01% in the first semester of 2017 from

2.60% in the second semester of 2016, while NPG

deteriorated from 3.32% to 3.51%. Nevertheless, the

NPG ratio has begun to improve gradually since March

2017. In general, the higher NPG ratio was caused by

an increase of KUR claims after reaching half maturity

with an average tenor of 2-3 years. Consequently,

KUR claims approved in 2015 and 2016 began to

increase in the first semester of 2017.

4.1.3. Market Risk

Market risks originate from the impact of changes

to market interest rates on: (i) deposit and lending

rates; (ii) SBN portfolio prices in the banking

industry; and (iii) currency risk.

4.0%

5.0%

2.0%

3.0% 2.96%

1.41%

1.0%

0.0%

Gross NPL Net NPL

Sem

II

Sem

II

Sem

II

Sem

II

Sem

II

Sem

II

Sem

II

Sem

II

Sem

II

Sem

I

Sem

I

Sem

I

Sem

I

Sem

I

Sem

I

Sem

I

Sem

I

Sem

I

Sem

I

2008 20122010 2014 20162009 20132011 2015 2017

Graph 4.22 NPL Ratio

Graph 4.23 Gross NPL Ratio by Loan Type



3.74%

3.26%

1.67% 1.53%1.72%

3.59%

3.21%3.49% 3.37%

4.0%

2.0%

3.0%

1.0%

0.0%Working Capital Loans

Sem I 2016 Sem II 2016 Sem I 2017

Investment Loans Consumer Loans

110 BANK INDONESIA


Interest Rate Risk

The banks continued to lower lending rates in the

first half of 2017 in line with bank targets and efforts

to stimulate credit growth. Meanwhile, deposit rates

were also reduced but to a lesser degree. Deeper

cuts to lending rates compared to deposit rates

narrowed the intermediation spread. Nonetheless,

the narrower spread has not significantly eroded

bank profitability, with the net interest margin (NIM)

maintained at a level of 5% and ROA increasing on

the previous period.

During the first semester of 2017, Bank Indonesia

maintained the BI 7-Day (Reverse) Repo Rate

at 4.75%, down from 5% in September 2016.

The historical data showed that reductions to

the BI 7-Day (Reverse) Repo Rate or BI Rate are

followed by corresponding reductions to deposit

rates, including term deposits, demand deposits

and savings deposits. At the end of the reporting

semester, the interest rate on rupiah 1-month

term deposits was lowered to 6.46%, while the

rate on rupiah demand deposits was reduced from

2.18% to 2.13% and rupiah savings deposits

from 1.59% to 1.53%. All bank groups lowered

deposit rates in the reporting period, excluding

interest rates on rupiah demand deposits at BUKU

1 and 2 banks.

The banks lowered lending rates on all loan types.

Interest rates on rupiah working capital loans fell

from 11.38% to 11.14%, rupiah investment loans

Graph 4.24 Gross NPL Ratio by Economic Sector (%)

0.0%

4.0%

20%

6.0%

8.0%

1.0%

5.0%4.35%

3.23%

4.25%3.92%

1.97%1.85%

2.58%

7.84%

1.56%

2.96%

1.73%

3.0%

7.0%

9.0%

Trade TransportationOthers


Construction Agriculture Agriculture Corporate Services

Social Services

Mining Electricity Supply

TOTAL

Graph 4.25 Gross NPL Growth by Economic Sector (Rp, trillions)

120

100

80

60

40

202.66

3.38

(1.59)(0.91)

0.90

(0.49) (0.07) (0.23)

0.75 0.56

-20

Trill

ion

Rp

0

-40

Trade

Transp

ortation

Others

Constructi

on

Agricu

lture

Corporate Se

rvice

s

Socia

l Servi

ces

Manufac

turing I

ndustry

Mining

Electricit

y Supply


111BANK INDONESIA





from 11.21% to 11.00% and rupiah consumer

loans from 13.59% to 13.21%. In addition to

intermediation costs, the banks lowered lending

rates in order to stimulate credit growth against a

backdrop of weak demand for new loans.

Currency Risk

In general, currency risk in the banking industry

was relatively well contained, evidenced by a

comparatively low net open position (NOP). Sharp

exchange rate depreciation in the second semester

of 2016 after Donald Trump won the US election

was transient. In the first semester of 2017, the

banks recorded a long position on foreign exchange

totalling Rp6.34 trillion, reversing the previous short

position of Rp5.09 trillion. Meanwhile, the NOP ratio

increased from 2.18% in the second semester of

2016 to 2.32% in the first semester of 2017, which

was still well below the 20% threshold of bank

capital. BUKU 4 banks maintained the highest NOP

ratio at 3.31%, followed by BUKU 2 banks (1.87%),

BUKU 3 banks (1.21%) and BUKU 4 banks (0.95%).

Risk of Lower SBN Prices

Market risk in the banking industry originating from

changes in SBN prices was mitigated in line with

lower SBN volatility and yields. The IDMA index, as

a measure of SBN prices, rallied from 99.0 in the

second semester of 2016 to 103.64 in the first

semester of 2017.

Table 4.12 Gross NPL by Region

Table 4.13 Gross NPL Ratio by BUKU Bank Group


Island Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017 Credit Share inSemester I 2017 (%)

Credit Share inSemester II 2016 (%)

Java 2.27 2.91 2.92 2.85 69.73 69.90

Sumatra 2.82 3.14 2.68 2.79 14.62 14.66

Kalimantan 3.86 4.76 4.40 4.73 6.04 5.91

Sulawesi 2.98 2.99 2.58 2.97 5.07 4.98

Bali and Nusa Tenggara 2.15 2.69 2.47 3.11 3.26 3.26

Papua and Maluku Islands 3.72 3.79 3.12 3.54 1.28 1.29

Source: Financial Services Authority (OJK), processed

BUKU Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 2.74 2.35 3.21 2.99 3.03

BUKU 2 3.32 3.03 3.81 3.35 3.70

BUKU 3 2.72 2.85 3.17 3.13 2.98

BUKU 4 2.18 2.06 2.73 2.66 2.73

Industry 2.56 2.49 3.05 2.93 2.96

112 BANK INDONESIA


Continuing the trend from the previous period, the

banking industry sought to bolster SBN holdings

congruent with the inflow of Tax Amnesty funds.

Furthermore, larger SBN holdings in the banking

industry were also in line with slower credit growth.

The banks increased placements in available for sale

(AFS) and held to maturity (HTM) SBN portfolios,

indicating the propensity of banks to use SBN as

a liquid asset and for long-term investment rather

than trading.

The banks’ SBN portfolio expanded 1.56% from

Rp541.27 trillion in the second semester of 2016

to Rp458.31 trillion in the first semester of 2017.

Based on bank group, BUKU 1, 2 and 4 banks

expanded their SBN portfolios, contrasting BUKU 3

banks that tended to release some of their tradeable

government securities (SBN). SBN portfolios at

BUKU 3 and 4 banks were maintained for liquidity

purposes through AFS, which can be liquidated at

any time. On the other hand, BUKU 1 and 2 banks

preferred HTM SBN for long-term investment.

BUKU 4 banks dominated SBN holdings, followed

by BUKU 3 and 2 banks.

4.1.4. External Debt in the Banking Industry

Banks used various sources of funds to meet the

requirement for liquidity and financing, including

external debt. In general, banks used the external

debt to extend as loans, improve the funding

maturity structure and as a liquidity buffer to

manage liquidity. Several banks also used external

debt in the form of subordinated loans to bolster

the capital base.

Table 4.14 Share of Restructured Loans to Total Credit


Quality Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

Level 1 1.14% 1.95% 2.42% 2.88% 2.62%

Level 2 0.90% 1.22% 1.56% 1.65% 1.83%

Level 3 0.13% 0.14% 0.25% 0.39% 0.34%

Level 4 0.05% 0.05% 0.13% 0.13% 0.17%

Level 5 0.35% 0.34% 0.48% 0.53% 0.57%

Total 2.54% 3.71% 4.84% 5.59% 5.53%

Graph 4.26 Restructured Loan Developments

Sem I Sem I Sem I Sem I Sem I Sem I Sem ISem II

2011

0

50

150

250

100

200

300 120

%,yoy

100

80

60

40

20

0

Rp T

2012 2013

Value Growth

2014 2015 2016 2017

Sem II Sem II Sem II Sem II Sem II


113BANK INDONESIA





Graph 4.27 Gross NPL Ratio of MSME Loans by Year

3%


4%

4.65%5%

2014 2015 2016 2017

4.59%4.58%

4.10%

Source: Monthly Commercial Bank Reports, 2017, processed

Based on the source, banks sought external debt

from affiliated parties (parent company or within the

same business group) and unaffiliated parties. Based

on maturity, external debt in the banking industry

consisted of short-term debt (≤ 1 year) and long-term

debt (≥ 1 year). Pursuant to prevailing regulations,

banks are only permitted to hold short-term external

debt amounting to 30% of the respective bank’s

capital. Bank regulatory compliance is monitored

daily by Bank Indonesia through the Daily Commercial

Bank Reports.

In the first semester of 2017, total outstanding

external debt in the banking industry stood at

USD29.13 billion, falling 2.03% on the previous

period and accounting for just 17.65% of total

private external debt or 8.69% of total outstanding

external debt in Indonesia. External debt has

contracted in the banking industry since the first

semester of 2015 in line with weak demand for

new loans and adequate liquidity maintained in the

industry.

The largest holders of outstanding external debt

are national private banks with USD16.41 billion

(56.35%), followed by joint venture banks with

USD7.06 billion (24.23%), state-owned banks

with USD4.09 billion (14.06%) and foreign bank

branches with USD1.56 billion (5.36%).

Based on maturity, most external debt in the

banking industry is short term, accounting for

Graph 4.28 Gross NPL Ratio of MSME Loans by Business Scale

4%

2%

6%

1%

5%

3%

7%

Dec-

13

Feb-

14

Apr-1

4

Jun-

14

Aug-

14

Oct

-14

Dec-

14

Feb-

15

Apr-1

5

Jun-

15

Aug-

15

Oct

-15

Dec-

15

Feb-

16

Apr-1

6

Jun-

16

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-1

7

Jun-

17

5.46%

4.79%4.59%

2.94%2.59%

NPL of Micro Enterprises NPL of Small EnterprisesNPL of Medium Enterprises NPL of MSME LoansNPL of Total Credit

Source: Monthly Commercial Bank Reports, 2017, processed

114 BANK INDONESIA


57.04% and worth USD16.61 billion, primarily in

the form of currency and deposits. Nevertheless,

the ratio of short-term external debt to bank capital

is still below the 30% threshold.

In the first semester of 2017, long-term external debt

totalled USD12.51 billion (42.96%), with growth

recorded at 0.03% (yoy). Currency pressures from

maturing external debt were relatively mild, with

most long-term external debt due to mature in 2025,

amounting to USD3.35 billion (28.68%). Meanwhile,

long-term external debt that matured in 2017 stood at

USD2.02 billion (17.3%).

Based on the Bank Business Plan (BBP) submitted

to Bank Indonesia, Indonesia’s banking industry

applied for USD9.88 billion in long-term external

debt in 2017. Of that total, as much as USD3.8

billion had been realised in the first half of the

year. Bank Indonesia has increased its monitoring

of external debt, particularly in the banking sector,

in order to mitigate the associated risks and

encourage the optimal use of external debt to

support development financing.

4.1.5. Bank Profitability, Efficiency and

Capital Profitability

In the first semester of 2017, an increase in ROA

from 2.17% to 2.42% was indicative of improving

bank profitability in general. Against a backdrop of

sluggish credit growth, as the main source of bank

income, the rising ROA stemmed more from efficiency

gains in terms of business activity management, as

reflected by the successful consolidation of non-

performing loans (NPL). All BUKU bank groups

confirmed increases in ROA.

The net interest margin (NIM) fell from 5.47% to

5.21% in the first semester of 2017 due to lower

lending rates, reduced to stimulate credit growth,

Graph 4.29 KUR NPL and NPG

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

9%

5%

7%

3%

8%

4%

6%

2%

1%

0%

3.51%

2.01%

NPG NPL

Graph 4.30 Lending and Deposit Rates

9.0

8.5

8.0

7.5

7.0

6.5

6.0

(%) (%)14

12

10

8

6

4

2

Jan-

10

Jan-

12

Jan-

11

Jan-

13

Jan-

14

Jan-

15

Jan-

16

Apr-1

0

Apr-1

2

Apr-1

1

Apr-1

3

Apr-1

4

Apr-1

5

Apr-1

6

Jul-1

0

Jul-1

2

Jul-1

1

Jul-1

3

Jul-1

4

Jul-1

5

Jul-1

6

Oct

-10

Oct

-12

Oct

-11

Oct

-13

Oct

-14

Oct

-15

Oct

-16

Jan-

16

Apr-1

6

Jun-

16

Spread (rhs)Lending Rates Deposit Rates

Source: Bank Indonesia, Commercial Bank Reports, processed

115BANK INDONESIA





Table 4.15 Deposit Rates by BUKU Bank Group


Rupiah 1-Month Term Deposit Rate (%) Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 8.82 9.03 8.63 8.44 7.63 7.49 7.21

BUKU 2 8.64 8.93 8.37 8.25 7.40 7.23 6.86

BUKU 3 8.48 9.00 8.13 8.00 7.01 6.63 6.27

BUKU 4 7.87 8.06 7.12 6.93 6.26 5.96 5.96

Industry 8.27 85.8 7.78 7.60 6.82 6.46 6.28

Rupiah Demand Deposit Rate (%) Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 2.68 2.30 2.75 3.04 3.14 2.47 2.61

BUKU 2 2.79 2.58 2.73 2.57 2.73 2.46 2.58

BUKU 3 2.48 2.43 2.45 2.35 2.30 2.34 2.31

BUKU 4 1.99 2.00 1.88 1.84 1.83 2.03 1.87

Industry 2.32 2.22 2.25 2.10 2.17 2.18 2.13

Rupiah Savings Deposit Rate (%) Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 3.13 3.07 3.20 3.03 2.86 2.69 2.58

BUKU 2 3.24 3.16 3.05 2.82 2.59 2.15 2.08

BUKU 3 2.55 2.66 3.00 3.04 2.74 2.64 2.46

BUKU 4 1.47 1.41 1.33 1.37 1.22 1.20 1.19

Industry 1.88 1.87 1.85 1.86 1.67 1.59 1.53



Table 4.16 Lending Rates by BUKU Bank Group


Lending Rate on Working Capital Loans (%) Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 17.98 17.96 16.89 16.39 15.43 16.59 13.56

BUKU 2 13.20 14.14 13.77 13.57 13.18 13.27 13.04

BUKU 3 13.05 12.95 12.72 12.62 11.90 11.44 11.07

BUKU 4 12.08 12.21 12.27 11.98 11.31 10.67 10.58

Industry 12.64 12.81 12.71 12.48 11.84 11.38 11.14

Lending Rate on Investment Loans (%) Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 19.72 18.06 17.16 16.63 14.96 14.94 13.78

BUKU 2 13.06 13.52 13.41 13.03 12.76 12.65 12.56

BUKU 3 13.42 13.42 13.35 13.19 12.73 12.22 11.62

BUKU 4 11.17 11.37 11.35 11.27 10.57 10.38 10.33

Industry 12.25 12.36 1.230 12.12 11.49 11.21 11.00

Lending Rate on Consumer Loans (%) Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 13.41 13.31 13.36 13.34 13.86 14.07 13.57

BUKU 2 12.98 13.30 13.34 13.37 13.02 12.92 12.85

BUKU 3 15.24 15.39 15.68 15.53 15.24 14.83 14.18

BUKU 4 11.51 11.95 12.24 12.57 12.84 12.68 12.45

Industry 13.30 13.58 13.82 13.88 13.83 13.59 13.21

116 BANK INDONESIA


which outpaced the reductions to deposit rates.

BUKU 2, 3 and 4 banks reported declines in the NIM

ratio, contrasting BUKU 1 banks.

Net profit after tax in the banking industry soared

from Rp51.92 trillion in the second semester of 2016

to Rp65.66 trillion in the first semester of 2017, with

increases recorded at all BUKU bank groups. Rising

profits stemmed from lower non-interest operating

expenses, primarily in the form of lower provisions for

impairment losses compared to the previous period.

In terms of income, interest operating income

expanded by 4.42% on the previous semester,

originating from placements in securities and

disbursed loans, accounting for 75.3% of total

interest operating income. Interest income from

placements at Bank Indonesia, securities and loans

increased respectively by 16.19%, 7.10% and

0.77% on the previous period. Meanwhile, non-

interest operating income climbed 0.30%, with

spot and derivative transactions confirmed as the

main contributors (rising 53.91%) along with sales

of securities (up 36.38%). The share of both sources

of income accounted for 53.6% of total non-

interest operating income in the reporting period.

Interest operating expenses in the banking industry also

increased, rising 9.20% on the previous period, in line

with faster deposit growth. The share of interest expenses

on deposits dominated the structure of interest operating

expenses, accounting for 48.1%. Meanwhile, the non-

interest operating expenses declined by 6.47% thanks to

bank efforts to reduce overheads, particularly in the form

of provisions for impairment losses. The share of non-

interest operating expenses was dominated by spot and

derivative transactions (25.2%) as well as payroll expenses

(24.4%), while the share of provisions for impairment

losses reduced from a dominant 31.5% to 23.1%.

Efficiency

Banking industry efficiency has improved. The

BOPO efficiency ratio improved from 82.85% to

79.48% in the reporting period, affecting all BUKU

groups as the banks successfully reduced overheads

through lower provisions for impairment losses.

Another efficiency indicator, namely the cost-to-

income ratio (CIR), which is calculated as the ratio

of non-interest operating expenses (excluding

provisions for impairment losses) to income ticked

upwards from 55.53% to 57.85% in the first

semester of 2017. The improvement stemmed from

Graph 4.31 Total NOP and NOP Ratio by Bank Group

8

4

6

2

0

7

3

5

1

-1 BUKU 4BUKU 2 BUKU 3BUKU 1

NOP RatioTotal NOP by Bank Group in Semester I 2017

BUKU 4 Industry

BUKU 2 BUKU 3BUKU 1

5%

3%

4%

2%

1%

4%

2%

3%

1%

0%

Dec-

11

Dec-

12

Dec-

14

Dec-

16

Dec-

13

Dec-

15

Jun-

12

Jun-

14

Jun-

16

Jun-

13

Jun-

15

Jun-

17

Source: Bank Indonesia, Commercial Bank Reports, 2017, processed

Rp T

117BANK INDONESIA





relatively larger increases in interest and non-interest

operating expenses compared to non-operating

income, in addition to the declines reported in terms

of net interest income and non-interest operating

income.

The disparate trends of the cost-to-income ratio (CIR)

and BOPO efficiency ratio demonstrated the strong

influence provisions for impairment losses have on

bank efficiency. The efficiency gains achieved in the

reporting period were caused by bank propensity

to form large provisions for impairment losses in

the previous semester, leading to comparatively

lower provisions for impairment losses in the first

semester of 2017.

Capital

The banking industry maintained adequate capital.

The Capital Adequacy Ratio (CAR) was recorded

well above the 8% threshold at 22.52% in the first

semester of 2017, down slightly from 22.69% on

increasing lending, particularly to the corporate

services and construction sectors as well as through

consumer loans, which raised the level of risk-

weighted assets (RWA) in the banking industry.

The current level of CAR denotes that the banking

industry in Indonesia has already fulfilled its Basel III

commitments in the form of the capital conservation

buffer, countercyclical buffer and capital surcharge

for systemically important banks (SIB), which have

been effective since the beginning of 2016. The

composition of bank capital was dominated in the

reporting period by core capital (Tier 1), accounting

for 92.12%, down slightly from 92.16% in the

previous semester.

4.1.6. Banking Stress Tests

Stress tests were conducted to gauge the resilience

of bank capital (CAR) as an industry and by BUKU

bank group using macroeconomic scenarios

transmitted through credit risk and market risk

(interest rates, exchange rates and SBN prices) to

balance sheet data and bank performance as of

June 2017. Departing from previous stress tests,

the scenarios applied in the first semester of

2017 consisted of: 1) baseline (BL); 2) severe; and

3) prolonged slow growth (PSG). Based on those

three scenarios, banking industry dynamics through

to 2019 were shown to be adequately resilient

in response to the various economic shocks and

distress that could occur.

Graph 4.32 SBN Yield Volatility

10

6

8

4

9

5

7

Sem II 2014 Sem I 2016Sem I 2015 Sem I 2017Sem II 2015 Sem II 2016


1 6 11 16 21 26 31 4136 46 51 56 61 66 71 76 81 86 91 96 101 106 111 116 121 126

118 BANK INDONESIA


Table 4.17 Value of SBN Holdings by Bank Group


Trading SBN (Rp, trillions) Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 0.10 0.03 0.23 0.26 0.02 0.04 0.20

BUKU 2 9.68 12.16 7.84 13.51 12.01 4.66 6.89

BUKU 3 17.18 11.32 15.93 17.31 21.74 24.05 20.26

BUKU 4 1.97 2.39 3.61 2.62 2.47 2.57 12.21

Industry 28.93 25.90 27.62 33.70 36.23 31.33 39.57

AFS SBN (Rp, trillions Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 1.01 1.13 1.17 1.21 0.88 0.57 0.42

BUKU 2 18.60 19.09 25.44 27.92 27.51 17.44 20.93

BUKU 3 51.11 56.35 67.67 79.62 84.36 115.61 93.64

BUKU 4 123.26 123.14 96.44 110.74 126.21 138.78 156.07

Industry 193.98 199.71 190.73 219.50 238.96 272.40 271.07

HTM SBN (Rp, trillions) Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 1.99 2.35 2.58 2.67 2.64 1.07 1.09

BUKU 2 14.06 15.49 18.79 23.61 29.29 18.54 21.41

BUKU 3 14.24 18.25 21.47 30.97 28.55 44.96 45.66

BUKU 4 55.00 59.56 54.32 66.79 73.88 82.97 79.52

Industry 85.28 95.65 97.16 124.05 134.37 147.54 147.67

Table 4.18 Share of SBN Holdings by Bank Group


BUKU 4 Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

Trading 1.09 1.29 2.34 1.46 1.22 1.15 4.93

AFS 68.39 66.53 62.47 61.47 62.31 61.87 62.98

HTM 30.51 32.18 35.19 37.07 36.47 36.99 32.09


Trading 20.82 13.17 15.16 13.53 16.14 13.03 12.70

AFS 61.93 65.59 64.40 62.25 62.65 62.62 58.69

HTM 17.25 21.24 20.44 24.22 21.21 24.35 28.61


Trading 22.87 26.02 15.06 20.77 17.45 11.48 14.00

AFS 43.93 40.84 48.86 42.93 39.98 42.91 42.51

HTM 33.20 33.14 36.08 36.30 42.57 45.61 43.49


Trading 3.09 0.83 5.87 6.34 0.58 2.48 11.80

AFS 32.56 32.16 29.44 29.28 24.95 33.85 24.53

HTM 64.35 67.01 64.69 64.38 74.46 63.66 63.67

Industry Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

Trading 9.39 8.06 8.75 8.93 8.85 6.94 8.63

AFS 62.94 62.16 60.45 58.18 58.35 60.36 59.15

HTM 27.67 29.77 30.80 32.88 32.81 32.69 32.22

119BANK INDONESIA





Macroeconomic Scenarios

Calculating the stress tests begins with setting the

scenarios. When preparing the stress scenarios,

the sources of risk must be known, including

domestic sources, such as rising fuel prices and

deteriorating corporate performance, as well as the

external sources, including lower commodity prices

and economic moderation in China that could

threaten the banking system. The sources of risk

will influence macroeconomic and financial system

stability and would ultimately be transmitted to the

banking system though the banks’ balance sheets

in the form of credit and currency risks as well as

SBN prices. After considering all forms of domestic

and external risk that could undermine banking

system performance, three types of stress scenarios

were formulated as mentioned previously.

350

USD, billions

12.0

% yoy

4.0

8.0

0.0

10.0

2.0

6.0

250

150

50

300

200

100

-Sem I Sem I Sem I* Sem I**Sem II Sem II Sem II**

2014

Total External Debt External debt Growth (rhs)

2015 2016 2017

Graph 4.33 External Debt in Indonesia Graph 4.34 Government and Private External Debt

Sem I

Government and Central Bank Growth of Government and Central Bank (rhs)

Private Growth of Private (rhs)

Sem I Sem I* Sem I**Sem II Sem II Sem II**

2014 2015 2016 2017

200 20.0

10.0

0.0

-20.0

-10.0

100

150

50

-

USD, billions

Source: Statistics Department, Bank Indonesia

Graph 4.35 Share of Private External Debt

Graph 4.36 External Debt Growth in the Banking Industry

100%

81.9 80.6 81.6 81.0 82.2 81.5 82.3

18.1 19.4 18.4 19.0 17.8 18.5 17.45

80%

40%

60%

20%

0%

Bank Nonbanks

Sem I Sem I Sem I* Sem I**Sem II Sem II Sem II**

2014 2015 2016 2017

* Preliminary Data ** Projected Data


35,000

USD, billions %, yoy

25,000

15,000

5,000

30,000

20,000

10,000

-

35.0

25.0

15.0

5.0

0.0

-5.0

-10.0

30.0

20.0

10.0

Sem I Sem I Sem I* Sem I**Sem II Sem II Sem II**

2014

Bank Growth (rhs)

2015 2016 2017


120 BANK INDONESIA


Graph 4.37 External Debt by Bank Type Graph 4.38 External Debt Maturity

Smt I Smt I Smt I* Smt I*Smt II Smt II Smt II*2014 2015 2016 2017

18,000

USD, billions

14,000

10,000

6,000

16,000

12,000

8,000

4,000

2,000-

State-owned Bank Private Foreign Private Joint Venture Private National

Smt I Smt I Smt I* Smt I*Smt II Smt II Smt II*2014 2015 2016 2017

100%

80%

40%

60%

20%

0%

34% 37% 37% 43% 42% 41% 43%

66% 63% 63% 57% 58% 59% 57%

Short Term Long Term

The baseline (BL) scenario is the preliminary

projection assuming no distress in the economy and

financial system. Therefore, this scenario assumes

economic growth, prices and the exchange rate are

stable. The BL scenario is used as a benchmark of

banking system dynamics for the other stress tests.

According to the severe scenario, a deep economic

contraction is assumed, including a financial crisis

occurring in one of Indonesia’s major trading

partners, the end of rising commodity prices and

a significant Federal Funds Rate (FFR) hike that

triggers a sudden capital reversal. Such inauspicious

pressures would depress GDP growth in Indonesia

significantly. On the other hand, an FFR hike in

the United States would also create substantial

market disruptions that would manifest as rupiah

depreciation and falling securities prices.

The prolonged slow growth (PSG) scenario assumes

a gradual but moderate global economic downturn,

precipitated by weaker-than-expected economic

growth in Indonesia’s major trading partners,

coupled with an FFR hike beyond expectations.

Graph 4.39 Ratio of Short-Term External Debt to Capi-tal in the Banking Industry

Source: Daily Commercial Bank Reports

Sem I

6,42

30

%

25

20

15

10

5

0

7,35 6,36 6,66 6,40 6,155,26

Sem I Sem I Sem ISem II Sem II Sem II

2014 2015 2016 2017

Ratio of Short-Term External Debt to Capital Threshold



121BANK INDONESIA





Graph 4.40 Maturity Profile of Long-Term External Debt in the Banking Industry

2026

Year

25.0

15.2

467.1

80.0

535.3

1,644.4

933.6

2,601.2

2,021.9

2,000- 4,000

3,346.7

2024

2020

2022

2018

2025

2023

2019

2021

2017

Graph 4.41 Maturity Composition of Long-Term External Debt in the Banking Industry

Source: External Debt Information System (SIUL), June 2017

Position as of June 2017 Position as of June 2017

28.7%

2018

2017

2020

2019

2021

2023

2022

2026

2024

2025

14.1%

17.3%

22.3%

8.0%

4.6%4.0%

0.7%

0.2%0.1%

Such distress would destabilise domestic growth

and trigger shocks in the foreign exchange and

securities markets due to capital outflows.

The scenarios were calculated using structural models

that can detect the interactions between domestic

and external sources of distress. Such models

generated projections of various macroeconomic

variables, including GDP growth, inflation and

exchange rates up to three years into the future.

The variables represent the main components of the

transmission of distress to the banking system.

Transmission of Credit Risk

Using NPL as a proxy of credit risk, the stress tests

aimed to measure CAR resilience in the banking

industry against a spike in the gross NPL ratio, which

would increase provisions for impairment losses and

ultimately erode bank profitability and, thus, capital

growth, leading to a lower Capital Adequacy Ratio

(CAR).

Based on the simulations, the BL scenario

demonstrated that the gross NPL ratio of the banking

industry would remain stable and well below the 5%

threshold through to the end of 2019 consistent with

stable economic dynamics. According to the sever

scenario, however, the gross NPL ratio of the banking

industry could potentially increase to 8.05% at the

end of 2019 in line with the severe distress in the

economy. Furthermore, the higher NPL ratio would

increase the provisions for impairment losses and

impair profits that could ultimately slow the rising

Capital Adequacy Ratio (CAR). Meanwhile, based

on the PSG scenario, the NPL ratio of the banking

industry would increase to 2.68% at the end of 2018

and then to 4.62% at the end of 2019 in line with

gradual economic moderation.

Transmission of SBN Price Risk

SBN price risk is transmitted through the SBN portfolio

channel on the asset side of the bank balance sheet.

The available for sale (AFS) and trading SBN portfolios

faced the most pressure because of mark-to-market

(M2M) pricing. Lower SBN prices in both categories

were calculated based on yield, which increased or

decreased according to the scenario. SBN prices that

have already experienced distress were calculated

USD, billions

122 BANK INDONESIA


1.5

0.5

2.5

3.5

0.0

Sem I - 14 Sem I - 14 Sem I - 16 Sem I - 16 Sem I - 15 Sem I - 15 Sem I - 17 Sem I - 17Sem II - 14 Sem II - 14 Sem II - 16 Sem II - 16 Sem II - 15 Sem II - 15

2.172.42

2.0%

1.0

3.0

4.0

Graph 4.42 ROA by BUKU Bank Group Graph 4.43 NIM by BUKU Bank Group

2

0

4

65.21

3

1

5

%

*) Banks are classified based on OJK BUKU groups as of June 2017Source: Bank Indonesia, Commercial Bank Reports, processed

Table 4.19 Banking Industry Profit/Loss (Rp, trillions)

BUKU

Pre-Tax Profit Post-Tax Profit

2014 2015 2016 2017 2014 2015 2016 2017

I II I II I II I I II I II I II I

BUKU 1 0.87 0.46 0.77 0.72 0.75 0.22 1.24 0.68 0.08 0.63 0.45 0.50 (0.11) 0.92

BUKU 2 7.38 6.15 5.99 6.84 7.95 6.36 8.06 6.01 4.13 4.71 5.17 6.20 4.60 6.44

BUKU 3 21.07 16.97 17.21 11.86 19.12 12.67 23.79 16.72 12.90 12.96 8.77 14.71 9.29 18.15

BUKU 4 44.15 46.52 40.42 49.62 42.06 48.33 49.76 35.02 36.62 32.55 39.45 33.22 38.15 40.14

Industry 73.47 70.11 64.39 69.04 69.89 67.58 82.85 58.43 53.72 50.84 53.83 54.62 51.92 65.66

using the discounted cash flows (DCF) approach.

More intense pressures, based on the macroeconomic

scenario, would lead to higher yields of greater

magnitude and, therefore, lower SBN prices, which

incur a cost to correct asset prices in the banks’ profit

& loss report that would impede additional capital

growth and lower the Capital Adequacy Ratio (CAR).

Transmission of Currency Risk

Bank exposure to rupiah exchange rates occurs

through the net open position (NOP), on-balance

sheet and off-balance sheet. According to the BL

scenario, the exchange rate is stable in line with

solid macroeconomic fundamentals. Based on the

severe scenario, the exchange rate would depreciate


Table 4.20 Breakdown of Income (Rp, trillions)

Income Position2014 2015 2016 2017 Increase

/Decrease ShareI II I II I II I

Interest Operating Income 268.96 299.03 316.32 329.82 339.06 342.40 357.52 4.42% 100%

Placements at Bank Indonesia 3.27 4.55 3.99 3.63 2.97 3.02 3.51 16.19% 1.0%

Securities 17.32 19.89 22.06 20.68 25.58 26.82 28.73 7.10% 8.0%

Loans 193.30 210.60 219.53 231.10 235.89 238.81 240.65 0.77% 67.3%

Non-Interest Operating Income 80.22 68.21 93.94 116.90 129.11 119.74 120.11 0.30% 100%

Sales of Securities 3.24 3.07 3.40 2.19 4.75 4.13 5.63 36.38% 4.7%

Trading (Spot and Derivatives) 30.94 19.81 39.72 67.96 63.15 38.17 58.74 53.91% 48.9%

Dividends, Commissions/Provisions/Fees 26.67 27.54 28.77 29.09 30.66 32.32 33.35 3.16% 27.8%

Correction to Provisions for Impairment Losses 13.38 9.61 15.79 8.13 23.05 22.45 12.99 -42.14% 10.8%

Non-Operating Income 12.82 12.41 12.15 11.93 7.86 12.86 17.38 35.23% 100%



BUKU 4BUKU 4 IndustryIndustry BUKU 2BUKU 2 BUKU 3BUKU 3 BUKU 1BUKU 1



123BANK INDONESIA






Table 4.21 Breakdown of Expenses (Rp, trillions)

Expense Positions2014 2015 2016 2017 Increase

/Decrease ShareI II I II I II I

Interest Operating Expenses 136.06 157.78 168.99 169.02 172.46 166.17 181.45 9.20% 100%

To Other Banks 2.24 2.37 2.96 3.52 3.57 3.36 3.80 13.25% 2.1%

To a Third Party (nonbank) 79.56 93.37 94.76 92.31 89.31 85.67 87.34 1.96% 48.1%

Securities 3.51 3.49 3.92 4.04 3.83 4.39 4.69 6.66% 2.6%

Loans Received 1.76 1.75 1.91 2.43 3.44 2.89 3.47 20.06% 1.9%

Non-Interest Operating Expenses 138.92 139.92 177.46 208.41 226.98 229.24 214.40 -6.47% 100%

Losses on Securities 1.66 0.92 1.39 1.46 0.75 1.73 0.75 -56.58% 0.3%

Spot and Derivatives 27.18 16.70 35.92 62.19 57.46 44.33 53.95 21.70% 25.2%

Insurance Premiums 4.76 5.13 5.82 6.11 6.50 6.19 6.54 5.72% 3.1%

Provisions for Impairment Losses 27.38 27.70 44.44 42.22 63.08 72.18 49.50 -31.42% 23.1%

Payroll 39.62 41.13 45.20 44.08 50.05 48.19 52.21 8.36% 24.4%

Non-Operating Expenses 13.56 11.83 11.57 12.18 6.70 12.86 16.75 30.27% 100%

sharply in 2018 by 49.3% (yoy), reaching its nadir

in 2019. Meanwhile, the PSG scenario assumed

gradual depreciation until the end of 2019. In

the case of deep rupiah depreciation, the banks

maintaining a net-long position would benefit from

the difference in rates. Conversely, the banks with a

net-short position would incur corresponding losses

that could influence CAR.

Transmission of Interest Rate Risk

Bank exposure to the risk of higher interest rates is

measured by the exposure to short-term (< 1 year)

rupiah liabilities and net claims, which are considered

more sensitive to interest rate fluctuations. The

baseline scenario assumed stable interest rates with

no detriment to the balance sheet. According to the

severe scenario, interest rates would rise 800bps in

2018 and by 340bps in 2019, totalling 1140bps over

two years. Based on the PSG scenario, interest rates

would increase 415bps in the first year and by 505bps

in the second, totalling 920bps over two years. Banks

with a positive gap (claims larger than liabilities) in

the balance sheet would benefit from higher interest

rates. In contrast, banks with a negative gap (claims

smaller than liabilities) would incur losses from higher

interest rates that could undermine CAR.

Aggregated Stress Test Results

The magnitudes of each shock and respective

types of risk were aggregated in order to produce

integrated stress test results. Through dynamic

stress test scenarios, the impact of each shock on

the banking system could be calculated periodically

through to the end of 2019. In general, the stress

tests indicated that the banking industry would

maintain a solid capital base, as reflected by a Capital

Adequacy Ratio (CAR) above the 8% threshold at

the end of the second semester of 2019 for each

scenario.

Credit risk dominated each scenario, explaining

an average of 87.3% of the capital shortfall based

on the severe scenario and 80.59% according to

the PSG scenario. At the end of 2019, the capital

shortfall of the severe scenario was predicted to

reach Rp198.75 trillion.

Stress Test Results by BUKU Bank Group

Based on the severe scenario, all BUKU bank groups

maintained a Capital Adequacy Ratio (CAR) above

the 8% threshold at the end of 2019. The most

affected, however, were the BUKU 2 banks, with

the respective CAR declining by 12.13% to 10.05%,

124 BANK INDONESIA


Graph 4.45 Cost-to-Income Ratio (CIR) by BUKU Bank Group (%)

Graph 4.44 BOPO Efficiency Ratio by BUKU Bank Group (%)

10

50

30

70

90

20

60

40

80

100

%





57.85

10

50

30

70

90

20

60

40

80

100

%

and BUKU 3 banks, decreasing 10.49% to 13.16%.

Furthermore, BUKU 2 banks recorded the lowest CAR

after experiencing the shocks. In general, though,

solid bank resilience was maintained. Individually,

several small banks required a capital injection,

especially if the economic slowdown persisted.

Based on the PSG scenario, the stress tests showed

that all BUKU bank groups would maintain a

Capital Adequacy Ratio (CAR) in excess of the

8% threshold in the face of significant economic

distress. At the peak of the distress, at the end of

2019, BUKU 2 banks would experience the largest

decline in CAR, falling 8.09% to 14.09%, along

with BUKU 3 banks, decreasing 7.03% to 16.62%.

Furthermore, BUKU 2 banks recorded the lowest

CAR after the shocks. Nevertheless, stress testing

the PSG scenario showed that all BUKU groups

would maintain a solid capital base in the face of

significant economic distress.

6,000 22.52

4,000

5,000

Rp (T

)

3,000

2,000

1,000

23

21

22

20 %

19

18

17

Capital Risk-Weighted Assets CAR

Graph 4.46 Banking Industry CAR (%) Graph 4.47 Tier 1 Ratio in the Banking Industry (%)

Source: Banking Information System (SIP), processed Source: Banking Information System (SIP), processed

25

21

23

19

%

17

15

22.52

20.75

CAR Tier 1

79.48

Sem I - 14 Sem I - 14 Sem I - 16 Sem I - 16 Sem I - 15 Sem I - 15 Sem I - 17 Sem I - 17Sem II - 14 Sem II - 14 Sem II - 16 Sem II - 16 Sem II - 15 Sem II - 15

Sem I - 14 Sem I - 16 Sem I - 15 Sem I - 17Sem II - 14 Sem II - 16 Sem II - 15 Sem I - 14 Sem I - 16 Sem I - 15 Sem I - 17Sem II - 14 Sem II - 16 Sem II - 15

BUKU 4BUKU 4 IndustryIndustry BUKU 2BUKU 2 BUKU 3BUKU 3 BUKU 1BUKU 1

125BANK INDONESIA





Notes: Semester I 2017 data is based on BUKU bank groups as of June 2017

Table 4.22 CAR Performance by BUKU Bank Group

Source: Banking Information System (SIP), processed

%

Highest CAR Lowest CAR Average CAR CAR

2015 2016 2017 2015 2016 2017 2015 2016 2017 2015 2016 2017

I II I II I* I II I II I* I II I II I* I II I II I*

BUKU 1 145.53 142.94 116.85 123.45 94.33 10.02 8.98 11.29 13.05 11.33 25.28 29.42 24.70 27.58 29.60 19.86 23.24 20.87 21.86 22.85

BUKU 2 61.48 121.23 138.42 119.80 107.42 12.11 14.67 11.65 11.76 12.37 22.53 26.23 28.22 26.97 25.92 19.96 22.40 22.35 22.83 22.27

BUKU 3 77.04 80.56 84.09 85.16 77.84 13.56 14.20 11.98 12.54 14.36 21.56 22.76 23.79 24.66 24.37 22.35 23.50 24.58 24.49 25.13

BUKU 4 20.16 20.16 21.79 22.64 22.52 17.23 18.61 19.26 18.12 18.23 18.66 19.29 20.89 21.02 20.68 18.78 19.26 21.06 21.24 20.88

Industry 20.28 21.39 22.56 22.69 22.52

Credit risk continued to dominate nearly all BUKU

groups based on the severe and PSG scenarios,

demonstrating that credit risk remains the primary

source of risk in the banking system. Therefore,

prudent credit risk mitigation would enhance bank

resilience under stress conditions.

Graph 4.48 Credit Risk (NPL) Scenarios

9

2.60 2.60 2.60 2.562.81 2.68

2.53

8.05

4.62

%

2017

Baseline Severe PSG

2018 2019

5

7

3

0

8

4

6

2

1


Graph 4.49 SBN Yield Scenarios

9

10

5

7

3

87.00 7.00 7.00 7.00 7.00

8.00 8.00

9.00 9.00

4

6

2

1

02017 2018 2019

Baseline Severe PSG


126 BANK INDONESIA


2017 2018 2019

60% yoy

20

40

0

50

10

30

-10

2.25 2.25 2.25 -0.07

49.29

21.16

0.00

6.72

22.13

Graph 4.50 Currency Depreciation Risk Scenarios

Baseline Severe PSG


Sem II 2017 Sem II 2018 Sem II 2019

20%

12

16

8

4

18

10

14

6 6 6 6 6

14

10

17

15

6

2

0

Graph 4.51 Currency Risk Scenarios

Baseline Severe PSG

Graph 4.52 Aggregate Stress Test Results

2017 2018 2019

25.0 22.82 22.79 22.6922.6

19.2

13.0

22.620.5

16.415.0

5.0

20.0

10.0

0.0

Capital Adequacy Ratio (CAR) – All Scenarios

CAR

(%)

Baseline Severe PSG



127BANK INDONESIA





Graph 4.53 Share of Capital Shortfall in the Banking Industry (Aggregate)

%

90100

50

70

30

80

40

60

2010

Severe

Credit Risk Securities Holding Risk

PSG0

87.23 80.59

12.77 19.41

Graph 4.54 Stress Test Results by BUKU Group (Severe Scenario)

2017

BUKU 4 BUKU 2BUKU 3 BUKU 1

2018 2019

25.0

15.0

5.0

20.0

10.0

0.0


21.90

19.35

13.88

23.65

19.78

13.16

22.18

17.84

10.05

21.90

17.95

13.75

CAR

(%)



Graph 4.55 Stress Test Results by BUKU Group (PSG Scenario)

2017 2018 2019

25.0

15.0

5.0

20.0

10.0

0.0


21.9020.36

17.00

23.65

21.20

16.62

22.18

19.26

14.09

21.90

19.45

15.60

CAR

(%)


BUKU 4 BUKU 2BUKU 3 BUKU 1

128 BANK INDONESIA


4.2. Nonbank Financial Industry

In the first semester of 2017, the nonbank financial

industry4, specifically finance companies and

insurance companies, performed soundly.

The performance gains by finance companies

were observed in terms of financing and funding.

Funding was bolstered by foreign loans and

financing increased to the trade sector as well as

leasing services, labour and travel. Nevertheless,

non-performing financing (NPF) also increased

slightly, which eroded profitability in terms of a

lower ROA compared to conditions in the previous

period. A smaller portion of external debt in the

funding structure of finance companies reduced

exposure to currency risk.

Asset and investment growth were indicative of

stronger performance in the insurance industry. All

types of insurance achieved asset and investment

growth, particularly social insurance and life

insurance. Meanwhile, the ratio of premiums to

claims moderated slightly on the previous period.

Nonetheless, liquidity risk was contained, as

reflected by a ratio of current assets5 to current

liabilities6 of >1. Profitability was also maintained,

indicated by modest increases in the ROA and

ROE.

The first semester of 2017 saw interconnectedness

between the banking industry and finance

companies increase, primarily due to a surge

of bank loans disbursed to finance companies.

Furthermore, bank interconnectedness with the

insurance industry also increased as insurance

companies were more inclined to place their funds

and securities in the banking system.

4.2.1. Finance Companies

In the first semester of 2017, the assets of finance

companies expanded by 6.45% (yoy), up from

3.99% (yoy) in the second semester of 2016.

Financing also experienced growth, accelerating

from 6.89% (yoy) to 8.85% (yoy) over the same

period. On a semesterly basis, financing growth

stood at 4.64%. The main driver of growth was

financing extended to the trade sector (63.49%,

ytd), followed by leasing services, labour and travel

(57.72%, ytd) as well as the manufacturing industry

(17.38%, ytd). By business sector, the trade sector

dominated the financing disbursed by finance

companies, accounting for 15.59%, followed by

the household sector (13.92%) and the others

sector (10.99%), primarily in the form of automotive

financing.

Based on business activity7, finance company

financing was dominated by multipurpose

financing, accounting for 58.38% of total

financing, followed by investment financing

(27.38%), sharia-compliant financing (8.38%)

and working capital financing (5.82%).

By currency, rupiah-denominated financing

continued to dominate, with growth accelerating

to 16.42% (yoy) and totalling Rp378 trillion in

the reporting period, up from 13.75% (yoy) in

the second semester of 2016 and 3.15% (yoy)

in the same period one year earlier. In contrast,

foreign currency financing continued to track

a declining trend, totalling Rp42 trillion and

contracting by -12.84% (yoy). The contraction

has endured since the second semester of

4 The nonbank financial institutions discussed are finance and insurance companies.5 Current assets = Total Assets – Strata Title Buildings and Land in Use – Other Fixed Assets – Other Assets.6 Current Liabilities = Total Liabilities.

129BANK INDONESIA





Graph 4.56 Finance Company Assets and Financing

50

Dec-14 Dec-15 Dec-16Jun-15 Jun-16 Jun-17

-

250

150

350

450

100

300

200

400

420 430 426 434 443462

366 370 363 373 388406

500

(Rp T)

Assets Financing

Graph 4.57 Finance Company Financing by Business Activity

Corporate Leasing FactoringConsumer FinancingWorking Capital FinancingOther OJK-Approved Financing

Investment FinancingCredit Cards

Multipurpose FinancingSharia-Compliant Financing

500

(Rp.T)

400

300 246 249 247 261 230 237

3134

111 111 105 100 105 111

9 10 11 11 21 24

100

200


Source: Financial Services Authority (OJK) Source: Financial Services Authority (OJK)

2014 due to dwindling demand from the heavy

equipment subsector in line with sluggish mining

sector performance.

Congruent with subdued economic growth, credit

risk at finance companies tended to escalate, as

reflected by a deterioration in the non-performing

financing (NPF) ratio from 3.26% to 3.47%. The NPF

ratio was most severe in the transportation sector

in line with weak mining sector performance. Most

financing objects in the transportation sector were

used to finance ships and trucks for transporting

mining commodities.8

In general, simulations9 conducted by Bank

Indonesia showed that finance company profits

could absorb an increase in NPF to a level of 4.73%.

Therefore, any potential deterioration of non-

performing financing (NPF) at finance companies

demands increased vigilance, especially if the

national economy remains sluggish.

In the first semester of 2017, the total funding of

finance companies stood at Rp337 trillion, with

growth accelerating from 4.29% (yoy) to 6.11%

(yoy). The main source of funds was still domestic

loans, typically from the banking industry, amounting

to Rp169.9 trillion or 45.06% of the total. The use

of domestic loans expanded by 15.67% (yoy) in the

reporting period as the banks continued to lower

lending rates. In the first semester of 2017, 47.52%

of bank loans were disbursed to finance companies

with a lending rate of below 10%, increasing

markedly from 27.38% in the previous period.

Consistent with the surge in funding from domestic

loans, funding from external debt declined. In the

first semester of 2017, funding from external debt

decreased by 11.22% (yoy), not therefore as deep

as the 22.82% posted in the second semester of

2016. Notwithstanding the decline, the portion of

funding from external debt remained relatively high

at 22.45%, totalling Rp84.7 trillion.

7 Pursuant to OJK Regulation (POJK) No. 29/POJK.05/2014 concerning the Business Activities of Finance Companies, the business activities of finance companies consist of investment financing,

working capital financing, multipurpose financing, sharia-compliant financing and other financing based on OJK approval. Previously, the types of financing were limited to corporate leasing,

factoring, credit cards and consumer financing.8 The increase in NPF was also attributable to the reclassification of financing collectability through the implementation of OJK Regulation (POJK) No. 29/POJK.05/2014 concerning the Business

Activities of Finance Companies, which expanded the collectability classifications from three (current, doubtful and loss) to five (current, special mention, substandard, doubtful and loss).9 The simulations used P&L data as of December 2016 with the following assumptions:

- All loans with a collectability classification of 2 (special mention) were downgraded to 3 (substandard); and

- If the profit was not zero, loans with a collectability classification of 3 were downgraded to 4 (doubtful) and loans with a collectability classification of 4 were downgraded to 5 (loss).

130 BANK INDONESIA


10 ???

Seeking to mitigate currency risk, finance companies

indebted with foreign loans and with most financing

disbursed in rupiah hedged their external debt. That

strategy reduced potential currency risk and foreign

loan defaults. For finance companies partially owned

by a bank with a ≥25% stake, hedging was used to

mitigate the contagion effect on the parent bank.

In the reporting period, 42 finance companies

held outstanding external debt valued at Rp84.66

trillion. Of the total, eight finance companies were

partially owned by a bank with a ≥25% stake

and the total outstanding external debt stood at

Rp25.79 trillion, which exposed the parent bank

Graph 4.58. Financing by Types of Forex

50

-

250

150

350

450

(Rp.T)

Rupiah Current Exchange

100

300

200

400

55 55 52 4947

42

311 314 311 324 354378


Sumber : Otoritas Jasa Keuangan

Graph 4.59. Ratio of NPF PP (%)

1.5

0.5

NPF (%)

Mar

-13

Jun-

13

Sep-

13

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

0

2.5

3.5

2

1

2.20

3.26

3.47

3

4

%

Sumber: Sumber : Otoritas Jasa Keuangan

to currency risk considering that most financing

was disbursed in rupiah, totalling Rp91.4 trillion,

while foreign currency financing only amounted to

Rp1.82 trillion.

Of the finance companies indebted with foreign

loans and highly exposed to currency risk, a total of

36 firms also recorded net foreign liabilities (NFL)10.

Stress testing currency depreciation against the

capital of those 36 finance companies, assuming

the rupiah slumped to Rp20,000/USD, showed that

capital resilience was maintained at all 36 finance

companies, while 12 finance companies would

experience negative equity.

131BANK INDONESIA





The efficiency of finance companies has improved

slightly, as indicated by a dip in the BOPO efficiency

ratio to 82.24% in the first semester of 2017 from

82.77% in the previous period and from 82.71% in

the same period one year earlier. The efficiency gains

have not been reflected in the profitability ratios,

however, which decreased on the previous period due

to high non-operating costs. Accordingly, the ROA fell

from 3.87% to 3.83% and the ROE from 12.01% to

11.49% in the reporting period.

The interconnectedness between finance

companies and the banking industry has increased

due to a surge of loans disbursed by the banks to

finance companies, accelerating from 20.31% (yoy)

to 20.42% (yoy) in the reporting period. On the

other hand, finance companies were less inclined to

place their funds in the banking industry (demand

deposits, savings deposits and term deposits),

with growth contracting by 10.98% after posting

positive 9.93% in the second semester of 2016.

Graph 4.60 Financing and Funding Growth

20

%

15

10

-

(5)

Total Funding Total Financing

5

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

8.95

6.11

Graph 4.61 Sources of Funds

400345 351 346 355 361

377

(Rp.T)

300

100

-

200

Domestic Loans

Total FundingIssued Securities

Foreign Loans Capital

Dec-14 Jun-15 Jun-16 Jun-17Dec-15 Dec-16

37 39 40 47 4851

53 56 61 67 7072

114 121 107 95 8385

141 136 138 147 160170


Graph 4.62 Market Share of Finance Company Borrowings based on Lending Rates

0%-10% > 12%10.01%-12%

60

%

50

40

20

47.52

33.66

18.81

10

30

Jun-

13

Sep-

13

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

132 BANK INDONESIA


4.2.2. Insurance Companies

The insurance industry achieved slower gains in

the first semester of 2017 compared to conditions

in the previous period. Nonetheless, the insurance

industry posted stronger assets and investment.

The total assets of the insurance industry reached

Rp1,012 trillion, with growth decelerating from

17.53% in the second semester of 2016 to 16.09%

(yoy) in the reporting period. The controlling

shareholders of most insurance companies are

private nationals, with 146 companies offering

the gamut of life insurance, general insurance

and reinsurance, social insurance and compulsory

insurance. The total assets were dominated in the

first semester of 2017 by life insurance, accounting

for 42.95%, followed by social insurance (30.91%),

general insurance and reinsurance (13.86%) as

well as compulsory insurance (12.28%).

Investment grew at 20.51% (yoy) in the first

semester of 2017, down from 21.70% (yoy) in

the previous period. Consequently, the ratio of

investment to assets increased from 82.62% to

83.97%.

The insurance industry placed most assets in

financial instruments, dominated by tradeable

government securities (SBN) totalling Rp240.03

trillion (28.24%), followed by stocks totalling

Rp181.30 trillion (21.33%) and mutual funds

totalling Rp150.54 trillion (17.71%). The insurance

industry bolstered SBN holdings during the first half

of the year to meet prevailing OJK regulations11.

Although asset and investment growth slowed

compared to conditions in the previous period, the

profitability of the insurance industry increased. The

developments were explained by increases in the

ROA and ROE from 3.21% and 11.02% to 3.61%

and 12.48% respectively.

Business risk in the insurance industry increased in the

reporting period, with a decline in the ratio of premiums

to claims from 157.99% in the second semester of

2016 to 147.31% in the first semester of 2017. The

build-up of risk affected all types of insurance, except

General Insurance and Reinsurance due to a decrease

of claims that exceeded the decline of income from

premiums. Meanwhile, liquidity risk in the insurance

Graph 4.63 External Debt at Finance Companies

15

1023.86

(11.22)

5

(10)

0

(20)

(30)

25

30

35

20

20

10

-

30

40

% %

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

Share of External Debt to total Liabilities (%) External Debt Growth (yoy) (rhs)

11 OJK Regulation (POJK) No. 1/POJK.05/2016, dated 11th January 2016, concerning SBN Investments.

133BANK INDONESIA






Graph 4.64 ROA, ROE and BOPO Efficiency Ratio of Finance Companies

6 78

2 74

- 72

10 82

14 86

8 80

4 76

12 84

16 88

ROA ROE BOPO (rhs)

%%

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

Table 4.23 Interconnectedness between the Banking Industry and Finance Companies

Source: Monthly Commercial Bank Reports

Component Dec-15 Jun-16 Dec-16 Jun-17 ∆ Term Deposits % Demand Deposits

Investment (Rp, billions) 25,827 25,411 22,518 21,719 (3,692) (14.53)

Savings Accounts 15,785 19,537 17,352 17,391 (2,146) (10.98)

Claims, Spot and Derivatives 7,405 3,409 2,327 710 (2,699) (79.17)

Banker’s Acceptances - - - - - -

Securities Held by Finance Companies 447 156 - 59 (97) (62.09)

Disbursed Loans 2 ,136 2,279 2,758 3 ,368 1,089 47.80

Loan Capital 41 20 70 180 160 803.55

Repo Liabilities - - - - - -

Guarantees 13 11 12 11 (1) (5.07)

Liabilities (Rp, billions) 125,089 136,536 154,488 167,204 30,667 22.46

Bank Debt 100,070 109,778 120,399 132,200 22,421 20.42

Spot and Derivative Liabilities 1,896 1,420 1,161 1,933 514 36.18

Securities Issued by Finance Companies 14,370 16,391 19,781 19,181 2,791 17.03

Banker’s Acceptances 2 - - - - -

Investments from Banks 8,750 8,948 13,148 13,848 4,900 54.77

Repo - - - - - -

Reverse Repo - - - - - -

Miscellaneous Assets 0 - - 41 41 -

industry was relatively stable, as evidenced by the ratio

of current assets to current liabilities12, which increased

slightly on the previous period from 1.66% to 1.67%.

The indicators of insurance density and product

penetration performed well. The density indicator

soared from Rp1,272,493 to Rp1,319,116, while

product penetration remained relatively stable,

moderating slightly from 2.65% to 2.62%.

Notwithstanding the gains, insurance density

and penetration in Indonesia remained below the

global trends13 of USD621 and 6.2% respectively.

Low insurance density and penetration indicators

in Indonesia reveal the vast potential and

11.49%

82.24%

3.83%

12 Current Assets = Total Assets – Strata Title Land and Buildings in Use – Other Fixed Assets – Other Assets.13 Based on the Global Insurance Trends Analysis, 2016 – EY.

134 BANK INDONESIA


Graph 4.65 Asset Share in the Insurance Industry

13.86%

30.91%

12.28%

42.95%

Life Insurance General Insurance and Reinsurance

Social Insurance Compulsory Insurance


Graph 4.66 Insurance Industry Assets and Investments

800

400

200

-

1,200

(Rp T) %

1,000

600

78.22

692

542

804

641

755

610

872

705

777

622

945

780

1,012

850

80.7780.01 79.79

80.8982.62

83.97

65

55

50

75

85

70

60

80

90

Assets Investments Ratio (rhs)

Dec-14 Jun-15Jun-14 Jun-16 Jun-17Dec-15 Dec-16

opportunity for growth in line with the growing

population and increasing prosperity. The current

extensification program to increase the customer

base of the insurance industry is being intensified

by the government through the Social Security

Management Agency (BPJS) as well as the insurance

industry by offering products tailored to low-

income earners through the development of micro-

insurance.

Insurance industry dependence on external debt

was relatively low but tracking an upward trend.

Total external debt reached USD176 million in

the reporting period, up from USD145 million.

Therefore, the external debt of the insurance

industry (USD176 million) represented just 0.12%

of total corporate external debt (USD148,875

million). External debt in the insurance industry was

primarily in the form of premium debt, claim debt,

reinsurance debt, retrocession debt (reinsurance

companies) and commission debt.

Interconnectedness between the insurance and

banking industries increased in the first half of 2017,

reversing the previous contraction of -32.69% recorded

in the second semester of 2016 to increase by 4.91%

(yoy). Furthermore, insurance industry placements

in bank-issued securities has also continued to rise.

In the reporting semester, for instance, the growth

of insurance industry placements in securities issued

by the banking sector accelerated from 56.88% to

92.73% (yoy). At the same time, insurance industry

obligations to the banking industry also increased,

rising 36.78% (yoy) or Rp2.04 trillion, albeit down

from 51.69% (yoy) in the previous period.

BUKU 1 banks were the most interconnected with

the insurance industry but the dependence of BUKU

1 banks on insurance industry funds has tended to

decline due to lower average interest rates than the

average deposit rates offered by BUKU 1 banks. The

proportion of insurance industry funds placed in BUKU

1 deposits reached 5.77% in the reporting period,

135BANK INDONESIA





Table 4.24 Investment Ratio by Insurance Type

Source: Financial Services Authority (OJK), Bank Indonesia, processed

Life Insurance (Rp, trillions) Jun-16 Dec-16 Jun-17 ∆ yoy (%)

Assets 363.16 395.11 434.76 19.71

Investments 313.02 343.27 378.89 21.05

Investment/Asset Ratio 86.19 86.88 87.15 0.96

General Insurance and Reinsurance (Rp, trillions) Jun-16 Dec-16 Jun-17 ∆ yoy (%)

Assets 139.41 139.47 140.34 0.66

Investments 68.16 69.71 71.97 5.58


Social Insurance (Rp, trillions) Jun-16 Dec-16 Jun-17 ∆ yoy (%)

Assets 253.52 289.98 312.89 23.42

Investments 235.83 273.16 295.65 25.37


Compulsory Insurance (Rp, trillions) Jun-16 Dec-16 Jun-17 ∆ yoy (%)

Assets 115.93 120.01 124.36 7.28

Investments 88.36 94.28 103.52 17.16


Table 4.25 Insurance Industry Assets and Financial Performance

* Profitability applicable to Life Insurance as well as General Insurance and Reinsurance

Indicator (Rp, trillions) Jun-16 Dec-16 Jun-17 Growth yoy

Total Assets 872.02 944.58 1,012.34 16.09%

Total Investment 705.36 780.42 850.03 20.51%

Term Deposits 121.87 120.07 141.35 15.98%

Stocks 152.45 177.29 181.30 18.93%

Sukuk or Bonds 89.04 98.61 105.10 18.05%

SBN 188.95 220.67 240.03 27.03%

Securities 1.00 0.83 0.86 -14.39%

Mutual Funds 122.49 132.87 150.54 22.91%

Other Investments 29.57 30.08 30.84 4.31%

Total Non-Investment 50.14 51.84 55.86 11.40%

Total Equity 369.86 401.44 432.68 16.98%

Total Expenses 67.64 150.60 80.20 18.57%

Profitability Jun-16 Dec-16 Jun-17 ∆ yoy

ROA 3.69 3.29 3.61 (0.08)

ROE 12.22 12.16 12.48 0.26

136 BANK INDONESIA


-

400

200

600

800

100

Jun-16

Term Deposits Stocks SBNSecurities Mutual Funds Other Investments

Sukuk or Bonds

Dec-16 Jun-17

500

300

700

900(Rp T)

Graph 4.67 Insurance Industry Asset and Investment Composition


equivalent to 39.92% of total nonbank financial

industry deposits held at BUKU 1 banks.

Dari 146 perusahaan asuransi terdapat 12 perusahaan

yang sudah go public. Dari sisi permodalan, seluruh

perusahaan asuransi go public telah memenuhi

kewajiban permodalan minimum sebesar Rp100

miliar dan sudah memenuhi target minimum Risk

Based Capital (RBC) sebesar 120%. Pemenuhan

kecukupan permodalan sesuai ketentuan tersebut

diharapkan mampu meningkatkan ketahanan

perusahaan asuransi terhadap risiko yang muncul

dari aktivitas perekonomian.

Graph 4.68 Gross Premiums to Claims Ratio Graph 4.69 Ratio of Current Assets to Current Liabilities

800

1.60400

200

-

1,2001.80

1.67

(Rp T)

1,0001.70

600

1.50

Jun-

16

Jul-1

6

Aug-

16

Sep-

16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7

May

-17

Jun-

17

Current Assets Current Liabilities CA/CL (rhs)


350

(Rp T) %

165

145

155

135

160

140

150

130

125

250

150

300 155.78160.25

137.74140.17 145.14

155.74

157.99

147.31

200

100

50

-

Dec-

13

Dec-

14

Dec-

15

Dec-

16

Jun-

14

Jun-

15

Jun-

16

Jun-

17

Gross Premiums Gross Claims Gross Premiums to Claims (rhs)

Graph 4.70 Insurance Industry Indicators

Gross Premiums (Rp, trillions) Density (Rp, thousands) Penetration (rhs)

800

3

4001

200

-

%

-

1,200

1,400

1,000

600

2

Dec-11 Dec-13 Dec-15Dec-12 Dec-14 Dec-16


137BANK INDONESIA





Graph 4.71 Insurance Industry External Debt

200 155,000

USD, millions USD, millions

150 150,000

50

Insurance Industry External Debt Total External Debt (rhs)

140,000

- 135,000

100 145,000

148,875

176

Sep-

14

Nov

-14

Jan-

15

Mar

-15

May

-15

Jul-1

5

Sep-

15

Nov

-15

Jan-

16

Mar

-16

May

-16

Jul-1

6

Sep-

16

Nov

-16

Jan-

17

Mar

-17

Juni

-17


Table 4.26 Interconnectedness between the Banking and Insurance Industries

Source: Monthly Commercial Bank Reports

Component Dec-15 Jun-16 Dec-16 Jun-17 ∆ yoy % yoy

Investment (Rp, billions) 164,205 121,088 117,736 130,374 9,286 7.67

Term Deposits 152,452 108,729 102,612 114,072 5,343 4.91

Demand Deposits and Savings Deposits - - - - - -

Spot and Derivatives - - - - - -

Banker’s Acceptances 6,955 6,467 10,912 12,464 5,997 92.73

Securities Held by Insurance Companies 5 13 512 5 78 4 94 (18) (3.45)

Disbursed Loans 4,268 5,362 3,596 3,312 (2,051) (38.24)

Loan Capital - - - - - -

Guarantees 17 17 38 31 15 89.64

Liabilities (Rp, billions) 4,897 5,534 7,429 7,569 2,035 36.78

Bank Debt 537 1,176 1,333 1,854 678 57.67

Spot and Derivatives - - - - - -

Securities Issued by Insurance Companies - - - - - -

Banker’s Acceptances - - - 1 4 14 -

Investments from Banks 4,123 4,125 6,078 5,683 1,558 37.78

Repo - - - - - -

Reverse Repo - - - - - -

Miscellaneous Assets 237 233 18 18 (215) (92.10)

138 BANK INDONESIA


Graph 4.72 Weighted Average Deposit Rate in Rupiah at BUKU 1 Banks

6

%

4

4.51

4.17

3

5

Dec-

13

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16


Table 4.27 Risk-Based Capital of Public Listed Insurance Companies

Source: Financial Statements of Public Listed Insurance Companies, processed

Period ABDA AHAP AMAG ASBI ASDM ASJT ASRM LPGI MREI PNIN ASMI VINS

2017 Tw II 357 201 247 131 189 171 145 237 266 - 441 779

2016 Tw IV 332 206 261 136 255 233 142 217 242 - 287 794

2016 Tw I 306 242 531 149 213 160 139 182 253 - 209 878

4.3. Islamic Banking Sector Dynamics and Risks

Against a backdrop of consolidation in the

conventional banking industry, financing and

deposit performance at Islamic banks improved

during the first half of 2017. Islamic bank financing

expanded by nearly 20%, with funding growth

reaching 25% (yoy). Furthermore, Islamic bank

assets posted 24% (yoy) growth, backed by a solid

capital base and a 22% Capital Adequacy Ratio

(CAR). Despite the high level of non-performing

financing (NPF), recorded at 3.9%, conditions had

improved on the previous semester.

A. Islamic Banking Industry Performance and

Risks

1. Liquidity Risk

The Islamic banking industry maintained

liquidity on expansive financing, as reflected

by the slight decline in the liquid assets to

non-core deposits ratio from 121.27% in

the previous semester to 120.14%. The

decline was triggered by NCD growth of

8.63%, which outpaced that of liquid

assets at 7.61% to total Rp48.96 trillion.

Consistent with the decline in the LA/NCD

ratio, the liquid assets to deposits ratio also

decreased, falling from 22.04% to 21.82%.

The liquidity declines primarily affected

Weighted Average Deposit Rate Rupiah Deposit Rate for the Insurance Industry

Weighted Average Rupiah Deposit Rate (Total)

139BANK INDONESIA





BUKU 1 banks. As an industry, the position

of liquid assets to NCD at Islamic banks

was sound and remained well above the

threshold.

2. Intermediation Risk

The influx of deposits to the Islamic banking

industry was accompanied by expansive

financing performance. Deposit growth

stood at 25.14% (yoy) in the first semester

of 2017 with financing growth recorded

at 25.14% (yoy), well above the 9.47%

(yoy) achieved in the conventional banking

industry. Consequently, the financing-to-

deposit ratio (FDR) was 83% in the reporting

period. Economic consolidation in the first

half of 2017 prompted prudent lending in

the Islamic banking industry.

a. Deposits

Demand deposits and savings deposits

were the main drivers of deposit

growth in the Islamic banking industry,

10 90.00

0 50.00

20 130.00

15 110.00

5

LA/DepositsLA/MCD (rhs)

70.00

25(%) (%)

150.00

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

22.04

21.82121.27

120.14

Graph 4.73 Liquidity Ratios in the Islamic Banking Industry

120.0050.00

140.0060.00%Rp T

100.0040.00

80.00

30.0060.00

20.00 40.00

10.00 20.00

0.00Jun 14 Jun 15 Jun 16 Jun 17Dec 14 Dec 15 Dec 16

0.00

Liquid AssetsLA/NCD (rhs)

45.50

48.96

Graph 4.74 Banking Industry Liquid Assets

Table 4.28 LA/NCD of Islamic Banks by BUKU Bank Group


BUKU Jun-14 Des-14 Jun-15 Des-15 Jun-16 Des-16 Jun-17

BUKU 1 137.00% 139.92% 114.64% 132.40% 121.17% 165.34% 135.21%

BUKU 2 80.06% 115.11% 89.97% 123.07% 109.31% 126.84% 130.64%

BUKU 3 - - - 103.65% 98.71% 106.66% 100.74%

Islamic Banks 85.97% 117.45% 92.48% 115.78% 105.89% 121.27% 120.14%



140 BANK INDONESIA


Graph 4.75 Deposit and Financing Growth (yoy)

25.1420.83

16.4019.39

Okt 15 Dec 15 Apr 16 Okt 16 Apr 17Feb 16 Ags 16 Feb 17Jun 16 Dec 16 Jun 17

10.00

0.00

20.00

30.00%

15.00

5.00

25.00


expanding respectively at 50.88% (yoy)

and 23.63% (yoy). Demand deposits

were edged upwards by government

placements at Islamic banks and sharia

business units, which posted growth

of 47.07% and 40.28%. Furthermore,

the growth of corporate and individual

deposits topped 20%. By currency,

rupiah deposits achieved 26.09% (yoy)

and foreign currency deposits just

10.88% (yoy).

Expensive funds continued to dominate

funding sources in the Islamic banking

industry despite the significant bump in

government demand deposits. The share

Table 4.29 Financing-to-Deposit Ratio (FDR) by BUKU Bank Group


Description Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU I

Deposits (Rp, trillions) 39.37 20.62 21.70 11.09 16.62 12.82 13.65

Disbursed Financing (Rp, trillions) 43.95 19.36 21.42 11.17 16.10 12.39 12.27

Financing-to-Deposit Ratio (%) 111.66 93.88 98.75 100.70 96.83 96.69 89.90

BUKU II

Deposits (Rp, trillions) 261.69 150.10 141.12 101.75 96.64 123.63 138.47

Disbursed Financing (Rp, trillions) 243.68 129.06 129.86 92.49 90.18 110.26 116.14


BUKU III

Deposits (Rp, trillions) - - - 62.06 63.79 69.96 72.30

Disbursed Financing (Rp, trillions) - - - 50.86 52.51 55.39 57.85

Financing-to-Deposit Ratio (%) - - - 81.96 82.31 79.17 80.02

BUS

Deposits (Rp, trillions) 301 171 163 175 177 206 224

Disbursed Financing (Rp, trillions) 288 148 151 155 159 178 186



Rupiah Deposits (yoy) Foreign Currency Deposits (yoy) Total Deposits (yoy)

Oct 15

21.8426.09

25.1420.83

5.3910.88

Dec 15 Apr 16 Oct 16 Apr 17Feb 16 Aug 16 Feb 17Jun 16 Dec 16 Jun 17

-10.00

-15.00

10.00

0.00

20.00

30.00%

-5.00

15.00

5.00

25.00


Deposits (%, yoy) Disbursed Financing (%, yoy)

141BANK INDONESIA





of demand deposits increased from

10.01% to just 11.91% in the reporting

period, with stable term deposits,

decreasing slightly from 59.49% to

59.30%, and a decline in the market

share of savings deposits from 30.50%

to 28.79%.

The rate of return on deposits in the

Islamic banking industry was relatively

stable at 5.55%, with a moderate

decline on savings deposits from

1.86% to 1.70% and a slight increase

reported for demand deposits from

1.09% to 1.16%. In general, the

returns enjoyed by the Islamic banking

industry remained below the levels in

the conventional banking industry.

Geographically, all regions of the

Indonesian archipelago reported faster

deposit growth. The island of Java

dominated the market share of deposits,

however, accounting for 75.65% of the

total, followed by the islands of Sumatra

and Kalimantan.

Congruent with robust deposit growth, Islamic

banking industry assets also posted significant gains

compared to the second semester of 2016, primarily

at state-owned banks in line with the proliferation

of short-term securities, predominantly Islamic

Treasury Bills (SPNS) issued by the Government with

a tenor of up to 12 months.

Financing

Despite the build-up of credit risk, the Islamic

banking industry maintained expansive growth of

disbursed financing, accelerating from 16.40%

(yoy) in the previous period to 19.39% (yoy). Total

financing in the Islamic banking industry stood at

Rp266.60 trillion, accounting for 5.94% of the

national banking industry total. Rupiah financing

posted strong gains, increasing from 17.61% (yoy)

to 20.77% (yoy), while the contraction of foreign

currency financing deepened from -1.41% (yoy) in

the second semester of 2016 to -3.18% (yoy) in the

first quarter of 2017.

Corporate consolidation forced the Islamic banks to focus

on consumer financing. Disbursed consumer financing

achieved solid growth at 28.17% (yoy), compared to

13.79% (yoy) for working capital financing. In contrast,


Graph 4.77 Deposit Growth by Type

Okt 15

31.9950.88

24.08 23.77

17.58 21.63

Des 15

Apr 16

Okt 16

Apr 17

Feb 16

Ags 16

Feb 17

Jun 16

Des 16

Jun 17

20.00

(20,00)

60.00

100.00

40.00

-

80.00

%

Demand Deposits Savings Deposits Term Deposits

75%

100%

50%

25%

0%

Sem I 2014 Sem I 2015 Sem I 2016 Sem I 2017Sem II 2014 Sem II 2015 Sem II 2016

9.01 8.56 10.28 9.17 9.88 10.01 11.91

28.7930.5029.1129.7028.5929.1828.83

62.16 62.26 61.13 61.13 61.02 59.49 59.30

Graph 4.78 Deposit Composition in the Islamic Banking Industry

Tabungan DepositoDemand Deposits

142 BANK INDONESIA


10.00%

5.55%

1.80% 1.70%

5.55%

8.00%

6.00%

4.00%

2.00%

0.00%

Jan-

15

Feb-

15

Mar

-15

Apr-1

5

May

-15

Jun-

15

Jul-1

5

Aug-

15

Sep-

15

Oct

-15

Nov

-15

Dec-

15

Jan-

16

Feb-

16

Mar

-16

Apr-1

6

May

-16

Jun-

16

Jul-1

6

Aug-

16

Sep-

16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7

May

-17

Jun-

17

Demand Deposits Savings Deposits Deposito

1.09% 1.16%

Graph 4.79 Rate of Return on Deposits


Table 4.30 Deposit Share by Island


IslandAnnual Deposit Growth (yoy) Deposit Share

(%) Sem I 2017Sem I 2016 Sem II 2016 Sem I 2017

Java 13.73 16.67 18.17 75.65

Sumatra 13.18 58.92 77.72 16.83

Kalimantan 11.84 8.87 25.38 4.11

Sulawesi 10.88 1.75 6.67 1.99

Bali and Nusa Tenggara 12.48 11.32 25.41 0.87

Papua and Maluku Islands 11.97 6.94 10.29 0.56

100%

80%

60%

40%

20%

0%

Cash Placements at Other BanksPlacements at Bank IndonesiaSecurities Held InvestmentsFinancingOther Funds

11.74

5.787.24 7.55 8.55

9.55

12.4513.98 12.82 12.82

76.34 72.87 73.50 69.87 70.49

Sem I 2015 Sem I 2016 Sem I 2017Sem II 2015 Sem II 2016

Graph 4.80 Composition of Disbursed Funds

100%

80%

60%

40%

20%

0%

Islamic Treasury Bills (SPNS) Government Islamic Securities (SBSN)Other Securities

Sem I 2015 Sem I 2016 Sem I 2017Sem II 2015 Sem II 20161.40

10.753.67 7.09

14.77

75.3771.73 75.59 66.51 63.23

23.2417.52 20.74 26.40 22.00

Graph 4.81 Securities Holdings of the Islamic Banking Industry


growth of investment financing slowed from 16.15%

(yoy) in the second semester of 2016 to 14.29% (yoy).

Despite the focus of Islamic banks on consumer

financing, financing allocated to the construction

sector posted the strongest growth. By economic

sector, the construction sector was the main

contributor to financing growth in the first half of

the year, reaching 82.80% (yoy). Conversely, the

electricity, gas and water supply (utilities) sector as

well as the corporate services sector experienced

slower growth, while all other sectors achieved

gains. In addition to the construction sector,

the agricultural sector and social services sector

%

143BANK INDONESIA







10.00

-10.00

Oct

-15

Dec-

15

Feb-

16

Feb-

17

Apr-1

6

Apr-1

7

Jun-

16

Jun-

17

Aug-

16

Oct

-16

Dec-

16

0.00

20.00

Rupiah Financing Foreign Currency Financing Total Financing

-20.00

30.00

17.61

20.77

16.4019.39

(1.41)

(3.18)

Graph 4.82 Financing Growth (yoy) by Currency

also posted solid financing growth compared to

conditions in the previous semester.

The Islamic banking industry has begun to favour

musyarakah contracts. Accordingly, musyarakah

contracts grew by 35.22% (yoy) in the reporting

period, while istishna contracts expanded by 26.73%

(yoy). Nevertheless, murabahah contracts remained

dominant, accounting for more than 50%.

The rate of return on financing has decreased. In the

first semester of 2017, the average rate of return on

financing declined on the previous period. In general,

the return on murabahah contracts still exceeded

all other types of contract, while the returns on

istishna, qardh and profit sharing (mudharabah

and musyarakah) contracts moderated slightly.

Conversely, the returns on murabahah and ijarah

contracts increased on the previous semester.

The financing disbursed by BUKU 1 banks

contracted. By BUKU bank group, BUKU 2 banks

reported the strongest financing growth at 28.79%

(yoy), contrasting the -23.79% (yoy) contraction

reported by BUKU 1 banks.

3. Financing Risk

Financing risk in the Islamic banking industry

eased towards the end of the first semester

of 2017 after accumulating throughout the

period. Consequently, the non-performing

financing (NPF) ratio at the end of the first

10.00

0.00

20.00

30.00

%

15.00

5.00 2.711.34

9.27

13.79

23.94

21.70

16.15

14.29

2.11

6.52

23.65

28.17

25.00


Working Capital Investment Consumer

Sem II 2016

Graph 4.83 Disbursed Financing Growth by Type (yoy)

%

144 BANK INDONESIA


0.00

%

20.00

40.00

10.00

-10.00

-20.00

-30.00

-40.00

14.2914.97

26.7319.74

3.46 3.77

29.0935.22

(13.95)(8.92)

25.2830.00

Murabahah Mudharabah Musyarakah IjarahIstishna Qardh

Graph 4.84 Disbursed Financing Growth by Contract (yoy)

20.00

%

60.00

100.00

40.00

0.00

Agriculture Mining Manufacturing ConstructionUtilities

-20.00

80.00

8.6021.54 7.46

12.459.80

12.34

26.31

9.05

28.99

82.80

Graph 4.85 Disbursed Financing Growth by Economic Sector

Sem I 2016 Sem I 2016

Sem I 2016

Sem I 2017 Sem I 2017

Sem I 2017

Sem II 2015 Sem II 2015

Sem II 2015

Sem II 2016 Sem II 2016

Sem II 2016

18.75

8.6911.12

3.998.19

15.83

21.3926.76

(2.34)

0.00

20.00

10.00

-10.00

-20.00

30.00

%

Trade Transportation Corporate Services Social Services Others

MiningManufacturing

ConstructionListrik, Gas, Air

40.87

35.22

33.70

3.26

54,42

0.381.91

4.20 2.667.71

2.95

7.42

12.73

4.14

12.104.94

41.15

6.33

23.91

Consumer

Working Capital

Musyarakah

Ijarah

Murabahah

Istishna

Agriculture

Qardh

Mudharabah

Investment

TradeTransportationCorporate ServicesSocial ServicesOthers

Graph 4.86 Composition of Disbursed Financing

10.00

14.00 14.1413.04

11.8511.14

18.00

%

12.00

80.00

60.00

40.00

20.00

0.00

16.00

Mar

-14

Jun-

14

Sep-

14

Dec-

14

Mar

-15

Jun-

15

Sep-

15

Dec-

15

Mar

-16

Jun-

16

Sep-

16

Dec-

16

Mar

-17

Jun-

17

IjarahMurabahah Istishna Qardh Profit Sharing

Graph 4.87 Rate of Return on Disbursed Financing





145BANK INDONESIA





semester of 2017 was lower than that

recorded in the second semester of 2016.

The NPF ratio peaked in February and April

2017 at 4.41%, before improving to 3.97%

in June 2017.

Based on financing type, the NPF ratios of

working capital and investment financing

improved slightly on the previous semester,

contrasting the deterioration recorded in the

NPF of consumer financing. Working capital

financing posted the largest improvement,

with the corresponding NPF falling from

6.60% in the second semester of 2016 to

5.25% in the first semester of 2017, while

the NPF of investment financing improved

from 5.91% to 5.42%. By contract, the

NPF of murabahah contracts deteriorated

but the NPF of all other contracts improved

on conditions reported in the previous

period.

By economic sector, the dominant influencers

of non-performing financing (NPF) in the

first half of the year were corporate services,

the trade sector and transportation. The

NPF ratio for the transportation as well as

corporate services sectors increased, while

the ratio for the trade sector improved

in the reporting period. The highest NPF

ratio affected the utilities sector (electricity,

gas and water supply) despite early signs

of improvement. Nevertheless, the mining

sector still demands vigilance because

despite only accounting for 6.4% of total

financing from Islamic banks, the NPF ratio

In Trillion Rupiah


BUKU Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 43.95 19.36 21.42 11.17 16.10 12.39 12.27

BUKU 2 243.68 129.06 129.86 92.49 90.18 110.26 116.14

BUKU 3 - - - 50.86 52.51 55.39 57.85

Islamic Banks 287.64 148.42 151.28 154.53 158.79 178.04 186.27

Table 4.31 Disbursed Financing by BUKU Bank Group

6.00

12.00

14.00

Rp T%

5.00

NPF Value (rhs) NPF Ratio

10.004.00

8.00

3.006.00

2.004.00

1.00 2.00

0.00 0.00

4.13 3.97

Oct

-15

Oct

-14

Dec-

15

Dec-

14

Feb-

16

Feb-

15

Feb-

17

Apr-1

6

Apr-1

5

Apr-1

7

Jun-

16

Jun-

15

Jun-

17

Aug-

16

Aug-

15

Oct

-16

Dec-

16

Graph 4.88 Non-Performing Financing

146 BANK INDONESIA


7.00

6.00

5.00

4.00

3.00

2.00

1.00

0.00

Working Capital Investment Consumer

%6.60

5.665.25

5.915.60 5.42

2.93

1.93 2.02


Graph 4.89 NPF Ratio by Financing Type

stood at 10.48% and credit growth to

the sector accelerated to 13.49% in the

reporting period.

The sharp increase of NPF in the

transportation sector must also be

monitored further after a two-fold hike

on the previous period from 5.37% to

10.06%. The deteriorating quality of

financing extended to the transportation

sector, which accounted for 5.01% of

total financing allocated by Islamic banks,

was consistent with the declining quality

of financing from finance companies

and the banking industry allocated to

the transportation sector in Indonesia.

Consequently, financing growth in the

transportation sector experienced a deeper

contraction, decreasing from -0.02% in

the second semester of 2016 to -3.36% in

the first semester of 2017.

BUKU 1 banks confirmed an improvement

in their NPF ratio. Moreover, the NPF ratio

of Islamic banks categorised as BUKU 1

posted NPF gains despite remaining above

the 5% threshold, improving markedly from

12.91% to 8.96% in the reporting period

and also gaining on conditions reported in



7.00

8.00

%

6.00 5.54

4.484.79

2.301.85

1.48

2.73

1.911.88

1.85

2.472.38

5.21

3.663.09

3.56

7.23

4.015.00

4.00

3.00

2.00

1.00

0.00Musyarakah IjarahMurabahah Istishna Qardh Mudharabah

Graph 4.90 NPF Ratio by Contract



147BANK INDONESIA





4. Market Risk

The rate of return on deposits has remained

stable but returns on disbursed financing

have decreased. In the first half of 2017,

the rate of return on deposits was relatively

stable compared to conditions in the previous

semester, with the return on demand deposits

increasing slightly from 1.09% to 1.16%,

the return on savings deposits decreasing to

1.70% and stable returns reported on term

deposits at a level of 5.55%. On the other

hand, the average rate of return on financing

declined. The returns on murabahah and

ijarah contracts increased modestly in the

reporting period to 14.14% and 13.04%,

while the returns on all other contracts

tracked downward trends.

5. Profitability, Efficiency and Capital

The profitability of Islamic banks has begun to

improve. The ROA increased from 0.63% in

the second semester of 2016 to 1.10% in the

first half of 2017 in line with greater efficiency

as the BOPO efficiency ratio improved from

96.23% to 90.98% over the same period

and the NOM ratio increased from 0.68%

to 1.24%. Furthermore, the Islamic banking

industry also reported lower operating costs,

exceeding the corresponding decline in

operating income due to lower provisions

for impairment losses. Nonetheless, the

lower position of provisions for impairment

losses was not due to improvements in the

non-performing financing (NPF) ratio but the

result of expropriating productive assets.

Mining

Manufac

turing

Constructi

on

Utilities

Agricu

lture

Trade

Transp

ortation

Corporate Se

rvice

s

Socia

l Servi

ces

Others

10.00

14.00

%

12.00

80.00

60.00

3.16

8.62

4.34

10.30

3.634.84

9.82

5.62

2.452.14

40.00

20.00

0.00

Graph 4.91 NPF Ratio by Economic Sector

Table 4.32 Gross NPF Ratio of Islamic Banks by BUKU Bank Group


BUKU Sem II-2014 Sem I-2015 Sem II-2015 Sem I-2016 Sem II-2016 Sem I-2017

BUKU 1 3.29 4.74 8.30 10.07 12.91 8.96

BUKU 2 5.24 5.15 3.74 4.95 3.20 3.80

BUKU 3 - - 6.08 5.60 4.94 4.87

TOTAL 4.99 5.09 4.84 5.68 4.42 4.47



148 BANK INDONESIA


Table 4.34 Rate of Return on Disbursed Financing

PYD2015 2016 2017


Murabahah 15.44% 15.00% 13.34% 13.89% 14.14%

Istishna 12.37% 13.12% 13.00% 13.49% 13.05%

Qardh 12.57% 12.61% 7.13% 11.60% 11.14%

Profit Sharing 12.92% 12.45% 10.48% 12.90% 11.85%

Ijarah 10.32% 11.40% 10.07% 12.76% 13.04%


Table 4.33 Rate of Return on Deposits

DPK2015 2016 2017


Demand Deposits 0.73% 0.74% 0.86% 1.09% 1.16%

Savings Deposits 3.27% 2.93% 2.48% 1.86% 1.70%

Term Deposits 6.95% 6.71% 6.31% 5.55% 5.55%

The returns at Islamic banks tended to

increase despite lower interest rates. The

rising NOM at Islamic banks was caused by

an increase in the rate of return on financing,

contrasting the decline in the rate of return

on deposits. The higher rate of return in the

Islamic banking industry was contrary to

the lower rate reported by the conventional

banking industry in Indonesia.

a. Profitability

Islamic bank profitability remained below

that of conventional banks despite rising.

In terms of ROA, the profitability of

Islamic banks stood at 1.10% compared

to 2.47% for conventional banks. By

BUKU bank group, the ROA increase

was driven by BUKU 2 banks (ROA,

1.39%). Meanwhile, the ROA at BUKU

1 and 3 banks were recorded at 0.65%

and 0.59% respectively. The post-tax net

profit of Islamic banks was Rp2.25 trillion

in the first semester of 2017, up from

Rp952 billion in the previous period. All

BUKU groups reported profit gains.

b. Efficiency

The BOPO efficiency ratio declined,

indicating greater efficiency. In the

first semester of 2017, the BOPO

efficiency ratio decreased from 96.23%

to 90.98%, with all BUKU groups

reporting efficiency gains. Compared

to conventional banks, the lower BOPO

efficiency ratio at conventional banks

was indicative of greater efficiency.

Therefore, efficiency must be improved

in the Islamic banking industry in order

to increase competitiveness against their

conventional counterparts.

c. Capital

Islamic banks reported a relatively solid

Capital Adequacy Ratio (CAR). The

Islamic banking industry maintained

CAR well above the threshold,

increasing from 15.95% in the second

semester of 2016 to 16.42% in the

first semester of 2017. CAR was

reported to increase at BUKU 1 and

3 banks, while moderating slightly at

BUKU 2 banks.

149BANK INDONESIA






5.25% 15.00%

14.00%

12.00%

10.00%

5.00%13.00%

4.75%

11.00%

4.50%

BI 7-Day (Reverse) Repo Rate Industry Rate of Return

Jun-

16

Jul-1

6

Aug-

16

Sep-

16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7

Mei

-17

Jun-

17

Graph 4.92 Comparison of Returns on Disbursed Financing at Islamic Banks, Lending Rats and the BI 7-Day (Reverse) Repo Rate

2.00

%

1.00

0.00

-1.00

-2.00

-3.00

-4.00

-5.00

0.63 0.651.39

1.100.59

Sem I 2016Sem I 2015


BUKU 1 BUKU 2 BUKU 3 Total

Sem II 2014 Sem I 2017Sem II 2015 Sem II 2016

Graph 4.93 ROA by BUKU Group


150 BANK INDONESIA

3.00

%

2.50

2.00

2.47

1.101.50

1.00

0.50

0.00Sem I 2016Sem I 2015Sem II 2014 Sem I 2017Sem II 2015

Conventional Islamic

Sem II 2016

Graph 4.94 ROA Comparison between Islamic and Conventional Banks


2.00

-1.00

1.00

-2.00

-4.00

0.00

-3.00

-5.00 Sem I 2016Sem I 2015Sem II 2014 Sem I 2017Sem II 2015 Sem II 2016

BUKU 1

BUKU 1

BUKU 2

BUKU 2

BUKU 3

BUKU 3

Total

Total

Graph 4.95 NOM by BUKU Group

Table 4.35 P&L by BUKU Group


BUKUPre-Tax P&L Post-Tax P&L

Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 0.17 (0.15) (0.33) (0.15) (0.65) 0.11 0.14 (0.20) (0.33) (0.16) (0.66) 0.21

BUKU 2 0.66 1.14 0.96 1.25 1.63 2.26 0.56 0.95 0.72 0.95 1.28 1.67

BUKU 3 - - 0.35 0.44 0.43 0.48 - - 0.25 0.34 0.33 0.36

TOTAL 0.82 0.99 0.98 1.55 1.42 2.85 0.70 0.74 0.63 1.13 0.95 2.25

Graph 4.96 BOPO Efficiency Ratio by BUKU Group Graph 4.97 BOPO Comparison between Islamic and Conventional Banks


140.00

%

100.00

40.00

120.00

80.00

20.00

60.00

0.00

96.23 90.98

Sem I 2016Sem I 2015Sem II 2014 Sem I 2017Sem II 2015 Sem II 2016


79.0090.98

Conventional Islamic

120.00

%

100.00

80.00

60.00

40.00

20.00

0.00Sem I 2016Sem I 2015 Sem I 2017Sem II 2015 Sem II 2016Sem II 2014

180.00

210.00 16.42

15.95

120.00

150.00

Rp (T)

%

90.00

60.00

30.00

0.00Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

Capital Risk-Weighted Assets (RWA) CAR (rhs)

Graph 4.98 CAR

17.00

16.50

16.00

15.30

15.00

14.50

14.00

13.50

13.00

12.50

Table 4.36 CAR of Islamic Banks by BUKU Group

Source: Bank Indonesia Source: Bank Indonesia

BUKU Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 Sem II 2016 Sem I 2017

BUKU 1 17.56 20.89 20.58 21.28 20.86 20.88

BUKU 2 15.39 12.82 15.36 15.26 17.26 16.90

BUKU 3 - - 13.02 11.98 12.54 14.36

TOTAL 15.74 14.02 15.02 14.72 15.95 16.42





151BANK INDONESIA

Box 4.1. Seasonal Liquidity Trends during Eid-ul-Fitr

The banking industry maintained ample liquidity,

tracking an upward trend in the first half of 2017

compared to conditions in the previous year. Resilient

liquidity was bolstered by financial expansion by

the government, sluggish credit growth and faster

deposit growth. In general, the liquidity ratio in the

banking industry improved on the previous year,

increasing from 20.9% to 21.2%.

Notwithstanding, there is a cyclical tightening of

liquidity each year during Eid-ul-Fitr. In 2017, the

transient tightening of liquidity occurred at the end

of the first semester, as Eid-ul-Fitr coincided with

Source : Bank Indonesia

Box Table 4.1.1 Liquidity Ratio by Bank Type

LA/Deposits Ratio (%)

2015 2016 2017 2015(ytd)

2016(ytd)Des Juni Des Jun

State-Owned Banks 20.5 19.8 21.5 18.8 (0.7) (2.7)

Private National Commercial Banks 16.6 18.3 18.0 19.7 1.7 1.7

Regional Banks 12.9 17.8 18.6 24.3 4.9 5.7

Foreign Banks 53.2 53.3 53.4 64.2 0.1 10.8

Industry 19.4 20.3 20.9 21.2 0.9 0.3

Box Graph 4.1.1 Liquidity Ratios in the Banking Industry

2012

-TW

I

2014

-TW

I

2013

-TW

I

2015

-TW

I

2016

-TW

I

2017

-TW

I

2012

-TW

II

2014

-TW

II

2013

-TW

II

2015

-TW

II

2016

-TW

II

2017

-TW

II

2012

-TW

III

2014

-TW

III

2013

-TW

III

2015

-TW

III

2016

-TW

III

2012

-TW

IV

2014

-TW

IV

2013

-TW

IV

2015

-TW

IV

2016

-TW

IV

60

20

40

0

80

5

100

15

10

12025

20

140 30

101.26%

50%

21.15%

8.5%

%%

LA/Deposits LA/NCD (rhs)

Box Graph 4.1.2 Annual Liquidity Ratio Trends in the Banking Industry

Box Graph 4.1.3 Annual Liquid Asset Trends in the Banking Industry

1 2

24

23

20

22

19

21%

183 4 5 6 7 8 9 10 11 12

LA/Deposits Ratio in 2015



1 2

1,100

1,150

1,050

900

1,000

850

%950

8003 4 5 6 7 8 9 10 11 12

LA in 2015 LA in 2016 LA in 2017

June. Such dynamics were also reported in 2015

and 2016. The temporary tightening of liquidity

was evidenced by declines in the liquidity ratio and

liquid assets of the banking industry.

Furthermore, the interbank borrowing rate also

increased as an indication of tighter liquidity in the

banking system. Declining liquid assets coupled

with the rising interbank rate were the result of

the banks scrambling to bridge the funding gap

that arose from a large outflow of funds from

the banking system during Eid-ul-Fitr, which

undermined deposit growth. The banks overcame


152 BANK INDONESIA


Box Graph 4.1.4 Liquid Assets and Interbank Rates

H-31

H-30

H-29

H-28

H-27

H-26

H-25

H-24

H-23

H-22

H-21

H-20

H-19

H-18

H-17

H-16

H-15

H-14

H-13

H-12

H-11

H-10 H-

9

H-8

H-7

H-6

H-6

H-5

H-4 H-3

H-2

H -1

H+1

H+2

H+3

H+4

BUKU 1 Regional Banks (2016)

BUKU 4 State-Owned Banks (2016)

BUKU 3 State-Owned Banks (2016)

LA (rhs) BUKU 2 Regional Banks (2016)

BUKU 3 Private National Commercial Banks (2016)


BUKU 2 Foreign Banks (2016)

BUKU 3 Foreign Banks (2016)



BUKU 3 Regional Banks (2016)

6.2

4.7

4.7

4.7

5.7

5.7

5.7

4.2 4.2

4.2

5.2

5.2

5.2

%

Rp T

Downward Daily Trend of Liquid Assets Interbank

Rate

Weighted Interbank Rate in 2017

Weighted Average Interbank Rate in 2016

June JuliMei Juli

Eid-ul-Fitr

8.5

8

7.5

7

6.5

6

5.5

5

4.5

4

Overnight

Medium-Tenor Interbank Rates experienced Largest Increases

1 Month

2-4 Days

2 Months 3 Months >3 Months Weighted Average

H-31

H-30

H-29

H-28

H-27

H-26

H-25

H-24

H-23

H-22

H-21

H-20

H-19

H-18

H-17

H-16

H-15

H-14

H-13

H-12

H-11

H-10 H-

9

H-8

H-7

H-6

H-5

H-4 H-3

H-2

H -1

H+1

1 Week 2 Weeks

Eid-ul-Fitr

3 Weeks

Box Graph 4.1.5 Interbank Rate by Tenor

the funding gap by liquidating assets and through

interbank loans, while several banks turned to the

lending facility and term repo. In 2017, however,

the increase observed in the interbank rate was not

as severe nor as prolonged.

The interbank rate began to spike three days before

Eid-ul-Fitr (H-3) and peaked on H-1, affecting all

tenors, in particular medium tenors in line with

increasing demand. Furthermore, the higher

interbank rate impacted all bank groups, but

especially regional banks. The transient tightening

of liquidity at regional banks was exacerbated by

the postponement of salary dropping and General

Allocation Fund (DAU) payments for July until after

Eid-ul-Fitr. Banks successfully anticipated the delay

by stocking additional cash prior to Eid-ul-Fitr and

using the interbank money market to meet any

further cash shortfalls. The interbank rate quickly

returned to normal after Eid-ul-Fitr.



153BANK INDONESIA





25

10

20

5

15

0

H-31

H-30

H-29

H-28

H-27

H-26

H-25

H-24

H-23

H-22

H-21

H-20

H-19

H-18

H-17

H-16

H-15

H-14

H-13

H-12

H-11

H-10 H-

9H-

8H-

7H-

6H-

5H-

4H-

3H-

2H-

1H+

1

Rp T

Overnight

1 Month

2-4 Days

2 Months 3 Months >3 Months

1 Week 2 Weeks 3 Weeks

Eid-ul-Fitr

Box Graph 4.1.6 Interbank Money Market Transaction Volume

35

25

-5

15

-15

5

Rp T

-25

H-31

H-30

H-29

H-28

H-27

H-26

H-25

H-24

H-23

H-22

H-21

H-20

H-19

H-18

H-17

H-16

H-15

H-14

H-13

H-12

H-11

H-10 H-

9H-

8H-

7H-

6H-

5H-

4H-

3H-

2H-

1H+

1

BUKU 1 Regional Banks

BPD-BUKU 1 BPD-BUKU 2


BPD-BUKU 3


BUMN-BUKU 3

BUKU 3 State-Owned Banks

BUMN-BUKU 4

BUKU 3 Private National Commercial Banks

BUSN-BUKU 3 BUSN-BUKU 4 KCBA-BUKU 2


KCBA-BUKU 3

BUSN-BUKU 1

Eid-ul-Fitr

Box Graph 4.1.7 Net Interbank Money Market by Bank Type

BUKU 4 State-Owned Banks


BUKU 2 Foreign Banks BUKU 3 Foreign Banks

In addition to the interbank rate spike, interbank

money market transaction volume also experienced

a shift. Volume shifted to the medium tenors,

primarily 2-week tenors. In contrast, O/N volume

tended to decline, commencing three days before

Eid-ul-Fitr. Regional and small private national

commercial banks, which had been net placing

banks prior to Eid-ul-Fitr, become net taking banks.

Relatively more resilient liquidity dynamics in the

banking industry in 2017, despite seasonally tighter

liquidity during Eid-ul-Fitr, was due to the high

level of liquid assets maintained by the banking

sector compared to previous periods (in pursuance

of the 80% Liquidity Coverage Ratio enforced by

the Financial Services Authority (OJK) in the second

semester of 2017) combined with Bank Indonesia’s

response to tighter conditions in the money markets

by offering term repo.



154 BANK INDONESIA


Box 4.2. Correlation Analysis of Bank Deposits with Expansion of the Government’s Expenditure Budget in East Java

A priori, a relationship is often suggested between

deposits accumulated in the banking industry and

financial expansion by the government because the

banks play a role in the transmission of government

budget receipts and expenses. The position of

deposits, as demand deposits, term deposits

and savings deposits, correlates with trends of

government receipts and expenditures. When the

government spends money from the state coffers, it

is expected to influence the composition of demand,

term and savings deposits in the banking industry

due to the associated interactions with project

executors and the beneficiaries of government fund

disbursements.

Theoretically, the correlation is inextricably linked to

the macroeconomic concept that national savings

represent part of the Gross Domestic Product (GDP),

which is calculated using an expenditure approach.

In this regard, national savings are the total economic

income of a country after government consumption

and expenditure are deducted. Furthermore,

national savings consist of government deposits and

private deposits. Government savings constitute the

difference between state revenues and expenditure,

while private savings include corporate profits not

paid as dividends to the shareholders and household

savings as unspent household income.

Various studies have reviewed the correlation

and influence of government spending on

macroeconomic variables, including Barro (1987),

who revealed how government spending, interest

rates, inflation and budget deficits are correlated.14

14 Barro, Robert, J, Government Spending, Interest Rates, Prices and Budget Deficits in the United Kingdom, 1701-1918, Journal of Monetary Economics No. 20 (1978), 221-247, North-Holland.

Government spending influences the economy

through various channels, including the impact on

interest rates, output, consumption and investment.

Furthermore, government spending also has a

direct impact on prices and an indirect impact

through changes in monetary aggregates, while

also influencing the current account and budget

deficit.

This brief article does not intend to review the

impact of expansive local government spending

on the economy but attempts to observe the

correlation between changes in bank deposit

composition and local government spending. A

simple correlation method was used for the case

of East Java. Expansive government spending in

East Java (the province, all regencies and cities,

as well as the regional administration of East

Java) was shown to correlate with bank deposits.

Nominally, the local government budget in East

Java is not considered large in comparison to the

corresponding Regional Gross Domestic Product

(RGDP), accounting for around 8-9%. Therefore,

the local government of East Java is required to

allocate part of its expenditure budget to projects

and activities that stimulate value added in the

region, as reflected by changes in bank deposits,

particularly savings deposits.

Government Expenditure Budget Realisation

in East Java

Expansion of the government expenditure budget

in East Java, which originates from the provincial

budget, the budgets of the 38 regencies/cities

155BANK INDONESIA





Rp 22.50 T17%

East Java Provincial Budget

Box Graph 4.2.1 Average Regional Expenditure Budget Realisation 2014-2016

Regencies/Cities Budget

Budget in East Java

Rp 76.62 T56%

Rp 36.95 T27%

Source: Regional Asset and Finance Management Agency (BPKAD) and Regional Office of the Directorate General of the Treasury, East Java

and state budget disbursements for local projects,

has increased annually. Total realisation of the

expenditure budget in 2014 stood at Rp114.76

trillion, increasing in 2015 to Rp135.55 trillion and

Rp157.88 trillion in 2016, equivalent to growth of

18.12% (yoy) and 16.47% (yoy) respectively.

Based on the totals, expenditure budget realisation

for the 38 regencies/cities in East Java has remained

dominant, averaging Rp76.62 trillion per annum

(56%) for the period from 2014-2016, followed

by the provincial budget totalling Rp36.95 trillion

(27%) and state budget disbursements at Rp22.50

trillion (17%).

In terms of disbursement, all budgets follow the

same trend, increasing each quarter starting in

the first quarter and peaking in the fourth quarter.

During 2014-2016, average budget realisation in

the first quarter was 10.11%, with 19.31% in the

second, 26.98% in the third and 43.60% in the

fourth quarter of the total expenditure budget for

the current year.

Total government expenditure budget realisation

from 2014 to the first quarter of 2017 reached

Rp424.98 trillion, consisting of Rp71.52 trillion

from the provincial budget, Rp236.92 trillion

156 BANK INDONESIA


Box Graph 4.2.2 Government Expenditure Budget Realisation in East Java 2014-2016 (quarterly)

50

45

40

35

30

25

20

15

10

5

0TW I2014

Provincial Budget Provincial BudgetLocal Government Deposits Local Government Deposits

TW I2015

TW I2016

TW II2014

TW II2015

TW II2016

TW III2014

TW III2015

TW III2016

TW IV2014

TW IV2015

TW IV2016

Box Table 4.2.1 Government Expenditure Budget Realisation in East Java (Rp, billions)



QuarterGOVERNMENT EXPENDITURE BUDGET REALISATION IN EAST JAVA

Provincial Budget Regency/City Budgets State Budget Total

Tw I 2014 3,325 5,726 3,605 12,566

Tw II 2014 3,452 10,779 6,875 21,106

Tw III 2014 4,241 18,344 8,882 31,467

Tw IV 2014 9,100 26,849 13,674 49,623

Tw I 2015 2,639 6,928 3,974 13,541

Tw II 2015 6,455 14,777 6,459 27,691

Tw III 2015 5,356 19,918 10,328 35,602

Tw IV 2015 8,503 33,175 17,041 58,720

Tw I 2016 2,879 7,983 3,974 14,836

Tw II 2016 3,330 20,401 6,459 30,190

Tw III 2016 8,746 20,877 13,400 43,023

Tw IV 2016 9,562 44,088 16,186 69,836

Tw I 2017 4,020 7,075 5,682 16,777

Total 71,517 236,920 116,539 424,976

from the budgets of 38 regencies/cities in East

Java and Rp116.54 trillion from the state budget.

The following table presents the realisation of the

provincial budget, budgets for the 38 regencies/

cities and state budget disbursements from the first

quarter of 2014 until the first quarter of 2017.

Bank Deposit Developments in East Java

Total bank deposits in East Java increased by an

average of Rp40.85 trillion per annum from 2014

– 2016, with a decelerating growth trend. The

deposits accumulated by the banking industry in

East Java at the end of 2014 totalled Rp389.53

trillion, increasing 14.31% on the position recorded

at the end of 2013. The total increased to Rp429.66

trillion at the end of 2015 and Rp463.29 trillion at

the end of 2016, with growth slowing from 10.30%

(yoy) to 7.83% (yoy) respectively.

From 2014 to the first quarter of 2017, the deposits

recorded in the banking industry of East Java

increased by Rp128.69 trillion. Term deposits were

the main contributor to the gains, rising Rp62.71

trillion, followed by savings deposits at Rp38.24

157BANK INDONESIA





Box Table 4.2.2 Increase (Decrease) of Bank Deposits in East Java (Rp, billions)


Year Quarter Demand Deposits Savings Deposits Term Deposits Total

2014

I (1,114) (7,055) 5,479 (2,690)

II 8,218 2,883 7,322 18,422

III 1,714 5,866 13,352 20,931

IV (705) 9,506 3,313 12,114

2015

I 6,650 (9,199) 10,192 7,642

II 4,786 1,218 1,656 7,660

III 1,309 9,963 2,245 13,518

IV (5,126) 14,237 2,195 11,305

2016

I 5,412 (7,614) 3,487 1,286

II (1,885) 9,454 1,785 9,355

III 2,939 2,192 1,356 6,487

IV (2,446) 16,730 2,229 16,514

2017 I 7,989 (9,943) 8,097 6,143

Total 27,741 38,238 62,708 128,687

Box Graph 4.2.3 Bank Deposits in East Java

500,000450,000400,000350,000300,000

25,00020,00015,00010,000

5,000-

(5,000)(10,000)(15,000)

2014

I I I III II IIIII III IIIIV IV IV

2015 2016 2017

billion Rp

Demand Deposits Term DepositsSavings Deposits Total

Box Graph 4.2.4 Government Deposits in East Java

500,000

450,000

400,000

350,000

300,000

250,000

200,000

150,000

100,000

50,000

-TW I2014

TW IV2013

Total Deposits

billion Rp

Local Government DepositsGrowth of Total Deposits (yoy) Growth of Local Government Deposits (yoy)

TW I2015

TW I2016

TW II2014

TW II2015

TW II2016

TW III2014

TW III2015

TW III2016

TW IV2014

TW IV2015

TW IV2016

TW I2017

Source: Commercial Bank Reports, processed

trillion and demand deposits at Rp27.74 trillion.

Nevertheless, the upward trends of each respective

component differed by quarter, namely that savings

deposits were inversely correlated with demand

deposits, while term deposits were more stable and

fluctuated less in general.

A correlation analysis of deposits government

expenditure budget realisation and shifts in bank

deposits in East Java showed that budget realisation

tracked the same trend as savings deposits, namely

increasing from the first to fourth quarter each year,

as well as demand deposits, which decreased from

158 BANK INDONESIA


Box Table 4.2.3 Correlation between Government Expenditure Budget Expansion and Bank Deposits in East Java

Source: Pearson Correlation Testing

APBN + APBD APBD APBD PROV APBD KAB KOTA

DepositsCorrelation 0.49 0.48 0.28 0.51

P Value 0.09 0.10 0.36 0.07

Demand DepositsCorrelation (1.) (1.) (1.) (1.)

P Value 0.01 0.01 0.06 0.01

Savings DepositsCorrelation 0.88 0.89 0.68 0.91

P Value 0.00 0.00 0.01 -

Term DepositsCorrelation (0.) (0.)

P Value 0.10 0.09 0.06 0.12

Box Graph 4.2.5 Composition of Government and Private Deposits

500,000450,000400,000350,000300,000250,000200,000150,000100,000

50,000-

Rp T

rillio

n

Composition of Government and Private Deposits

2011 2012 2013 2014 2015 2016

% of Private Deposits 68.48% 66.68% 72.38% 70.51% 75.96% 81.32%

Private Deposits 174.372 198.126 246.636 274.658 326.379 376.757

% of Government Deposits 31.52% 33.32% 27.62% 29.49% 24.04% 18.68%

Government Deposits 80.279 98.990 94.117 114.873 103.276 86.539

Source: Commercial Bank Reports, processed

the first to fourth quarter each year. The following

graph maps the rising and falling trends of each

component of deposits in East Java from the first

quarter of 2014 to the fourth quarter of 2017.

Local Government Deposits in the Banking

Industry of East Java

Local government deposits in the banking industry

of East Java have expanded by an average of 2.83%

(yoy) over the past five years, following a decelerating

trend. At the end of 2016, total local government

deposits stood at Rp86.54 trillion, consisting of

savings deposits (2.64%), term deposits (31.65%)

and demand deposits (65.71%). The total had

increased 7.80% on the Rp80.28 trillion position

recorded at the end of 2011, or by an average of

Rp1.25 trillion per annum.

Statistical Testing

The results of statistical testing showed that the

correlation between government expenditure

budget expansion and growth of total deposits in

East Java was not statistically significant. Spatially,

however, government expenditure budget

expansion correlated positively with savings deposits

and was inversely correlated with demand deposits.

159BANK INDONESIA





Box Table 4.2.3 presents the results of Pearson

Correlation testing between government

expenditure budget expansion and the growth of

bank deposits in East Java from the first quarter

of 2014 to the first quarter of 2017. Based on

the testing, the following statistically significant

correlations were found:

1. The realisation of the local government

expenditure budget in East Java (provincial

budget, budgets of 38 regencies/cities and

state budget disbursements in East Java) with

increasing savings deposits and decreasing

demand deposits in the banking industry of East

Java.


expenditure budget in East Java (provincial

budget and budgets of 38 regencies/cities)

with increasing savings deposits and decreasing

demand deposits in the banking industry of East

Java.


expenditure budget in East Java with increasing

savings deposits in the banking industry of East

Java.

4. The realisation of the expenditure budgets of 38

regencies/cities with increasing savings deposits

and decreasing demand deposits in the banking

industry of East Java.

The results show empirical evidence of a significant

correlation between government expenditure

budget expansion and two components of bank

deposits, namely demand deposits and savings

deposits. A positive correlation was shown for

savings deposits and an inverse correlation for

demand deposits. In other words, government

expenditure budget expansion was consistent with

increasing savings deposits and decreasing demand

deposits in the banking industry of East Java.

Such dynamics are a result of the dominant

composition of government deposit in the banking

industry ranging from 18.68% to 33.22% in 2014-

2016. On the other hand, the results showed that

bank mindedness in East Java is already high, with

the government, entrepreneurs and public using

banking services, thus a shift in one component

would alter the composition of the other

components. In terms of deposits, the changes

sometimes only occur due to mutual offsetting,

primarily between demand deposits and savings

deposits.

Various apparatus is required during a puppet performance, including a banana stem and the puppets,

which are accompanied by a gamelan orchestra to create synergy and enhance the aesthetic value. In terms

of financial system stability, this signifies the financial system infrastructure. A stable financial system must

be underpinned by reliable infrastructure.

05


05

During the first semester of 2017, the payment systems operated by Bank Indonesia

and the industry remained secure, efficient, available and reliable, thereby helping to

maintain monetary and financial system stability, while facilitating economic activities.

Such developments were corroborated by the positive performance of the main and

supporting indicators. Bank Indonesia continued to focus payment system policy

and efforts towards consistently enhancing economic efficiency as well as sustainably

strengthening and developing payment system infrastructure, thereby demonstrating

Bank Indonesia’s avowed commitment to support financial system and national economic

stability.

FINANCIAL SYSTEM INFRASTRUCTURE

05


162 BANK INDONESIA

THE PAYMENT SYSTEM, AS A COMPONENT OF FINANCIAL SYSTEM INFRASTRUCTURE,PLAYS A STRATEGIC ROLE IN SUPPORTING DOMESTIC ECONOMIC ACTIVITIES ANDFINANCIAL SYSTEM STABILITY.

Transaction value: upRp3,152.19 trillion

Transaction volume: up3,263.14 million transactions


Transaction value: upRp 4.76 trillion

Transaction volume: up2,914.92 million transactions

Transaction volume: up348.22 million transactions

Card-Based Payment

Instruments (APMK)

E-Money

MO Placements down toRp12,094.26 trillion

Turnover Ratio down to1.04

Operational Risk Mitigation: • Business Continuity Plan (BCP) procedures, including the availability of backup systems, namely

infrastructure that is on continuous standby to fully replace the primary production system as required.

• Various measures were undertaken on the operator and participant sides, including antivirus updates and security patches as well as testing environment development and simulating transactions.

Bank Indonesia’s financial inclusion policy in 2017 focuses on expanding financial access through integration of the noncash ecosystemwith government services and programs, including: • Noncash Social Assistance disbursements • Digital Village Fund – Utilisation of the Noncash Village Fund• Toll Road Electronification

Transaction Queue: Low33 transactions worth Rp3,210.60 billion.0.0006% of total RTGS transaction value 0.0007% of total RTGS transaction volume

Risk Mitigation

Development of Digital Financial Services (DFS)

The payment systems operated by Bank Indonesia and the industry remained secure, available and efficient.

Payment System Indicators

Industry-Operated Payment System

The BI-Operated Payment System

Public access and adoption of financial services tended to increase nationally.


Transaction value: upRp 84,391.70 trillion

BI-RTGS

BI-SSSS

National Clearing System (SKNBI)


Transaction volume: down4.77 million transactions


Transaction volume: down0.14 million transactions

Transaction value: downRp1,679.99 trillion


Sem II 2016 Sem II 2016 Sem II 2016 Sem II 2016

Composite Financial Inclusion Index of Indonesia Transaction Value DFS Providers Agen LKD

Sem I 2017 Sem I 2017 Sem I 2017 Sem I 2017

0.41 13.49 billion 5 banks 133,811 agents 0.45 3.50 billion5 banks and 1

nonbank financial institution

160,524 agents

• Remittances• Electronification of Local Government Transactions

163BANK INDONESIA

The payment system is a component of financial

system infrastructure that plays a strategic role

in supporting domestic economic activities and

national financial system stability. Therefore,

Bank Indonesia is committed to issuing policy

that maintains a secure, efficient, available and

reliable payment system. Such conditions were

successfully met in the first semester of 2017, as

confirmed by payment system indicators. The

BI-operated payment system remained secure,

with the settlement risk contained and adequate

liquidity maintained during the reporting period.

Meanwhile, payment system reliability was

determined by system availability, which satisfied

the service level required. Furthermore, payment

system efficiency was enhanced through the

implementation of payment system infrastructure

that accelerated settlement for retail services

(National Clearing System - SKNBI) as well as the

introduction of liquidity-saving mechanisms for

high-value services (Bank Indonesia – Real Time

Gross Settlement (BI-RTGS) system and Bank

Indonesia – Scripless Securities Settlement System -

BI-SSSS). Such measures were bolstered by various

efforts to improve the operating performance of the

payment system, accompanied by risk mitigation.

This was achieved through policies and regulations,

infrastructure development as well as payment

system oversight. On par with the performance of

the payment system operated by Bank Indonesia,

the industry-operated payment system also

performed solidly, with no significant disruptions

reported in the settlement process combined with

an increase in transaction volume and value on the

previous period. Such developments were explained

5.1. Payment System Performance

by Bank Indonesia’s efforts to encourage and

promote the use of noncash payment instruments

in the national interest and to advance consumer

protection. Seeking to mitigate risk in the industry-

operated payment system, Bank Indonesia has

instituted payment system policies and regulations,

coordinated with institutions and the industry as

well as actively supervised the payment system.

As the payment system authority, Bank Indonesia

has promulgated regulations for the payment

systems operated by Bank Indonesia and the

industry. In the reporting period, Bank Indonesia

issued Bank Indonesia Circular Letter (SEBI) No.

18/42/DKSP concerning Nonbank Money Changers

as regulatory guidelines for Bank Indonesia

Regulation (PBI) No. 18/20/PBI/2016 on Nonbank

Money Changers, which was released to ensure

healthy and efficient nonbank money changers that

apply good governance principles.

In total, the payment system and securities

transaction systems operated by Bank Indonesia,

including the BI-RTGS system, BI-SSSS, National

Clearing System (SKNBI), and the industry-operated

retail payment system (card-based payment

instruments and e-money) accounted for 3,330,16

million transactions worth Rp87,466.17 trillion in


5.1.1. Payment System Operated by Bank

Indonesia

In the first semester of 2017, the payment system

operated by Bank Indonesia (high-value and retail

transactions) served 66.62 million transactions, up

2.88% on the 64.75 million in the previous semester.

Meanwhile, transaction value in the reporting

period totalled Rp84,391.70 trillion, increasing



Responds of Bank Indonesia’s Policy

Financial System InfrastructureBanking and IKNB

164 BANK INDONESIA


4.34% on the Rp80,877.87 trillion registered in the

same period one year prior. Solid payment system

performance was backed up by reliability and

availability in line with the service levels set, thereby

accommodating an increase in transaction volume

in terms of the high-value payment system (BI-

RTGS), securities settlement (BI-SSSS) and the retail-

value payment system (SKNBI). Service availability

achieved 100% of the 99.97% target in the

reporting period, denoting the availability, security

and reliability of the payment system, without any

significant disruptions or incidences in the critical

applications.

5.1.2. Industry Operated Payment System

In terms of the industry-operated payment system,

the number of instruments available as well as

the use of noncash payment instruments have

flourished, as indicated by the growing use of

card-based payment instruments and e-money on

the back of Bank Indonesia’s policies to stimulate

the use of noncash instruments. In addition, Bank

Indonesia has also coordinated with other payment

system providers to balance the infrastructure and

expand the instruments available. In the first half

of 2017, the industry-operated payment system

settled 3,263.14 million transactions with a value of

Rp3,152.19 trillion, representing a 9.45% increase

on the previous year.

In order to regulate and maintain payment system

availability, Bank Indonesia is also authorised to

supervise all licensed and approved payment

system operators as issuers of card-based payment

instruments and e-money. Oversight is conducted

through offsite supervision and onsite inspections. In

general, the scope of inspections includes regulatory

compliance, the implementation of specific

procedures, including Anti-Money Laundering and

Counter-Terrorism Financing (AML/CTF) as well as

internal control.

Table 5.1 BI-RTGS, BI-SSSS and SKNBI Performance

Bank Indonesia Noncash Payment System

Value Volume

Sem I 2016 Sem I 2017Δ (%)

Sem I 2016 Sem I 2017Δ (%)

(Rp, trillions) (Rp, trillions) (Transactions, millions) (Transactions, millions)

BI-RTGS 53,857.29 56,317.47 4.57% 2.96 4.77 61.26%

BI-SSSS 24,710.88 26,395.25 6.82% 0.15 0.14 -6.75%

SKNBI 2,309.69 1,678.99 -27.31% 61.64 61.71 0.10%

TOTAL 80,877.87 84,391.70 4.34% 64.75 66.62 2.88%


165BANK INDONESIA





Table 5.2 Card-Based Payment Instruments and Electronic Money Transactions

Value Volume

Sem I 2016 Sem I 2017Δ (%)yoy

Sem I 2016 Sem I 2017Δ (%)yoy

(Rp, trillions) (Rp, trillions) (Transactions, millions) (Transactions, millions)

Card-based Payment Instruments 2,876.75 3,147.43 9.41% 2,682.23 2,914.92 8.67%

ATM/debit cards 2,737.06 3,001.68 9.67% 2,533.02 2,752.56 8.67%

Credit Cards 139.70 145.75 4.33% 149.22 162.35 8.80%

Electronic Money 3.18 4.76 49.68% 308.10 348.22 -13.02%

TOTAL 2,879.92 3,152.19 9.45 2,990.33 3,263.14 11.36%

Financial transactions settled through the payment

system operated by Bank Indonesia increased in

the first half of 2017 in terms of value and volume.

Transactional developments through the BI-RTGS,

BI-SSSS and SKNBI are presented in Table 5.1.

Payment transaction settlement through the

Bank Indonesia – Real Time Gross Settlement (BI-

RTGS) system encompass monetary operations,

government transactions, transactions on behalf

of a customer, capital market and interbank money

market transactions, as well as interbank foreign

exchange transactions in rupiah, foreign exchange

transactions in rupiah between a bank and Bank

Indonesia and other transactions.

In the first semester of 2017, BI-RTGS transaction

value and volume increased on the same period

in the previous year (yoy). Nominally, transaction

value climbed 4.57% from Rp53,857.29 trillion to

5.2. Payment System Transactions

Rp56,317.47 trillion. On the other hand, transaction

volume soared 61.26% from 2.96 million to 4.77

million transactions.

Transactions between bank customers were the

main driver of the increase in transaction value and

volume settled through the RTGS system, with the

value increasing 16.60% or Rp1,633.07 trillion on

the Rp9,835.42 trillion recorded in same period one

year earlier and the volume soaring 91.98% or 1.87

million transactions on the 2.03 million registered in

the prior year1.

Payment system transactions through the Bank

Indonesia – Scripless Securities Settlement System

(BI-SSSS) also tracked an upward trend on the same

period one year earlier in terms of value despite

a decline in volume. BI-SSSS transaction volume

increased 6.82% from Rp24,710.88 trillion to

Rp26,395.25 trillion in the reporting period. On the

other hand, BI-SSSS transaction volume decreased

6.75% from 149.37 thousand transactions to

139.28 thousand over the same period.


1 The significant bump in BI-RTGS transaction volume, in terms of the total and between customers, compared to the same period one year earlier was the result of policy to lower the floor of RTGS

transactions from Rp500 million per transaction (since November 2015) to Rp100 million (since July 2016) in line with policies enforced post-implementation of the Second-Generation BI-RTGS

system. Compared to conditions in the second semester of 2016 (same flooring), with a total transaction volume of 4.70 million and transactions between customers standing at 3.78 million,

RTGS transaction volume increased in the first semester of 2017 by 1.49% and 2.98% respectively.

166 BANK INDONESIA


In terms of retail transaction services, transaction

activity through the National Clearing System (SKNBI)

in the first half of the year decreased in value but

increased in volume compared to conditions in the

same period one year earlier. Clearing transaction

value declined 27.31% from Rp2,309.69 trillion

to Rp1,678.99 trillion despite a 0.10% bump in

transaction volume, increasing from 61.64 million

to 61.71 million transactions, which was driven

primarily by credit clearing transactions between

clearing participants on behalf of their customers.

In contrast, debit clearing transactions experienced

declines in terms of value and volume, decreasing

by 24.65% and 22.58% respectively on the same

period in 2016.

Concerning the industry-operated payment system,

card-based payment instruments, namely ATM/

debit cards and credit cards, performed well on

stronger public consumption in the reporting period.

Nominally, card-based payment transactions posted

9.41% (yoy) gains to total Rp3,147.43 trillion,

while the volume grew 8.67% (yoy) to 2,914.92

million transactions in the first semester of 2017.

ATM/debit cards were the main contributor to

card-based payment growth, with the transaction

value and volume increasing by 9.67% (yoy) and

8.67% (yoy) respectively, while credit cards achieved

corresponding growth of 4.33% (yoy) and 8.80%

(yoy).

The growth of card-based payment instruments

was further bolstered by e-money, amounting to

Rp4.76 trillion in the first semester of 2017, with

transaction value and volume growing by 49.68%

(yoy) and 13.02% (yoy) respectively.

The uptake of card-based payment instruments

and e-money has remained in line with various

strategic payment system initiates, including the

electronification of noncash Social Assistance

disbursements, on-target energy subsidy

disbursements, noncash Village Fund disbursements,

as well as the electronification of public transport

systems in Jabodetabek along with vast sections of

toll road, in order to enhance economic efficiency.

Payment system policy is oriented towards

supporting the smooth and effective transmission

of monetary policy through efforts to ensure system

availability, while maintaining a high service level in

the Bank Indonesia Payment System (BIPS).

Striving towards greater national economic efficiency,

Bank Indonesia has issued policies to accelerate the

uptake of noncash transactions for public transportation

and toll roads in the Jabodetabek area in conjunction

with the Ministry of Public Works and Housing (PUPR).

A Memorandum of Understanding (MoU) concerning

coordination in the execution of duties at Bank Indonesia

and the Ministry of Public Works and Housing was

signed by Governor of Bank Indonesia, Agus D.W.

Martowardojo, and Minister of Public Works and

Housing, Basuki Hadimuljono, on Wednesday, 31st May

2017 to accommodate the coordinated electronification

of toll roads and implementation of the Multi-Lane

Free Flow (MLFF). The agreement represents a follow-

up measure to the Minimum Service Standards for

Indonesian toll roads pursuant to Ministerial Decree No.

16/PRT/M/2014, issued by the Minister of Public Works,

and was also signed to accelerate the uptake of e-money

towards the realisation of MLFF toll roads. Furthermore,

the electronification program is also expected to enhance

the toll road experience through greater transaction

convenience, shorter transaction times and reductions to

queueing times.

167BANK INDONESIA





5.3.1. MO Placements

MO placements are rupiah placements in the deposit

facility provided by Bank Indonesia under the

auspices of monetary operations. MO placements

are indicative of excess rupiah funds in the banking

system. Total MO placements by the banking

industry monitored through the BI-RTGS system

in the first half of 2017 fell 6% from Rp12,855.91

trillion to Rp12,094.26 trillion, reflecting tighter (but

normal) liquidity conditions in the banking industry.

5.3.2. Turnover Ratio – Excluding MO

Placements (TOR x MO)2

In the first semester of 2017, the value of TOR x MO

stood at 1.04, down 5% on the 1.10 recorded in

the second semester of 2016. The decline stemmed

5.3. Payment System Indicators

Graph 5.1 MO Placements

4,500

4,000

3,500

3,000

2,500

2,000

1,500

1,000

500

Trill

ion

Rp

Jan

Mar

May Ju

l

Sep

Nov Jan

Mar

May Ju

l

Sep

Nov Jan

Mar

May Ju

l

Sep

Nov Jan

Mar

May Ju

l

Sep

Nov Jan

Mar

May Ju

l

Sep

Nov Jan

Mar

May Ju

l

Sep

Nov Jan

Mar

May Ju

l

Sep

Nov Jan

Mar

May

2010 2011 2012 2013 2014 2015 2016 2017


from a decrease in banking industry transactions

after posting an increase in the prior period due to

the successful Tax Amnesty.

5.3.3. Queue Transaction3

In the first semester of 2017, a total of 33 transactions

were queued worth Rp3,210.60 billion. In terms of

volume, the queued transactions were equivalent to

0.0007% of total RTGS transactions or accounting

for just 0.0006% in terms of total RTGS transaction

value. Most queued transactions originated from

foreign banks, with a 63.23% share. The low

level of queued transactions demonstrates how

successfully liquidity risk was mitigated in the BI-

RTGS system. Additionally, all queued transactions

were subsequently settled on the same day. A

summary of queued transactions is presented in

Table 5.3.

2 TOR x MO is a comparison between outgoing transactions (excluding outgoing MO transactions) and the respective BI-RTGS participant’s opening balance. TOR x MO is used as a measure of

the participant’s relative ability to meet its payment system obligations. A value of > 1.00 indicates that the respective participant cannot meet its obligations using the opening balance alone

but would also require incoming transfers from another participant.3 Queued transactions are those that are queued in the Bank Indonesia – Real Time Gross Settlement (BI-RTGS) system due to insufficient funds at the respective bank to settle a transaction

when it is received. The transaction is, however, still settled on the same day.

168 BANK INDONESIA


Table 5.3 Queue Transaction

Month Frequency of Queued Transactions

Average Queue Time (minutes) Total Queued Funds (Rp)

Jan-17 2 20 menit 550,037,260,274

Feb-17 1 11 menit 93,231,637,066

Mar-17 6 17 menit 564,369,080,000

Apr-17 11 18 menit 496,039,499,946

May-17 5 32 menit 543,406,728,574

Jun-17 8 56 menit 963,519,220,735


Graph 5.2 Turnover Ratio x Monetary Operations

5.00

4.00

3.00

2.00

1.00

0.00

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

5.4.1. Settlement Risk4

Settlement risk was relatively well contained in the

first semester of 2017, as conveyed by the small

value and volume of unsettled transactions during

the window time of the BI-RTGS system.

In the reporting period, the total value of unsettled

transactions in the BI-RTGS system stood at

Rp4,180.22 billion, representing just 0.0074%

of the total. Likewise, only 65 RTGS transactions

were not settled, accounting for 0.0013% of the

7,657,448 total.

5.4. Payment System Risks and Mitigation Efforts

5.4.2. Liquidity Risk5

Liquidity risk in the payment system was also

well mitigated during the first semester of 2017.

Accordingly, Bank Indonesia received no requests

for the Intraday Liquidity Facility (ILF) or the Sharia

Intraday Liquidity Facility (SILF), which are funding

facilities provided by Bank Indonesia to participating

banks in the form of a securities repurchase

agreement. The Intraday Liquidity Facility is

available to participating banks upon approval

from Bank Indonesia and is provided automatically

when the account balance of a participating bank

is insufficient to execute its outgoing transactions.

The ILF is subsequently settled automatically upon

receipt of incoming transactions.

4 From a participant’s perspective, settlement risk could emerge due to late and failure-to-settle payment transactions while waiting for incoming transfers from other participants. From

the operator’s perspective, however, settlement risk is not considered possible because RTGS participants apply the no money-no game principles, where settlement transactions are only

processed if sufficient funds are available.5 Liquidity risk occurs in the payment system when an RTGS participant has insufficient funds to meet its obligations on time despite potentially fulfilling those liabilities in the subsequent

window time.

169BANK INDONESIA





6 Operational risks originate from operating factors, including system and network issues.7 Systemic risk is the risk of default at one or more financial institutions due to systemic events in the form of shocks that impact one or more institutions and then propagate through

contagion or shocks that simultaneously affect several large institutions (De Bandt and Hartmann, 2000, and Zebua, 2010, in the Monetary and Economic Bulletin, October 2013).

The lack of ILF/SILF requests from noncash

payment system participants received by Bank

Indonesia demonstrated that no participating

banks experienced a short-term funding shortfall in

the first semester of 2017 caused by a mismatch

between the incoming and outgoing transactions.

5.4.3. Operational Risk6

Under the auspices of operational risk management,

Bank Indonesia periodically checks the preparedness

of BI-RTGS, BI-SSSS and SKNBI infrastructure.

Furthermore, Bank Indonesia has a Business

Continuity Plan (BCP) in place to mitigate the

operational risk, which includes providing a backup

system that is on continuous standby to fully replace

the primary production system as required.

In the first semester of 2017, adjustments were

made to the backup systems of BI-RTGS, BI-SSSS

and SKNBI at the Disaster Recovery Centre (DRC).

Congruent with second-generation BI-RTGS, BI-

SSSS and SKNBI implementation, testing and partial

trials of the backup systems were conducted twice

in the reporting period, in March and May 2017.

Moreover, the infrastructural preparedness of the

Backup Front Office (BFO) was also tested in May

2017, while the Information Technology Recovery

Plan (ITRP) underwent testing in March, April and

August 2017.

Anticipating and mitigating the threat of malicious

software (malware), particularly ransomware, in

the BI-RTGS, BI-SSSS, BI-ETP and SKNBI systems,

a number of measures were taken during the

reporting period on the operator and participant

sides, including updating to the latest versions of

the antivirus software along with installing Windows

Table 5.4 Core Banks in the BI-RTGS System

Bank # of Counterparties Value (Rp)

Private National Commercial Bank

40 182,851,844,486,495

Regional Bank 47 83,549,500,000,000

State-Owned Bank 49 73,182,956,733,333

Regional Bank 42 61,607,000,000,000

Foreign Bank 22 49,684,000,000,000

Regional Bank 39 47,613,000,000,000

State-Owned Bank 49 45,477,839,355,723


36 42,408,000,000,000

Regional Bank 24 42,005,000,000,000


41 41,629,000,000,000

security patches, while also testing the environment

development and simulating transactions, which

began in May 2017.

5.4.4. Systemic Risk7

Systemic risk is the risk of default at one or more

banks due to systemic events. In the financial

system, systemic risk can be measured by the

interconnectedness of RTGS participants and

observed from the number of counterparties to

each respective participating bank. A larger number

of counterparties implies greater risk. During the

first half of 2017, a total of 10 core banks of the

interbank money market were monitored in the BI-

RTGS system as presented in Table 5.4.

If a systemically important bank (SIB) were to default

on settlement, the impact could affect settlement

at other interconnected banks and, thus, potentially

disrupt financial system stability. Addressing that

issue, Bank Indonesia constantly monitors any

entities with a high level of interconnectedness

as part of the central bank’s efforts to maintain

financial system stability.

170 BANK INDONESIA


8 The Sarma method uses three dimensions of financial inclusion as follows:

i. Availability, which is represented by two variables, namely total bank branches as well as total ATMs that are combined with the total number of DFS agents. The two variables are divided

per 100,000 adults and 1,000km2 (based on a review considering the area of Indonesia, the area was adjusted from 1 to 100km2, thus becoming 1,000m2);

ii. Penetration, which is measured using total number of accounts per 1,000 residents. The total is represented by total credit value and total deposit value;

iii. Utilisation, which is measured using the ratio of total credit value to total Gross Domestic Product (GDP) at prevailing prices and the ratio of total deposit value to total Gross Domestic

Product (GDP) at prevailing prices.

The Sarma (2012) method uses an index value of between 0 and 1. The index is divided into three categories, namely 0-0.3 (low), 0.3-0.6 (medium) and 0.6-1 (high). Therefore, a higher

financial inclusion index (approaching 1) indicates a higher level of financial inclusion (complete financial inclusion) in the corresponding country.

5.5.1. Indonesia Financial Inclusion

Composite Index (IKKI)

One benchmark of financial inclusion is the

Financial Inclusion Index, which is calculated using

several methods that vary from country to country

and influenced by geographical factors, public

awareness and regional infrastructure availability.

When calculating the Financial Inclusion Index,

Bank Indonesia applies the Sarma method8.

Using the Sarma (2012) method, the Financial

Inclusion Index for Indonesia in June 2017 was

considered medium, namely 0.45 or 45% (Graph

5.3), rising 9.78% on the position recorded in

5.5. Financial Inclusion and Digital Financial Services

0.500

0.450

0.400

0.350

0.300

0.250

0.200

Jan

Feb

Mar Ap

r

May Jun Jul

Aug

Sep

Oct

Nov De

c

Jan

Feb

Mar Ap

r

May Jun Jul

Aug

Sep

Oct

Nov De

c

Jan

Feb

Mar Ap

r

May Jun Jul

Aug

Sep

Oct

Nov De

c

Jan

Feb

Mar Ap

r

May Jun

2014

(Index Value)

2015 2016 2017

Graph 5.3 Indonesia Financial Inclusion Composite Index (IKKI)

Source: Financial Inclusion and Electronification Data, Semester II – 2016

December 2016, indicating that public access

and uptake of financial services in Indonesia

has historically tracked an upward trend despite

remaining in the medium bracket.

The index gains have stemmed from greater

financial access afforded by financial institutions,

by expanding the range of financial services

available to the public that facilitate financial

transactions. This has primarily been achieved

by increasing the number and distribution of

DFS agents that provide public access to formal

financial services. In addition, the increase has

also been facilitated by ongoing socialisation and

education activities provided by Bank Indonesia

in conjunction with the banking industry as

well as the relevant government ministries and

institutions.

171BANK INDONESIA





5.5.2. Digital Financial Services (DFS)

The spread of digital financial services (DFS) in Indonesia

has accelerated on the back of an increasing number

of DFS bank providers, DFS agents, DFS customers

and e-money transactions at DFS agents.

i. DFS Providers. Bank Indonesia has licensed

five DFS bank providers, namely BRI, Bank

Mandiri, BNI, CIMB NIAGA and BCA as well as

one nonbank institution, namely PT Telkomsel.

Based on coverage area, BRI enjoys the greatest

distribution of DFS agents, covering 469

regencies/cities, followed by Bank Mandiri

that provides DFS agents in 451 regencies/

cities. In contrast, CIMB Niaga has DFS agents

in three regencies/cities and BCA is currently

concentrating on Jakarta.

ii. DFS Agents. The number of DFS agents soared

19.96% at the end of the first semester of 2017,

increasing from 133,811 in December 2016 to

160,524 in June 2017. The total in June 2017

Figure 5.1 DFS Agents in Indonesia

14 Digital Finance Service Agents in 3 Regencies/ Cities

2 Agents of Digital Finance Service in 1 Regencies/ Cities

53,325 Digital Finance Service Agents in 451 Regencies/ Cities

Source: Bank Indonesia, June 2017, processed

107,183 Digital Finance Service Agents in 469 Regencies/ Cities

consisted of 145,927 Individual Agents and

14,597 business agents. Individual agents include,

small grocery shops/stalls, telephone credit sellers,

pharmacies, restaurants and payment point online

bank (PPOB), while business agents are comprised of

retailers, businesses, pawn brokers and cooperatives.

iii. Transactions at DFS Agents. In the first semester

of 2017, person-to-account transfers from e-money

accounts to non-e-money accounts dominated

customer transactions at DFS agents, accounting

for 36%, followed closely by cash withdrawals at

35%. The number of e-money accounts opened by

the public at DFS agents has followed an upward

trend, reaching 1,242,145 account holders with a

total value of Rp30 billion and 286,077 e-money

transactions in the first half of 2017. To further

promote the uptake of e-money and expand the

other transactions processed through DFS agents,

various public socialisation and education efforts

have continued.

172 BANK INDONESIA


Graph 5.5 Percentage of E-Money Transactions at DFS Agents

Person-to-Account Transfer

Initial

Top Up

Cash Withdrawal

Payment

Person-to-Person Transfer

Jun-17 1,242,145

May-17 1,242,308

Apr-17 1,242,494

Mar-17 1,242,811

Feb-17 1,243,565

Jun-17 1,241,571

Dec-16 1,244,102

Nov-16 1,240,849

Oct-16 1,238,128

Sep-16 1,235,169

Aug-16 1,231,729

Jul-16 1,227,684

Jun-16 1,226,126

Graph 5.6 E-Money Account Holders at DFS Agents (millions)

Graph 5.4 Total DFS Agents in 2017

165,000(Agents)

160,000

155,000

150,000

145,000

140,000

135,000

130,000

Jan Feb Mar Apr May Jun

Period 2017 Individual Agents Business Agents

Jan 125,679 15,064

Feb 131,117 14,933

Mar 135,377 14,491

Apr 139,452 14,302

May 142,339 14,312

Jun 145,927 14,597

Table 5.5 Total Individual and Business DFS Agents in 2017



5.5.3. Financial Inclusion and Electronification

As part of Bank Indonesia’s commitment to support

the National Financial Inclusion Strategy and the

National Noncash Movement (GNNT) to promote

greater use of noncash payment instruments

towards a less cash society, Bank Indonesia has

designed and rolled out various non-cash programs

and initiatives. The noncash movement aims to

upgrade all payment methods from physical to

digital, which is expected to precipitate numerous

benefits as follows: (i) more practical transactions;

(ii) broader public access; (iii) more transparent

transactions; (iv) reducing the costs of rupiah

currency management and cash handling; (v)

creating less economic friction, namely to reduce

spikes in the circulation of currency that increase

36%

35%3%

5%

5%

16%

money supply and, therefore, edge up inflation; (vi)

more accurate economic planning through more

complete and comprehensive transaction record

keeping; and (vii) enhancing good governance

because all data is recorded and stored.

Bank Indonesia always promotes and participates

in efforts to increase noncash transactions in order

to expand financial access as well as enhance

the efficiency, effectiveness and accountability of

financial management by the government, business

community and public in general. Various noncash

movement programs have been implemented

or are under development by Bank Indonesia in

conjunction with the relevant government ministries

or institutions as follows:

15.47%

173BANK INDONESIA





a. Electronification of social assistance

disbursements, namely to change the

disbursement method for social assistance

payments from cash to noncash (electronic)

means through the bank agent system, thereby

expanding financial access. Bank Indonesia

constantly seeks to increase noncash social

assistance disbursements through the Family

Hope Program and Noncash Food Assistance

Program by the Ministry of Social Affairs

through the Association of State-Owned

Banks (Himbara). The noncash social assistance

programs use family welfare cards, currently

available in 44 regencies/cities for the Noncash

Food Assistance Program and 68 regencies/cities

for the Family Hope Program. Furthermore,

noncash social assistance disbursements are

accompanied by financial education and

monitoring activities involving 28 regional Bank

Indonesia representative offices. The Noncash

Food Assistance Program was transformed from

the erstwhile Rice for The Poor program, which

previously offered assistance in the form of rice

but now provides money for groceries. The

program was launched by the President of the

Republic of Indonesia on 23rd February 2017.

Although not perfect, efforts to transform

social assistance disbursements have borne

significant successes. In the second semester of

2016, social assistance disbursements through

the Family Hope Program reached 1.2 million

families, which then increased significantly to

around 6 million families in the first semester

of 2017, representing nearly 100% of all

program beneficiaries. Regarding the Noncash

Food Assistance Program, 1.2 million low-

income families received disbursements at the

beginning of 2017, accounting for 7.7% of all

Rastra beneficiaries. Both programs, however,

shall be extended to 10 million families.

Meanwhile, social assistance in the form of the

Smart Indonesia Program has been disbursed

since 2016 to 100% of students. Furthermore,

Bank Indonesia, along with the Ministry of

Education and Culture, has disbursed School

Operational Assistance (BOS) in eight pilot

regions, namely Palembang, Bogor, Bandung,

Surabaya, Semarang, Samarinda, Makassar and

Mataram.

b. Various programs to expand the electronification

of payment and receipt transactions have also

been rolled out in conjunction with relevant

government ministries and institutions,

including the following:

1) Village Fund Electronification

Electronification of the Village Fund was

pioneered by Bank Indonesia through trials

and pilot projects in Sindangjawa village,

Cirebon, commencing in May 2016. The

pilot project applied the Cash Management

System (CMS), which is an internet banking-

based application for account-to-account

transfers. The CMS application was used

during the trials to support noncash

payments related to village development and

public empowerment, including the purchase

of materials, teacher honoraria, training,

foreman wages and operational spending

(office stationary, food and beverages for

meetings).

Monitoring of the pilot project showed

that electronification increased village fund

budget management transparency at the

local government level. Considering the

174 BANK INDONESIA


overwhelmingly positive response from the

Village Administration and lack of significant

constraints using the CMS application, Bank

Indonesia plans to expand the noncash village

fund pilot project to other areas. In addition,

Bank Indonesia has also developed various

business models for villagers in conjunction

with the Ministry of Villages, Underdeveloped

Regions and Transmigration, which will

stimulate expansion of the noncash

ecosystem in rural areas. To that end, Bank

Indonesia is coordinating with the relevant

government ministries and institutions,

including the Ministry of Home Affairs,

Ministry of Finance as well as the Ministry

of Villages, Underdeveloped Regions and

Transmigration.

2) Toll Road Electronification

In April 2016, the President of the Republic

of Indonesia insisted that queues at toll gates

must become a thing of the past through more

efficient toll road payment transactions. All

transactions must, therefore, be processed using

sensory technology that is connected directly

to a respective bank account. Acting upon

this directive, Bank Indonesia, as the payment

system authority, in conjunction with the

Ministry of Public Works and Housing (PUPR),

as the toll road authority, agreed to the gradual

electronification of the toll roads pursuant

to a Memorandum of Understanding (MoU)

signed on 31st May 2017. The implementation

phases are as follows: (i) electronification of

the toll roads, namely the use of e-money

on 100% of the toll roads by October 2017;

(ii) integrated tariffs and toll gates, namely by

eliminating superfluous toll gates under the

management of different operators, thereby

only tapping once upon exit of the toll road;

(iii) toll road integration with the Electronic

Toll Collection (ETC) consortium, which would

integrate a multi-issuer payment system; and

(iv) implementation of the multi-lane free flow

system, namely contactless payments with or

without barrier gates by the end of 2018.

To achieve the target of 100% toll road

electronification by October 2017, various

relevant parties, including Bank Indonesia,

the Toll Road Regulatory Agency (BPJT),

Toll Road Operators (BUJT) and the banking

industry, initiated a noncash socialisation and

education campaign in May 2017 through

different communication media and along

the existing toll roads. The strategic measures

successfully spurred a significant increase in

the share of noncash transactions recorded

on the toll roads, increasing from 16.4% in

January 2016 to 28% in June 2017 and 30%

in July 2018.

During Eid-ul-Fitr, Bank Indonesia, the Toll

Road Regulatory Agency (BPJT), Toll Road

Operators (BUJT) and the banking industry

integrated the socialisation campaign locally

and nationally, which further boosted the

penetration of noncash transactions on toll

roads in Jabodetabek to 33% in June 2017,

indicating growing public awareness of the

benefits of noncash transactions on the toll

roads, in particular using e-money.

175BANK INDONESIA





3) Remittances

Seeking to improve the welfare of

Indonesian migrant workers (TKI) and

their families, primarily through efforts to

enhance the efficiency and effectiveness

of the remittance mechanism, Bank

Indonesia has simultaneously developed

remittance business models and a digital

financial services (DFS) ecosystem for the

community of beneficiaries of remittance

payments. Bank Indonesia is trying to

change the previous remittance system

from Indonesian migrant workers, who

sent as cash to cash, towards a cash-to-

account system. Thus far, Bank Indonesia

has developed five business models as

follows: (i) mobile phone to mobile phone;

(ii) agent to agent; (iii) ATM deposits; (iv)

host to host; and (v) post office to post

office. Meanwhile, for the beneficiaries of

remittance payments, namely the families

of Indonesian migrant workers (TKI),

Bank Indonesia has developed remittance

receipts in the form of e-money through

DFS agents. To test the newly developed

business models and understand the

constraints in the field that might be faced,

pilot projects are currently underway in

conjunction with several operators.

4) Electronification of Local Government

Transactions

Striving to improve regional financial

management accountability and transparency,

the Ministry of Home Affairs issued Circular

Letter No. 910/1866/SJ and No. 910/1867/SJ

concerning the implementation of Noncash

Transactions in Provincial Governments and

Regional Administrations, dated 17th April

2017. The circulars were a follow-up measure

to Presidential Instruction No. 10 of 2016 on

Corruption Prevention and Eradication Measures

in 2016 and 2017, one of which included

the Acceleration of Noncash Transaction

Implementation at all Government Ministries/

Institutions and Local Governments.

Acting on the initiative, Bank Indonesia

coordinated with the Ministry of Home

Affairs and Ministry of Finance to expedite

the Implementation of Noncash Transactions

at Provincial Governments and Regional

Administrations. Consequently, local

governments were compelled to introduce

noncash payments and receipts by 1st January

2018. Furthermore, as the payment system

regulator, Bank Indonesia shall ensure the

availability of secure, efficient and reliable

payment system infrastructure services to

support the realisation of noncash transactions

at Provincial Governments and Regional

Administrations.

176 BANK INDONESIA


176 BANK INDONESIA

As an open economy, Indonesian residents demand

money changing services, not only large corporations

but also individuals and small businesses. Money

changing services are offered by banks as well as

nonbanks as money changers.

Additionally, money changing services are also very

much required by the influx of overseas travellers

visiting the Indonesian archipelago in order to spend

money in rupiah currency pursuant to Act No. 7

of 2011 concerning Mandatory Rupiah Use in the

Territory of the Republic of Indonesia, the violation

of which would incur a fine of up to Rp200 million

and a maximum custodial sentence of one year.

Furthermore, money changers are also sought by

local travellers wishing to visit overseas for tourism,

business or worship.

Against that backdrop, the business opportunity for

money changers is vast. Unfortunately, however,

many pursued shortcuts by establishing money

changing businesses without acquiring the requisite

license from Bank Indonesia. Based on the evidence

in the field, a lot of unlicensed money changers were

abusing their authority. Media reports emerged

of money changers being used to launder money

linked to narcotics, terrorism and corruption, which

had an adverse impact on the public, economy and

national image.

Pursuant to Bank Indonesia Regulation (PBI)

No. 18/20/PBI/2016, dated 3rd October 2016,

concerning Nonbank Money Changers, Bank

Indonesia afforded all money changers the

opportunity to apply for a license before 7th April

2017. From October 2017 2016 – April 2017, Bank

Indonesia also undertook widespread socialisation

activities, advising money changers to cease trading

and apply for the appropriate license. Furthermore,

Bank Indonesia also disseminated information in

conjunction with the Criminal Investigation Agency

(Bareskrim), National Narcotics Agency (BNN) and

Indonesian Financial Transaction Reports and

Analysis Centre (INTRAC) through various print and

online media. Bank Indonesia also coordinated with

various other institutions, including the judiciary,

Ministry of Trade, Ministry of Law and Human

Rights as well as several associations, such as the

Indonesian Notary Association, Indonesia Shopping

Centre Association (APPBI), Indonesian Hotel and

Restaurant Association (PHRI), Indonesia Travel

Agent Association (ASITA), Association of Foreign

Exchange Traders (APVA) and PD Pasar Jaya.

Based on mapping by Bank Indonesia, a total of 783

unlicensed money changers were identified on the

islands of Java, Sumatra, Bali and Nusa Tenggara,

Kalimantan as well as Sulawesi, Maluku and Papua

(Sulampua). After 7th April 2017, Bank Indonesia

required the unlicensed money changers to sign a

cease and desist order as well as affix a sticker on

their premises indicating that the business had been

closed by Bank Indonesia. The crackdown on illegal

money changers was implemented in two stages as

follows:

a. Policing began in 10 areas. Bank Indonesia

cooperated with the Criminal Investigation

Agency (Bareskrim) to control unlicensed money

Box 5.1. Unlicensed Nonbank Money Changers





177BANK INDONESIA

changers still in operation. The first stage of the

policing ran from 9th April – 5th May 2017, with

262 money changers facing forced closures in

areas with a Bank Indonesia presence, namely

Jabodetabek, West Sumatra, Pematang Siantar,

North Sumatra, Yogyakarta, Central Java, Solo,

Jember, Bali and West Nusa Tenggara.

b. The second phase began on 15th May

2017, executed by 20 supervisors from Bank

Indonesia representative offices with local

police assistance. As of August 2017, a total

of 698 money changers had faced forced

closures, representing around 80% of the initial

mapping. Therefore, around 162 illegal money

changers will continue to be pursued through

to the end of 2017.

In general, the unlicensed money changers were

primarily in the form of pure money changers, gold

merchants, grocery stores, electronic goods stores,

tour and travel businesses, restaurants, hotels and

other businesses. Furthermore, the crackdown

revealed a counterfeiter of money changer licenses,

licensed money changers selling branch office

licenses, unlicensed branch offices as well as money

changers failing to display their identities and the

official logo.

To identify a licensed money changer, one only

needs to look at the signage, license certificate

issued by Bank Indonesia and logo. To mitigate

the falsification of the official logo, Bank Indonesia

applied a number of security features, including a

license number to check the legality of the head

office or branch offices, the statement “supervised

by Bank Indonesia”, contact information for

consumer protection services along with a QR Code

that allows the user to check the status of the

money changer using a smartphone.

178 BANK INDONESIA


The puppeteer is the leader, the writer, producer, narrator and puppet master. When operating the

puppets, the puppeteer must direct the other performers, thus the success of the performance depends

on the puppeteer. Like the puppeteer, as the macroprudential policy authority, Bank Indonesia must play

a significant role in financial system stability, from preparing assessments and promulgating policies to

evaluating the policies issued. The macroprudential policies of Bank Indonesia are expected to maintain

financial system stability.

179BANK INDONESIA





0505

With a macroprudential mandate, Bank Indonesia constantly strives to identify financial

sector behaviour in order to strengthen the policy framework and maintain financial

system stability. Bank Indonesia’s macroprudential policy in the first semester of 2017

remained accommodative and countercyclical in response to prevailing financial system

developments, while remaining vigilant of the global and domestic economic risks.

During the first half of 2017, Bank Indonesia made regulatory refinements to the short-

term liquidity loan, set the countercyclical capital buffer (CCyB) and evaluated the RR-

loan to funding ratio (RR-LFR). Such macroprudential policies became an integral part of

Bank Indonesia’s overall policy mix, combined with monetary and payment system policy

as well as rupiah currency management. In addition to the policy response, financial

system stability was also maintained through efforts to strengthen coordination synergy

between Bank Indonesia and other relevant authorities in order to bolster the existing

bilateral coordination and cooperation framework instituted by Bank Indonesia in the

execution of its tasks, duties and jurisdiction in terms of monetary, macroprudential and

payment system policy as well as rupiah currency management.

BANK INDONESIA’S POLICY RESPONSE BACKING FINANCIAL SYSTEM STABILITY

06


180 BANK INDONESIA

ACCOMMODATIVE AND COUNTERCYCLICAL MACROPRUDENTIAL POLICY WAS MAINTAINED IN RESPONSE TO FINANCIAL SYSTEM DYNAMICS AND RISKS

Policy Response

The short-term liquidity loan was improved through promulgation of a Bank Indonesia Regulation (PBI) and Board of Governors Regulation issued to optimise the lender of last resort (LOLR) function, which is part of Bank Indonesia’s role to support financial system stability.

Concerning the evaluation of the loan-to-value (LTV) ratio and financing-to-value ratio (FTV), Bank Indonesia made no adjustments to the existing LTV/FTV requirements.

Bank Indonesia will publish a Financing Funding Ratio to replace the Loan-to-Funding Ratio (LFR). The policy aims to encourage the banking industry to purchase corporate bonds as an alternative when disbursing financing and to stimulate the real sector, thus catalysing national economic growth while adhering to prudential principles.

Regulatory Refinements to the Short-Term Liquidity

Loan

Evaluation of LTV/FTV Requirements

Evaluation of the RR-Loan to Funding Ratio (RR-LFR)

The Financial System Crisis Prevention and Mitigation (PPKSK) Act provides a solid foundation for the four institutional members of the Financial System Stability Committee to maintain financial system stability. Furthermore, Bank Indonesia also maintains bilateral coordination with the Financial Services Authority (OJK) and Deposit Insurance Corporation (LPS) to coordinate within the Financial System Stability Committee framework.

Policy Coordination between Bank Indonesia and other

Relevant Authorities

After an evaluation, Bank Indonesia decided to maintain the countercyclical capital buffer (CCyB) at 0%, unchanged from the evaluation in May 2017.

Maintaining the Countercyclical Capital

Buffer (CCyB) at 0%





181BANK INDONESIA

The lender of last resort (LOLR) function is an

integral part of Bank Indonesia’s role to support

financial system stability, which translates into the

provision of a short-term liquidity loan available to

banks experiencing a short-term liquidity shortfall

in accordance with the Bank Indonesia Act and

emphasised in the Financial System Crisis Prevention

and Mitigation (PPKSK) Act issued in 2016.

The LOLR function is required to prevent and

mitigate instability in the financial system triggered

by a liquidity shortfall experienced by a bank that

could spill over through the contagion effect and

adversely impact the financial system and, ultimately,

the economy. Under normal conditions, banks

typically meet the liquidity requirements through

access to available sources of funds, including the

interbank money market and monetary operations

by Bank Indonesia. In the event that such sources

are unavailable or fail to meet the respective bank’s

requirements, the bank in question may request a

short-term liquidity loan at Bank Indonesia as lender

of last resort (LOLR).

Bank Indonesia always adheres to prudential

principles when providing the short-term liquidity

loan, which represents a loan or financing. Based

on the provisions of the Bank Indonesia Act and


(PPKSK) Act, the main principle that Bank Indonesia

must adhere to is that the recipient bank must be

illiquid but solvent. Furthermore, given the inherent

credit risk of the short-term liquidity loan, the Bank

Indonesia Act and Financial System Crisis Prevention

and Mitigation (PPKSK) Act also stipulate high quality

6.1. Refining the Short-Term Liquidity Loans

collateral in the form of liquid and highly rated

securities as well as current loan assets. In addition,

coordination with the Indonesian Financial Services

Authority (OJK) is also essential when disbursing the

short-term liquidity loan in relation to: (1) assessing

whether the requirements of the short-term liquidity

loan have been met; and (2) supervising the recipient

bank to ensure the utilisation and repayment of the

liquidity loan are consistent with the agreement.

Underlying implementation of the short-term

liquidity loan, the provisions contained in the Bank

Indonesia Act and Financial System Crisis Prevention

and Mitigation (PPKSK) Act are also regulated in

more detail in corresponding regulations issued by

Bank Indonesia.

Bank Indonesia refined the prevailing short-term

liquidity loan regulations in 2017 by promulgating a

new Bank Indonesia Regulation (PBI) and Board of

Governors Regulation that superseded the existing

provisions released in 2012 and 2013. The main

differences between the old and new regulations are

as follows:

1. Regulatory harmonisation and alignment with

the Financial System Crisis Prevention and

Mitigation (PPKSK) Act:

a. The term “short-term funding facility” or

“sharia short-term funding facility” were

replaced by “short-term liquidity loan” or

sharia short-term liquidity financing”;

b. The requirements for eligible recipient

banks were adjusted to: (i) solvent banks;

(ii) with a composite soundness rating of no

less than 2 (two); (iii) access to high-quality

collateral as a guarantee for the short-term

liquidity loan that meets the requirements

stipulated in the corresponding Bank

Indonesia Regulation (PBI); and (iv) deemed

to have sufficient repayment capacity;

182 BANK INDONESIA


c. Contains coordination between Bank

Indonesia and the Financial Services

Authority (OJK) when disbursing the

short-term liquidity loan as follows: (i)

an evaluation of whether the short-term

liquidity loan requirements have been met;

(ii) supervision of the recipient bank to

monitor and ensure loan utilisation is as

agreed, the loan is repaid in accordance with

the agreed repayment plan and the specific

requirements have been met throughout

the loan period; and (iii) collateral execution;

2. Refinements to the collateral requirements,

with the inclusion of Bank Indonesia Certificates

of Deposit (SDBI) as an acceptable form of

collateral, as well as refinements to the criteria

of securities and credit/financing assets;

3. Refinements to the application and disbursement

mechanisms along with maturity extension,

raising or lowering the credit ceiling, reporting

responsibilities, repayment and collateral

execution.

4. Adjustments to the pricing of the short-term

liquidity loan. The previous margin of 100bps

on top of the lending facility rate applicable to

a commercial bank was raised to 400bps. For

Islamic banks, the nisbah on profit sharing was

lowered from 90% to 80%.

5. Refined the limitations and restrictions on

business activities during the short-term liquidity

loan period or the period until the loan has been

repaid; and refining the penalties and sanctions.

Meanwhile, the Board of Governors Regulation on

the short-term liquidity loan further regulated the

provisions necessary according to the Bank Indonesia

Regulation (PBI), emphasising the technical aspects

of the principles contained in the PBI. A list of Bank

Indonesia Regulations (PBI) and Board of Governors

Regulations concerning the short-term liquidity

loan issued by Bank Indonesia in 2017 is as follows:

1. Bank Indonesia Regulation (PBI) No. 19/3/

PBI/2017 concerning the Short-Term Liquidity

Loan for Commercial Banks (PBI PLJP);

2. Bank Indonesia Regulation (PBI) No. 19/4/

PBI/2017 concerning the Short-Term Liquidity

Loan for Islamic Banks (PBI PLJPS);

3. Board of Governors Regulation No. 19/6/

PADG/2017 concerning the Short-Term Liquidity

Loan for Commercial Banks (PADG PLJP); and

4. Board of Governors Regulation No. 19/8/

PADG/2017 concerning the Short-Term Liquidity

Loan for Islamic Banks (PADG PLJPS);

Bank Indonesia continuously reviews the new

regulations in light of the latest developments

regarding the short-term liquidity loans to ensure

that the content of the regulations remains up to

date and relevant with prevailing conditions, while

also adhering to prudential principles and good

governance.

183BANK INDONESIA





Maintaining accommodative macroprudential policy

against a backdrop of sluggish economic dynamics

and bank intermediation, Bank Indonesia upheld

the countercyclical capital buffer (CCyB) at 0% in

May 2017 based on first quarter data. The CCyB

was held at 0% because no signs of excessive credit

growth were identified that could trigger systemic

risk, as confirmed by the leading indicator, namely

the credit-to-GDP gap. In addition, the supporting

indicators further corroborated such economic

dynamics, consisting of macroprudential indicators,

macroeconomic indicators, banking indicators and

asset prices.

CCyB policy was introduced in January 2016 to

reduce procyclicality in the banking industry as

a source of economic vulnerability, where banks

tended to pursue expansive policies during an

economic upswing and contractive policies during

a downturn or recession. Bank Indonesia regularly

reviews and evaluates the magnitude and activation

period of the CCyB, no less than once every six

months, paying due consideration to the leading

indicator, supporting indicators and professional

judgement.

Leading Indicator

The leading indicator used when evaluating CCyB

policy is the credit-to-GDP gap, showing the disparity

between the credit-to-GDP ratio and its long-term

trend, which indicated that credit supply is still

required to stimulate economic growth. Congruent

with economic growth that reached 5.01% (yoy) in

6.2. Maintaining the Countercyclical Capital Buffer (CCyB) at 0%

the first semester of 2017, credit growth increased

by 1.38% to 9.24% (yoy) from 7.86% (yoy) in

the previous period. Such conditions were not

consistent with excessive credit growth that could

spur systemic risk, as evidenced by the credit-to-

GDP gap which indicated low risk of excessive credit

growth. Determining the magnitude of the CCyB as

well as when to activate refers to an upper (H) and

lower (L) threshold, namely 6 and 3 respectively1.

Consequently, a CCyB of 0% was recommended in

the reporting period based on the leading indicator.

Supporting Indicators

After reviewing the data from the leading indicator,

Bank Indonesia assessed the supporting indictors to

backup and complement the existing information.

(i). Macroprudential Indictors

The financial cycle of Indonesia (SKI) remained in

a contractionary phase during the first semester

of 2017 (Graph 6.3), attributable to sluggish

credit growth as the dominant component of

the financial cycle. The slowdown, however, is

also indicative of the low risk of excessive credit

growth that could potentially trigger systemic risk.

(ii). Macroeconomic Indicators

In general, the macroeconomic indicators

showed that more support is required to

stimulate credit growth in the banking

industry for the economy to post further

gains. For example, GDP growth, as one of

the macroeconomic indicators used, increased

slightly in the first quarter of 2017 to 5.01%

(yoy) from 4.94% (yoy) in the fourth quarter of

2016. Inflation also tracked an upward trend

over the same period, rising from 3.02% to

3.61% as a result of hikes to administered prices

(AP), such as vehicle registration renewals, fuel

1 For a detailed explanation of the upper and lower thresholds, refer to FSR No. 24, March 2015.

184 BANK INDONESIA


prices and electricity rates. Notwithstanding

the pressures, inflation remained under control

and within the inflation target of 4.0±1%. On

average, the rupiah depreciated early in the first

quarter of 2017 compared to conditions at the

end of 2016 but steadily rebounded in February

and March 2017 on the back off an influx of

foreign capital flows after Indonesia’s sovereign

Graph 6.1 Credit-to-GDP Gap

2004

Q3

2005

Q1

2005

Q3

2006

Q1

2006

Q3

2007

Q1

2007

Q3

2008

Q1

2008

Q3

2009

Q1

2009

Q3

2010

Q1

2010

Q3

2011

Q1

2011

Q3

2012

Q1

2012

Q3

2013

Q1

2013

Q3

2014

Q1

2014

Q3

2015

Q1

2015

Q3

2016

Q1

2016

Q3

2017

Q1

10

8

6

4

2

0

-2

Risk of Excessive Credit Growth

Low Risk of Excessive Credit Growth

High Risk of Excessive Credit Growth

Credit-to-GDP Gap L Threshold H Threshold Crisis

credit rating outlook was upgraded. Meanwhile,

the position of private external debt at the end

of the first quarter of 2017 also moderated

on the previous period. Consequently, the

macroeconomic indicators generally pointed to

the need for further support to stimulate bank

lending in order to catalyse stronger economic

growth.

Graph 6.2 CCyB Rate per the Leading Indicator

2.50

2.00

1.50

1.00

0.50

0.00

2004

Q3

2005

Q1

2005

Q3

2006

Q1

2006

Q3

2007

Q1

2007

Q3

2008

Q1

2008

Q3

2009

Q1

2009

Q3

2010

Q1

2010

Q3

2011

Q1

2011

Q3

2012

Q1

2012

Q3

2013

Q1

2013

Q3

2014

Q1

2014

Q3

2015

Q1

2015

Q3

2016

Q1

2016

Q3

2017

Q1



185BANK INDONESIA





Graph 6.3 Financial Cycle of Indonesia

1994

Q1

1994

Q4

1995

Q3

1996

Q2

1997

Q1

1997

Q4

1998

Q3

1999

Q2

2000

Q1

2000

Q4

2001

Q3

2002

Q2

2003

Q1

2003

Q4

2004

Q3

2005

Q2

2006

Q1

2006

Q4

2007

Q3

2008

Q2

2009

Q1

2009

Q4

2010

Q3

2011

Q2

2012

Q1

2012

Q4

2013

Q3

2014

Q2

2015

Q1

2015

Q4

2016

Q3

2017

Q2

(0.10)

(0.08)

(0.06)

(0.04)

(0.02)

0.02

0.04

0.06

0.08

0.10

1995Q2Q2

2005Q2Q2

2013Q3Q2

2009Q3Q2

2000Q2Q2

Financial Cycle (rhs) Financial Cycle Peak Financial Cycle Trough Crisis

Graph 6.4 Real GDP Growth Graph 6.5 Inflation (yoy)

6.0

2.0

4.0

5.0

1.0

3.0

7.0

8.0

CrisisReal GDP Growth (yoy)

2002

Q1

2002

Q4

2003

Q3

2004

Q2

2005

Q1

2005

Q4

2006

Q3

2007

Q2

2008

Q1

2008

Q4

2009

Q3

2010

Q2

2011

Q1

2011

Q4

2012

Q3

2013

Q2

2014

Q1

2014

Q4

2015

Q3

2016

Q2

2017

Q1

10

2

6

8

0

4

12

14

1620

03Q

3

2004

Q2

2005

Q1

2005

Q4

2006

Q3

2007

Q2

2008

Q1

2008

Q4

2009

Q3

2010

Q2

2011

Q1

2011

Q4

2012

Q3

2013

Q2

2014

Q1

2014

Q4

2015

Q3

2016

Q2

2017

Q1

CrisisCPI (yoy)

Graph 6.6 Exchange Rate (Rp/USD)

12,500

8,500

10,500

11,500

7,500

9,500

13,500

14,500

15,500

2001

Q2

2002

Q1

2002

Q4

2003

Q3

2004

Q2

2005

Q1

2005

Q4

2006

Q3

2007

Q2

2008

Q1

2008

Q4

2009

Q3

2010

Q2

2011

Q1

2011

Q4

2012

Q3

2013

Q2

2014

Q1

2014

Q4

2015

Q3

2016

Q2

2017

Q1

CrisisExchange Rate (Rp/USD)

Graph 6.7 Private External Debt in Rupiah (yoy)

16

14

12

10

8

6

4

2

0

2003

Q3

2004

Q2

2005

Q1

2005

Q4

2006

Q3

2007

Q2

2008

Q1

2008

Q4

2009

Q3

2010

Q2

2011

Q1

2011

Q4

2012

Q3

2013

Q2

2014

Q1

2014

Q4

2015

Q3

2016

Q2

2017

Q1

CrisisPrivate External Debt (yoy)


186 BANK INDONESIA


Graph 6.8 Credit Growth (yoy)

15

-5

5

10

-10

0

20

25

30

35

40

2001

Q2

2002

Q1

2002

Q4

2003

Q3

2004

Q2

2005

Q1

2005

Q4

2006

Q3

2007

Q2

2008

Q1

2008

Q4

2009

Q3

2010

Q2

2011

Q1

2011

Q4

2012

Q3

2013

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2014

Q1

2014

Q4

2015

Q3

2016

Q2

2017

Q1

CrisisCredit (%, yoy)


10

0

5

15

20

25

2002

Q4

2003

Q3

2004

Q2

2005

Q1

2005

Q4

2006

Q3

2007

Q2

2008

Q1

2008

Q4

2009

Q3

2010

Q2

2011

Q1

2011

Q4

2012

Q3

2013

Q2

2014

Q1

2014

Q4

2015

Q3

2016

Q2

2017

Q1

CrisisDeposit (%, yoy)

Graph 6.10 NPL Ratio (%) Graph 6.11 ROA Ratio (%)

8

0

4

6

-2

2

10

12

14

16

18

2002

Q1

2002

Q4

2003

Q3

2004

Q2

2005

Q1

2005

Q4

2006

Q3

2007

Q2

2008

Q1

2008

Q4

2009

Q3

2010

Q2

2011

Q1

2011

Q4

2012

Q3

2013

Q2

2014

Q1

2014

Q4

2015

Q3

2016

Q2

2017

Q1

CrisisNPL (%)

2

1

3

4

2003

Q3

2004

Q2

2005

Q1

2005

Q4

2006

Q3

2007

Q2

2008

Q1

2008

Q4

2009

Q3

2010

Q2

2011

Q1

2011

Q4

2012

Q3

2013

Q2

2014

Q1

2014

Q4

2015

Q3

2016

Q2

2017

Q1

CrisisROA (%)

Graph 6.12 Capital Adequacy Ratio (%) Graph 6.13 Loan-to-Deposit Ratio (%)

20

10

15

25

30

2003

Q3

2004

Q2

2005

Q1

2005

Q4

2006

Q3

2007

Q2

2008

Q1

2008

Q4

2009

Q3

2010

Q2

2011

Q1

2011

Q4

2012

Q3

2013

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2014

Q1

2014

Q4

2015

Q3

2016

Q2

2017

Q1

CrisisCAR (%) CrisisLDR (%)

100

90

80

70

60

50

40

30

2001

Q2

2002

Q1

2002

Q4

2003

Q3

2004

Q2

2005

Q1

2005

Q4

2006

Q3

2007

Q2

2008

Q1

2008

Q4

2009

Q3

2010

Q2

2011

Q1

2011

Q4

2012

Q3

2013

Q2

2014

Q1

2014

Q4

2015

Q3

2016

Q2

2017

Q1


187BANK INDONESIA





Graph 6.14. JCI Volatility

0.10

-

0.05

0.15

0.20

0.25

2002

Q1

2002

Q4

2003

Q3

2004

Q2

2005

Q1

2005

Q4

2006

Q3

2007

Q2

2008

Q1

2008

Q4

2009

Q3

2010

Q2

2011

Q1

2011

Q4

2012

Q3

2013

Q2

2014

Q1

2014

Q4

2015

Q3

2016

Q2

2017

Q1

CrisisVolatilitas IHSG

(iii). Banking Indicators

Compared to conditions in the previous period,

the banking indicators began to display early

signs of improvement in the first quarter of

2017, including credit growth, deposit growth,

the Capital Adequacy Ratio (CAR) and return on

assets (ROA). In contrast, non-performing loans

(NPL) deteriorated somewhat. Consequently,

maintaining the CCyB rate at 0% was not

expected to restrain banking activities, especially

lending, thus allowing banking industry

performance to continue improving.

(iv). Asset Prices

Jakarta Composite Index (JCI) volatility tended

to decline on the previous period, reflecting

relatively low pressure on the capital market.

Consequently, maintaining the CCyB at 0% was

expected to support capital market stability.

Bank Indonesia refined the RR-loan to funding

ratio (RR-LFR) for conventional commercial banks in

August 2016 by raising the floor from 78% to 80%,

while maintaining the ceiling at 92%. The policy was

6.3. Assessment of the RR-Loan to Funding Ratio (RR-LFR)

oriented towards strengthening domestic demand

in line with the lower primary reserve requirement

and interest rates. The banking industry is

expected to stimulate the intermediation function

and national economic growth while adhering to

prudential principles. The RR-loan to funding ratio

(RR-LFR) is a macroprudential instrument that aims

to catalyse a more optimal intermediation function,

while maintaining capital resilience, adequate

liquidity and credit risk management.

The loan-to-deposit ratio (LDR) and financing-to-

deposit ratio (FDR) were lowered in the first semester

of 2017 because deposit growth was outpacing

credit growth in line with economic moderation.

Meanwhile, the banks issued more securities in

2017 than in 2016. The banking industry has

begun to utilise the securities issued as the main

source of bank funding in line with policy to include

bank-issued securities in the LDR (RR-LFR) in August

2015, which aimed to expand funding sources for

the banking industry, while simultaneously backing

financial market deepening efforts.

The reduction to the LFR in the first semester of

2017 prompted an increase in the number of banks

188 BANK INDONESIA


Graph 6.15Loan-to-Deposit Ratio (LDR) and Financing-to-Deposit Ratio (FDR) Developments

Graph 6.16 Loans, Deposits and Securities

Jun-

15

Aug-

15

Oct

-15

Dec-

15

Feb-

16

Apr-1

6

Jun-

16

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-1

7

Jun-

17

5,000

4,800

4,600

4,400

4,200

4,000

3,800

3,600

3,400

3,200

3,000

45

40

35

30

25

20

Securities (rhs)

Loans Deposits

Value (Rp, trillions) Value (yoy)

Loans Deposits

Jun-

15

Aug-

15

Oct

-15

Dec-

15

Feb-

16

Apr-1

6

Jun-

16

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-1

7

Jun-

17

16%

14%

12%

10%

8%

6%

4%

2%

0%

80%

70%

60%

50%

40%

30%

20%

10%

0%

with an LFR of below 80% compared to conditions

in the previous period. In the second semester of

2017, a total of 39 banks reported an LFR of less

than 80%, more than doubling from just 18 banks

in December 2016. On the other hand, the number

of banks with an LFR in excess of 92% decreased

from 44 to 28. The intermediation function of the

affected banks was supported by adequate capital

resilience (CAR ≥ 14%), consistent with the goal of

the RR-loan to funding ratio (RR-LFR) policy.

92%

91%

90%

89%

88%

87%

86%

85%

2015 20172016

Jun

Aug

Oct

Dec

Feb

Apr

Jun

Feb

Apr

Jun

Aug

Oct

Dec

LDR FDR


Securities (rhs)


189BANK INDONESIA





32

24

18

3839

39

40 40

3635 31

36

41

28 28

0

2

3

0 0

Jun 16 Jun 16 Jun 16 Jun 16Sep 16 Sep 16 Sep 16 Sep 16Dec 16 Dec 16 Dec 16 Dec 16Mar 17 Mar 17 Mar 17 Mar 17Jun 17 Jun 17 Jun 17 Jun 17

LFR < 80% 80% ≤ LFR ≤ 92% LFR ≥ 92% & CAR ≥ 14% LFR ≥ 92% & CAR ≥ 14%

Graph 6.17The Number of Banks Fulfilling the RR-Loan to Funding Ratio (RR-LFR)


A sluggish property sector compelled Bank Indonesia

to continue easing LTV policy, which began in 2015.

Weaker growth of property sales and slower rising

prices, accompanied by dwindling demand for

housing loans were indicative of a tepid property

sector. In response, Bank Indonesia began to ease

macroprudential policy in 2015 by raising the LTV/

FTV ratios on property loans/financing.

The move in 2015 successfully stifled the waning

growth of housing loans/financing disbursed by

the banking industry. Nevertheless, loosening the

LTV/FTV policy was insufficient to catalyse credit/

financing growth, thereby necessitating further

easing, which ultimately stimulated credit/financing

growth in the property sector while maintaining

prudential principles. A surge of activity in the

property sector is considered strategic because of

6.4. Assessment of the Loan-to-Value (LTV) and Financing-to-Value (FTV) Ratios for Property Loans/Financing and Downpayments on Automotive Loans

the large multiplier effect to supporting sectors,

which would help stimulate an economic recovery.

To that end, Bank Indonesia once again eased LTV/

FTV policy by issuing Bank Indonesia Regulation

(PBI) No. 18/16/PBI/2016 concerning the Loan-to-

Value (LTV) Ratio for Property Loans, the Financing-

to-Value Ratio (FTV) for Property Financing and

Downpayments on Automotive Loans/Financing.

The adjustment to the FTV/LTV policy began to bear

fruit almost immediately, with growth of housing

loans accelerating from 6.21% in August 2016 to

7.51% in June 2017, despite remaining below total

credit growth disbursed by the banking industry

at 7.75%. Meanwhile, the share of housing loans

to total bank loans reached 9.09%, dominated by

houses with a floor area of 22-70m2 and more than

70m2.

Based on bank activity, as of June 2017, the

share of housing loans at conventional banks

accounted for 85.28% of the total in the banking

industry, while the share of Islamic housing

financing accounted for the remaining 14.72%.

190 BANK INDONESIA


Graph 6.18 Housing Loans

20.0

15.0

10.0

5.0

0.0

-5.0

-10.0

-15.0

25.0

20.0

15.0

10.0

5.0

0.0

-5.0

-10.0

Jan-

15Fe

b-15

Mar

-15

Apr-1

5M

ay-1

5Ju

n-15

Jul-1

5Au

g-15

Sept

-15

Oct

-15

Nov

-15

Dec-

15Ja

n-16

Feb-

16M

ar-1

6Ap

r-16

May

-16

Jun-

16Ju

l-16

Aug-

16Se

pt-1

6O

ct-1

6N

ov-1

6De

c-16

Jan-

17Fe

b-17

Mar

-17

Apr-1

7M

ay-1

7Ju

n-17

yoy (%)

yoy (%) LTV 2015 LTV 2016

RT 22 - 70

RT > 70

RT ≤ 21

8.41

2.861.95

(8.44)

Ruko/Rukan

Flat/Apt 21-70

Flat/Apt > 70

14.54

2.55

(9.23)

Graph 6.19 Housing Loans by Type

Flat/Apt ≤ 21

14.0

12.0

10.0

8.0

6.0

4.0

2.0

-

9.50

9.40

9.30

9.20

9.10

9.00

8.90

8.80

Jan

Feb

Mar Ap

r

May Jun Jul

Aug

Sep

Oct

Nov De

c

Jan

Jan

Feb

Feb

Mar

MarAp

r

Apr

May

MayJun

JunJul

Aug

Sep

Oct

Nov De

c

yoy(%) LTV2015

LTV2016

(%)

7.75

7.51

9.09

Share (rhs)Housing Loan Growth

2015 2016 2017

Total Credit Growth

Source: Monthly Commercial Bank reports, June 2017


191BANK INDONESIA





Graph 6.20 Housing Loan Performance by Bank Activity

Jan-

15

Feb-

15

Mar

-15

Apr-1

5

May

-15

Jun-

15

Jul-1

5

Aug-

15

Sept

-15

Oct

-15

Nov

-15

Dec-

15

Jan-

16

Feb-

16

Mar

-16

Apr-1

6

May

-16

Jun-

16

Jul-1

6

Aug-

16

Sept

-16

Oct

-16

Nov

-16

Dec-

16

Jan-

17

Feb-

17

Mar

-17

Apr-1

7

May

-17

Jun-

17

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

90

80

70

60

50

40

30

20

10

-

15.82

5.90

Conventional Share Islamic ShareConventional Growth (rhs) Islamic Growth (rhs)


Furthermore, housing loan growth at Islamic

banks stood at 5.90%, compared to 15.82% at

conventional banks.

Housing Credit Risk

The increase of housing loan growth was

accompanied by heightened credit risk, as reflected

by an increase in the corresponding gross NPL

ratio from 2.54% in December 2016 to 2.94%

in June 2017. Nevertheless, the level of NPL was

still considered low in comparison to the industry

average at 2.96%. The gross NPL ratio was highest

on housing loans for a flat/apartment of ≤ 21m2

at 4.88% and the lowest was 1.52% for a flat/

apartment of > 70m2. Meanwhile, the NPL on

loans for a house ranged from 2.67% to 3.13%.

Furthermore, housing credit risk was higher at

conventional banks rather than Islamic banks.

Housing Loan Disbursements by Province

Regionally, housing loans tended to concentrate

on the island of Java, accounting for 68.26% of

the total. In terms of value, housing loans were

concentrated in four provinces of Java, namely

West Java, Jakarta, Banten and East Java. Nearly all

provinces of Indonesia experienced stronger growth

of housing loans, with Jambi, North Maluku and Bali

as the only exceptions. Regarding high credit risk,

East Kalimantan, North Sulawesi and North Sumatra

recorded a gross NPL ratio above the 5% threshold.

192 BANK INDONESIA


Table 6.1 Housing Loan Performance by Type


Property Type (m2)

Current LTV Policy (PBI No. 18/16/PBI/2016) Credit Performance

Property Loans and Islamic Property Financing with Murabahah and Istishna

Contracts

Islamic Property Financing with MMQ and IMBT Contracts Current Conditions (June 2017)

Credit Growth (%)

KP and PP FACILITY

I II III dst I II III dst Value(Rp, billions)

Share (%) NPL (%) Dec’12 Dec’13 Dec’14 Dec’15 Ags’16 Dec’16 Jan’17 Feb’17 Mar’17 Apr’17 May’17 Jun’17

House

Type>70 85% 80% 75% 90% 85% 80% 128,989 31.60 3.13 47.23 19.73 9.23 3.78 1.02 3.45 3.79 2.41 2.68 2.00 1.67 2.55

Type 22-70 - 85% 80% - 90% 85% 210,884 51.66 2.67 18.58 32.21 15.07 13.80 13.93 14.32 14.42 13.67 15.44 14.45 15.10 14.54

Type21 - - - - - - 27,188 6.66 2.82 (32.40) 34.74 15.14 (6.18) (7.62) (5.34) (5.36) (5.42) (5.69) (5.52) (9.62) (9.23)

Apartment

Type>70 85% 80% 75% 90% 85% 80% 5,751 1.41 1.52 68.08 46.33 7.67 (5.35) (3.59) (3.33) (2.79) (1.24) (0.04) 0.40 1.34 1.95

Type 22-70 90% 85% 80% 90% 85% 80% 6,718 1.65 2.64 80.44 1.15 12.38 1.92 (1.95) (0.57) 0.59 1.05 3.68 5.57 5.83 8.41

Type21 - 85% 80% - 85% 80% 972 0.24 4.88 293.26 (11.30) 11.20 (1.46) 10.21 14.75 14.92 10.80 (9.41) (9.18) (8.45) (8.44)

Home Store/Home Office

- 85% 80% - 85% 80% 27,741 6.80 4.58 31.43 24.97 3.96 2.35 3.09 3.17 2.82 3.41 2.15 (0.76) 2.99 2.86

TOTAL HOUSING LOANS 408,242 100.00 2.94 22.44 26.49 11.89 6.96 6.21 7.67 7.87 7.14 7.95 7.13 7.34 7.51

Total Credit 4,491,373 9.09 2.96 23.08 21.60 11.58 10.45 6.83 7.86 8.28 8.65 9.24 9.47 8.71 7.75

Graph 6.2 Housing Loan Performance by Bank Activity


TYPE

Housing Loans as of June 2017 Gross NPL Ratio of Housing Loans as of June 2017 (%) Net NPL Ratio of Housing Loans as of June 2017 (%) Share of Total Credit as of June 2017 (%) Housing Loan Growth as of June 2017 (yoy, %)

Conventional Total

Islamic Housing Financing

Conventional Total

Islamic Total

Conventional Total

Islamic Total

Conventional Total

Islamic Total

Conventional Total


Islamic Total

Istishna& Murabahah

MMQ& IMBT

Other Contracts

IslamicTotal

Istishna& Murabahah

MMQ& IMBT

Other Contracts

Islamic Total

Istishna& Murabahah

MMQ& IMBT

Other Contracts

IslamicTotal

Istishna& Murabahah

MMQ& IMBT

Other Contracts

Islamic Total

Istishna& Murabahah

MMQ& IMBT

Other Contracts

House

Type > 70 108,784 20,205 9,554 9,160 1,491 3.17 2.89 3.24 2.81 1.17 1.87 2.17 2.14 2.38 1.13 26.65 4.95 2.34 2.24 0.37 0.13 17.9 11.4 26.6 13.0

Type 22-70 178,965 31,919 27,698 2,373 1,848 2.77 2.07 1.98 1.61 4.01 1.89 1.37 1.22 1.36 3.69 43.84 7.82 6.78 0.58 0.45 13.15 23.4 24.6 52.5 (11.4)

Type ≤ 21 23,948 3,240 1,835 30 1,375 2.90 2.20 1.52 - 3.16 2.21 1.95 1.16 - 3.05 5.87 0.79 0.45 0.01 0.34 (9.23) (8.8) (0.6) 638.7 (19.2)

Apartment

Type > 70 5,021 723 251 396 76 1.60 0.91 1.94 0.05 2.02 1.02 0.77 1.56 0.03 2.01 1.23 0.18 0.06 0.10 0.02 0.36 14.6 (2.0) 42.9 (22.0)

Type 22-70 5,965 753 435 230 88 2.62 2.79 1.81 0.88 2.70 1.77 2.35 3.15 0.76 2.60 1.46 0.18 0.11 0.06 0.02 8.35 9.9 (0.6) 59.9 (15.3)

Type ≤ 21 816 157 92 61 4 5.40 2.17 3.36 0.39 2.05 3.23 1.59 2.42 0.32 1.98 0.20 0.04 0.02 0.01 0.00 (14.10) 39.4 (8.3) 691.1 (15.9)


24,655 3,086 1,441 1,469 176 4.73 3.39 3.98 2.37 7.10 2.79 2.53 2.49 2.04 6.95 6.04 0.76 0.35 0.36 0.04 2.72 4.1 7.4 6.5 (27.2)

TOTAL 348,160 60,081 41,304 13,718 5,058 3.03 2.42 2.34 2.43 2.99 1.96 1.74 1.50 2.06 2.83 85.28 14.72 10.12 3.36 1.24 5.94 17.93 18.74 29.35 (8.96)

193BANK INDONESIA





Property Type (m2)

Current LTV Policy (PBI No. 18/16/PBI/2016) Credit Performance

Property Loans and Islamic Property Financing with Murabahah and Istishna

Contracts

Islamic Property Financing with MMQ and IMBT Contracts Current Conditions (June 2017)

Credit Growth (%)

KP and PP FACILITY

I II III dst I II III dst Value(Rp, billions)

Share (%) NPL (%) Dec’12 Dec’13 Dec’14 Dec’15 Ags’16 Dec’16 Jan’17 Feb’17 Mar’17 Apr’17 May’17 Jun’17

House

Type>70 85% 80% 75% 90% 85% 80% 128,989 31.60 3.13 47.23 19.73 9.23 3.78 1.02 3.45 3.79 2.41 2.68 2.00 1.67 2.55

Type 22-70 - 85% 80% - 90% 85% 210,884 51.66 2.67 18.58 32.21 15.07 13.80 13.93 14.32 14.42 13.67 15.44 14.45 15.10 14.54

Type21 - - - - - - 27,188 6.66 2.82 (32.40) 34.74 15.14 (6.18) (7.62) (5.34) (5.36) (5.42) (5.69) (5.52) (9.62) (9.23)

Apartment

Type>70 85% 80% 75% 90% 85% 80% 5,751 1.41 1.52 68.08 46.33 7.67 (5.35) (3.59) (3.33) (2.79) (1.24) (0.04) 0.40 1.34 1.95

Type 22-70 90% 85% 80% 90% 85% 80% 6,718 1.65 2.64 80.44 1.15 12.38 1.92 (1.95) (0.57) 0.59 1.05 3.68 5.57 5.83 8.41

Type21 - 85% 80% - 85% 80% 972 0.24 4.88 293.26 (11.30) 11.20 (1.46) 10.21 14.75 14.92 10.80 (9.41) (9.18) (8.45) (8.44)


- 85% 80% - 85% 80% 27,741 6.80 4.58 31.43 24.97 3.96 2.35 3.09 3.17 2.82 3.41 2.15 (0.76) 2.99 2.86

TOTAL HOUSING LOANS 408,242 100.00 2.94 22.44 26.49 11.89 6.96 6.21 7.67 7.87 7.14 7.95 7.13 7.34 7.51

Total Credit 4,491,373 9.09 2.96 23.08 21.60 11.58 10.45 6.83 7.86 8.28 8.65 9.24 9.47 8.71 7.75

TYPE

Housing Loans as of June 2017 Gross NPL Ratio of Housing Loans as of June 2017 (%) Net NPL Ratio of Housing Loans as of June 2017 (%) Share of Total Credit as of June 2017 (%) Housing Loan Growth as of June 2017 (yoy, %)

Conventional Total


Conventional Total

Islamic Total

Conventional Total

Islamic Total

Conventional Total

Islamic Total

Conventional Total


Islamic Total

Istishna& Murabahah

MMQ& IMBT

Other Contracts

IslamicTotal

Istishna& Murabahah

MMQ& IMBT

Other Contracts

Islamic Total

Istishna& Murabahah

MMQ& IMBT

Other Contracts

IslamicTotal

Istishna& Murabahah

MMQ& IMBT

Other Contracts

Islamic Total

Istishna& Murabahah

MMQ& IMBT

Other Contracts

House

Type > 70 108,784 20,205 9,554 9,160 1,491 3.17 2.89 3.24 2.81 1.17 1.87 2.17 2.14 2.38 1.13 26.65 4.95 2.34 2.24 0.37 0.13 17.9 11.4 26.6 13.0

Type 22-70 178,965 31,919 27,698 2,373 1,848 2.77 2.07 1.98 1.61 4.01 1.89 1.37 1.22 1.36 3.69 43.84 7.82 6.78 0.58 0.45 13.15 23.4 24.6 52.5 (11.4)

Type ≤ 21 23,948 3,240 1,835 30 1,375 2.90 2.20 1.52 - 3.16 2.21 1.95 1.16 - 3.05 5.87 0.79 0.45 0.01 0.34 (9.23) (8.8) (0.6) 638.7 (19.2)

Apartment

Type > 70 5,021 723 251 396 76 1.60 0.91 1.94 0.05 2.02 1.02 0.77 1.56 0.03 2.01 1.23 0.18 0.06 0.10 0.02 0.36 14.6 (2.0) 42.9 (22.0)

Type 22-70 5,965 753 435 230 88 2.62 2.79 1.81 0.88 2.70 1.77 2.35 3.15 0.76 2.60 1.46 0.18 0.11 0.06 0.02 8.35 9.9 (0.6) 59.9 (15.3)

Type ≤ 21 816 157 92 61 4 5.40 2.17 3.36 0.39 2.05 3.23 1.59 2.42 0.32 1.98 0.20 0.04 0.02 0.01 0.00 (14.10) 39.4 (8.3) 691.1 (15.9)


24,655 3,086 1,441 1,469 176 4.73 3.39 3.98 2.37 7.10 2.79 2.53 2.49 2.04 6.95 6.04 0.76 0.35 0.36 0.04 2.72 4.1 7.4 6.5 (27.2)

TOTAL 348,160 60,081 41,304 13,718 5,058 3.03 2.42 2.34 2.43 2.99 1.96 1.74 1.50 2.06 2.83 85.28 14.72 10.12 3.36 1.24 5.94 17.93 18.74 29.35 (8.96)

194 BANK INDONESIA


Coordination between the institutional members

of the Financial System Stability Committee,

pursuant to the Financial System Crisis Prevention

and Mitigation (PPKSK) Act (No. 9) of 2016, plays

an important role in the efforts to maintain financial

system stability. Inter-authority coordination is

crucial considering the linkages and overlaps in the

execution of function, duties and jurisdiction of the

authorities in the financial system. The Financial


Act serves as a solid foundation for coordination

and cooperation between Bank Indonesia, the

Financial Services Authority (OJK), Ministry of

Finance and Deposit Insurance Corporation (LPS),

primarily to prevent and resolve a financial system

crisis.

6.5. Policy Coordination between Bank Indonesia and Other Relevant Authorities

Graph 6.21 NPL of Housing Loans

NPL(%) LTV2015

LTV2016

4.00

3.50

3.00

2.50

2.00

1.50

Jan-

15Fe

b-15

Mar

-15

Apr-1

5M

ay-1

5Ju

n-15

Jul-1

5Au

g-15

Sept

-15

Oct

-15

Nov

-15

Dec-

15Ja

n-16

Feb-

16M

ar-1

6Ap

r-16

May

-16

Jun-

16Ju

l-16

Aug-

16Se

pt-1

6O

ct-1

6N

ov-1

6De

c-16

Jan-

17Fe

b-17

Mar

-17

Apr-1

7M

ay-1

7Ju

n-17

Conventional Housing Loans

3.03

Total Credit

Total Housing Loans

2.942.96


2.45

Graph 6.22 NPL of Housing Loans by Type

Jan-

15Fe

b-15

Mar

-15

Apr-1

5M

ay-1

5Ju

n-15

Jul-1

5Au

g-15

Sept

-15

Oct

-15

Nov

-15

Dec-

15Ja

n-16

Feb-

16M

ar-1

6Ap

r-16

May

-16

Jun-

16Ju

l-16

Aug-

16Se

pt-1

6O

ct-1

6N

ov-1

6De

c-16

Jan-

17Fe

b-17

Mar

-17

Apr-1

7M

ay-1

7Ju

n-17

6.05.55.04.54.03.53.02.52.01.51.00.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

NPL(%) LTV2015

LTV2016

Flat/Apt 22 - 70

2.67

2.64


2.94

4.58

3.13

1.52

2.82

4.88

Flat/Apt > 70

Flat/Ap ≤ 70

RT 22 - 70

Total Housing Loans RT > 70

RT≤ 21


In relation to inter-authority coordination, the


(PPKSK) Act mandates Bank Indonesia, in its

role as the monetary, payment system and

macroprudential authority, to coordinate with the

other authorities as follows:

i) Exchange data and/or information; ii) coordinate

with the Deposit Insurance Corporation (LPS) to

resolve bank solvency problems; iii) coordinate with

the Financial Services Authority (OJK) to provide

the short-term liquidity loan as well as update the

list of systemically important banks (SIB); and iv)

coordinate with other authorities to support the

bank restructuring program run by LPS.

Promulgation of the Financial System Crisis

Prevention and Mitigation (PPKSK) Act also

strengthened the bilateral cooperation and

coordination framework of Bank Indonesia in terms

of executing its function, duties and authority in the

monetary, payment system and macroprudential

195BANK INDONESIA





Table 6.3 Housing Loans by Province

No Province NPL (%) Share (%) Yoy (%)

1 West Java 2.89 25.79 13.14

2 Jakarta 2.38 15.75 1.45

3 Banten 1.77 10.92 12.49

4 East Java 2.11 10.76 8.29

5 Central Java 2.40 5.04 5.97

6 North Sumatra 5.44 3.68 6.65

7 South Sulawesi 4.65 3.38 4.64

8 Bali 3.01 2.42 (20.72)

9 South Kalimantan 4.64 2.07 4.88

10 East Kalimantan 7.35 2.05 3.94

11 Riau 4.46 2.02 8.74

12 South Sumatra 4.06 1.98 8.19

13 Riau Islands 2.12 1.75 3.46

14 West Kalimantan 2.69 1.27 13.94

15 North Sulawesi 6.41 1.08 9.83

16 Yogyakarta 1.98 1.03 8.77

17 Jambi 3.67 0.99 (0.72)

18 Lampung 3.26 0.93 15.27

19 West Nusa Tenggara 2.13 0.87 7.62

20 West Sumatra 3.66 0.82 5.86

21 Central Kalimantan 2.70 0.69 13.58

22 Nanggroe Aceh Darussalam 2.45 0.67 9.36

23 Central Sulawesi 3.03 0.63 4.85

24 Papua 3.11 0.61 21.42

25 Southeast Sulawesi 4.69 0.61 8.03

26 Bengkulu 2.21 0.47 13.17

27 West Irian Jaya 2.12 0.38 55.33

28 Bangka Belitung Islands 3.86 0.35 13.58

29 East Nusa Tenggara 1.64 0.33 6.21

30 Gorontalo 3.78 0.21 1.22

31 Maluku 1.24 0.19 14.44

32 West Sulawesi 2.92 0.16 24.09

33 North Maluku 1.17 0.11 (11.02)

TOTAL HOUSING LOANS 2.94 100.0 7.51


sectors, primarily through coordination and

cooperation with the Financial Services Authority

(OJK) and Deposit Insurance Corporation (LPS).

a. Bilateral Coordination between Bank

Indonesia and the Financial Services Authority

(OJK)

The cooperation and coordination framework in

operation between Bank Indonesia and the Financial

Services Authority (OJK) was complemented by

the promulgation of the Financial System Crisis

Prevention and Mitigation (PPKSK) Act. The Act

specifically instructs Bank Indonesia to coordinate

with the other authorities in pursuance of the PPKSK

Act, including the coordinated provision of the

short-term liquidity loan as well as determining and

updating the list of systemically important banks

(SIB) with OJK. The basis of Bank Indonesia and OJK


196 BANK INDONESIA

cooperation and coordination is also contained in

BI-OJK Joint Decree No. , dated

18th October 2013, concerning Cooperation and

Coordination in the Execution of Duties at Bank

Indonesia and the Financial Services Authority (OJK).

The joint decree details four components of BI-OJK

cooperation and coordination, namely: i) supporting

task implementation in accordance with the

respective jurisdictions; ii) exchanging information

on financial services institutions as well as managing

the bank reporting system and financing by BI and

OJK; iii) utilising Bank Indonesia’s property and

documentation by OJK; and iv) managing BI officials

and employees assigned to OJK.

Thus far, those four components of BI-OJK

cooperation and coordination have performed

well. Accordingly, Bank Indonesia and the

Financial Services Authority (OJK) have successfully

cooperated and coordinated on the following:

1. Cooperation and coordination to support

task implementation at both institutions in

pursuance of the respective jurisdictions.

BI and OJK have coordinated and cooperated

periodically or as required to support task

implementation at both institutions through

requests for inputs and responses to draft

regulations in the financial services sector.

Such inputs and recommendations are crucial

considering the interconnectedness and

overlaps of the function, duties and authority

of both institutions. Such cooperation is

expected to enhance regulatory effectiveness

and prevent duplicate rules applicable to

financial institutions operating in the financial

services sector.

PRJ-11/D.01/2013

15/1/KEP.GBI/2013

2. Exchanging Information on financial services

institutions as well as managing the bank

reporting system and financing by Bank

Indonesia and OJK.

Bank Indonesia and OJK cooperate and

coordinate to exchange data and/or

information in the execution of duties at each

respective institution. In general, BI and OJK

require data from financial services institutions,

including banks, nonbank financial institutions

and the capital market. Information and/

or data is exchanged through the Integrated

Information Exchange System (SAPIT) for

machine-to-machine data, including the

reporting application for financial services

institutions. For data that is not machine-

to-machine transferable, the Integrated

Information Exchange System – Information

Exchange Application (SAPIT IEA) is used along

with correspondence, various storage media

and e-mail.

3. Utilising Bank Indonesia’s property and

documentation by OJK.

From time to time, Bank Indonesia and OJK also

cooperate and coordinate in terms of utilising

Bank Indonesia’s property and documents by

OJK. In terms of the archives/documentation,

Bank Indonesia has gradually enhanced

archive management containing the bank

supervision and regulation documents prior

to 2013 under the control of Bank Indonesia.

Archive management has involved sorting

and documenting all the archives, which are

now available as required. Bank Indonesia

and OJK have jointly prepared procedures and





197BANK INDONESIA

mechanisms for borrowing archives/documents.

In terms of OJK using the assets and property

of Bank Indonesia, a mechanism has also been

developed for borrowing and extending the use

of BI property by OJK.

4. Managing BI officials and employees assigned

to OJK.

In accordance with the OJK Act, Bank Indonesia

assignments to OJK were completed on 31st

December 2016. The subsequent process of

transferring staff to permanent OJK positions

or back to Bank Indonesia has been completed

per the schedule. BI and OJK continued to

cooperate and coordinate before, during and

after the completion of the assignment process

to ensure the rights and responsibilities of those

employees wishing to transfer permanently to

OJK as well as those wishing to return to Bank

Indonesia in line with prevailing regulations.

To further facilitate coordination and cooperation

between both institutions, on 15th June 2017 Bank

Indonesia and OJK signed Joint Implementation

Guidelines containing: i) Coordination Mechanism

Protocol; and ii) Coordination Mechanism

Implementation Guidelines. The Coordination

Mechanism Implementation Guidelines consist of

eight operational guidelines as follows: i) exchanging

data and/or information on the supervision

of financial services institutions and macro-

surveillance; ii) implementing bank inspections; iii)

conducting joint reviews/research; iv) formulating

Indonesia’s stance on issues raised at international

forums; v) conducting public education and

socialisation activities; vi) the payment system; vii)

coordination between BI and OJK regional offices;

and viii) providing the short-term liquidity loan to

commercial banks and the short-term liquidity

financing to Islamic banks. In addition, after the


(PPKSK) Act, BI-OJK also prepared implementation

guidelines for determining and updating the list of

systemically important banks (SIB).

Moving forward, with the rapid development

of products and services combined with the

proliferation of financial institutions operating in

the financial services sector, BI-OJK cooperation

and coordination, including with other authorities,

will have to be strengthened. Rapid development

in terms of financial market deepening, FinTech

and financial inclusion will clearly come under

the auspices of various authorities, entailing

overlaps in the function, duties and jurisdictions

of the respective authorities. Consequently,

cooperation and coordination between authorities

with jurisdiction over the financial services sector

will be required in terms of issuing regulations as

well as introducing initiatives to ensure greater

effectiveness and efficiency, while not impairing

the industry.

b. Bilateral Coordination between Bank

Indonesia and the Deposit Insurance

Corporation (LPS)

Coordination between BI and LPS is based on

Memorandum of Understanding (MoU) No.

concerning Cooperation and Coordination in the

Execution of Duties at Bank Indonesia and the

Deposit Insurance Corporation (LPS), signed on 28th

July 2016. The Memorandum of Understanding

(MoU) also contains the provisions of the Financial


Act, specifically addressing the resolution of bank

18/12/NK/GBI/2016

MoU-3/DK/2016


198 BANK INDONESIA

solvency issues. The scope of coordination and

cooperation between BI and LPS consists of: i)

the resolution of bank default without systemic

impact through revocation of the business license;

ii) funding to resolve bank solvency issues; iii)

exchange of data and/or information; iv) employee

competence development; v) joint research, reviews

and/or surveys; vi) joint education and socialisation

activities; vii) employee assignments; and viii)

execution of other duties in accordance with

prevailing laws, including supporting the National

Noncash Movement (GNNT), financial market

deepening and expanding financial access.

BI-LPS cooperation and coordination in 2017 entered

the implementation phase of the Memorandum of

Understanding (MoU) with the following achieved:

1) Following up on Article 27 of the Financial


Act, Bank Indonesia and the Deposit Insurance

Corporation (LPS) signed a Cooperation

Agreement concerning the Sale of Securities

by the Deposit Insurance Corporation to Bank

Indonesia on 31st October 2016. The agreement

was in the form of implementation guidelines

for BI and LPS to sell tradeable government

securities (SBN) in order to resolve solvency

issues at systemically important banks (SIB)

and other banks under financial system crisis

conditions in pursuance of the decision taken

by the Financial System Stability Committee.

2) Exchanging data and/or information was

facilitated, including Regional Balance Sheet

data from Bank Indonesia as well as Crisis

Management Protocol (CMP) indicators

currently under development at the Deposit

Insurance Corporation (LPS).

3) Bank Indonesia and LPS also cooperate and

coordinate to provide socialisation activities

regarding the function, task and authority

of both institutions to stakeholders in the

operational area of the head office and

regional offices. The socialisation activities are

expected to bolster public and stakeholder

understanding regarding the function, task

and authority of Bank Indonesia and LPS.

Furthermore, Bank Indonesia and LPS also

coordinate to formulate rules and regulations

that involve interconnectedness or overlaps

with the function, tasks and authority of a

third party, including the preparation of LPS

regulations on the Resolution of systemically

important banks (SIB) and settlement of non-

systemically important banks as required by

the Financial System Crisis Prevention and

Mitigation (PPKSK) Act.





199BANK INDONESIA

The reserve requirement is a monetary policy

instrument used by central banks in various

countries. Bank Indonesia controls the magnitude

of the reserve requirement for all conventional and

Islamic commercial banks in rupiah and a foreign

currency. The reserve requirement sets the minimum

amount of reserves that must be maintained by a

commercial Bank, as determined by Bank Indonesia

and expressed as a percentage of the deposits. In

general, RR funds are maintained by a commercial

bank and held at the central bank as demand

deposits. The commercial banks’ funds are used

to meet the requirement for intraday customer

withdrawals and /or noncash activities.

Bank Indonesia has refined the reserve requirement

to enhance the effectiveness of monetary policy

transmission. The most recent refinements have

consisted of follow-up measures to the reformulation

of the monetary policy operational framework

planned in the previous year. Accordingly, the

adjustments are contained in Bank Indonesia

Regulation (PBI) No. 19/6/PBI/2017 as the fifth

amendment to Bank Indonesia Regulation (PBI) No.

15/15/PBI/2013 concerning the Minimum Reserve

Requirement in Rupiah and a Foreign Currency for

Conventional Commercial Banks.

The main provisions of the regulation that were

improved include meeting the primary reserve

requirement in rupiah. Accordingly, the primary

reserve requirement in rupiah, which was previously

set at 6.5% of deposits in rupiah and met on a daily

basis, was lowered to 5% of rupiah deposits to be

met on a daily basis and an average of 1.5% of

rupiah deposits over a given period.

The central bank regulation, which is known as

the average reserve requirement, is considered a

best practice, as applied by nearly all central banks

around the world. There are three main goals of

the average reserve requirement. First, to provide

flexibility for liquidity management, thus enhancing

bank efficiency. Second, to provide an interest rate

buffer, thereby reducing interest rate volatility in

the money market. Third, to provide an alternative

outlet to place liquidity, hence supporting financial

market deepening.

The average primary reserve requirement will be

implemented prudently and gradually while paying

due consideration to the challenges faced. Current

conditions represent a challenge for implementation

of the average reserve requirement, including surplus

liquidity in the banking system that is not evenly

distributed, the minimal availability of instruments in

the money market and the unbalanced distribution

of access to interbank transactions. Through a

rigorous review, coordination with relevant parties,

adjustments prepared to an established system and

an intensive communication process with those

involved, the banks are expected to take optimal

advantage of the additional liquidity management

flexibility the new regulations afford, which become

effective on 1st July 2017 with a 1-month transition

period immediately thereafter.

Box 6.1. Average Reserve Requirement Ratios


200 BANK INDONESIA200 BANK INDONESIA

The Development of Dual-Purpose Islamic

Financial Instruments

Islamic financial and economic developments

encompass three main pillars, namely: (i) economic

sector empowerment; (ii) enhancing Islamic

financial market efficiency; and (iii) improving the

quality of research and education. The economic

sectors, production and efficiency as well as Islamic

financial market deepening are strengthened

through mutually reinforcing principles due to the

requirements between financial instruments and the

underlying assets. Increasing Islamic financial market

efficiency is, therefore, in line with the development

of Islamic financial institutions (including Islamic

banks, takaful and mutual funds) and Islamic

financial market deepening. In this case, the quality

of research is crucial in terms of accelerating Islamic

financial and economic development.

A lack of Islamic financial market deepening efforts

in terms of Islamic Social Finance (ISF) has led to

an emphasis on the development of commercial

financial instruments and financing. Meanwhile,

efforts to mobilise funds based on the ISF platform

through waqf (and zakat) remain scarce. Indeed, if

formulated carefully, the development of ISF-based

schemes would provide a dual benefit.

Box 6.2. Innovative Islamic Financial Instruments: Awqaf-Linked Sukuk

Traditionally, zakat and waqf are instruments used

by the government to accelerate the process of

levelling the playing field for all segments of society,

while simultaneously improving the inclusiveness of

development. Nevertheless, the governance of ISF

institutions is not yet at a level that instils public

confidence. To that end and to optimise the growing

potential of waqf funds, the management of waqf

(and zakat) funds must become more effective,

efficient and accurate.

Seeking to garner public confidence in ISF

management, in conjunction with the Islamic

Research and Training Institute – Islamic

Development Bank (IRTI-IDB) and national waqf and

zakat authorities (including the National Amil Zakat

Board (Baznas), Indonesia Waqf Board, etc.) as well

as international ISF authorities, Bank Indonesia

has initiated the formulation of a governance

framework in the form of zakat and waqf core

principles, which are currently being complemented

by the preparation of technical notes.

In relation to utilising social funds for economic

activity, the concept of awqaf-linked sukuk integrates

the potential of waqf funds to finance development,

thus providing dual commercial and social benefits.

Domestic and international sources of funds include





201BANK INDONESIA 201BANK INDONESIA 201

the cash waqf funds accumulated by several waqf

institutions in Indonesia under the auspices of the

Indonesia Waqf Board (BWI) using a fiduciary scheme.

Technically, the concept of awqaf-linked sukuk is the

utilisation of cash waqf (with a maturity of typically

more than one year) accumulated by Nadzhir for

investment in selected SBSN projects that provide a

regular return. Selected projects provide the uniqueness

of this concept, where the projects are considered in

line with waqif expectations and are generally in

accordance with the Sustainable Development Goals as

well as improving the Human Development Index (HDI).

According to the scheme, upon maturity the

principal of the disbursed fund is returned to

the waqif, while the returns are handed over by

the government to the Nadzhir to be given as

shodaqah (based on the approval of the waqif) to

the Amil Zakat Institutions (LAZ) for distribution

to social projects/activities. Consequently, the

commercial and social sectors (waqf and zakat

funds) become integrated, such as by upgrading

micro-entrepreneurs, broadening financial access

(financial inclusion) and so on that ultimately

increase productivity and expand the national

production base.

1. Waqf included interconnectedness he productive waqf forum are committed to temporary waqf funds.

2. Waqf funds are used to purchase invest in Government Islamic Securities (SBSN).

3. Commercial projects generate returns.

4. SBSN provide returns and the principal upon maturity.

5. SBSN principal is returned to the Nadzhir and then to the Waqif.

6. SBSN returns (same or shodaqoh to zakat institution below the market rate) becomes the shodaqoh to the zakat institution.

7. The zakat institution utilises the funds for social projects.

Wakif Nadzhir &17 LKS PWU SBSN

Wakif

Wakif

WCP

LAZ Social Projects *

Social Projects Commercial Projects

ZCP

Productive Waqf Forum

BI, BWI & Baznas

Deposit waqf funds Investment in SBSN

SBSN return

and principal

Project

return

SBSN Principal

Social Project financing

Shodaqoh

SBSN return

(after Nadzhir)

to LAZ

Box Figure 6.2.1 Awqaf-Linked Sukuk

1

2

6

3

4

2

7


202 BANK INDONESIA

The concept of awqaf-linked sukuk has dual

benefits from a commercial and social perspective,

including: 1) providing additional sources of

financing for government infrastructure projects,

especially social projects such as new schools,

hospitals and so on; 2) providing additional

new local and international investor segments,

particularly social (waqf) investors, thus deepening

the Islamic financial markets; 3) the investment

returns can be used to finance social projects

through zakat schemes; 4) the low cost of waqf

funds will help alleviate pressures on the cost of

funds of the respective project, thus reducing the

cost price of production and increasing efficiency.

Such benefits indicate that awqaf-linked sukuk

would provide a deflator function and, therefore,

stabilise the financial sector as a whole.

Furthermore, when the awqaf-linked sukuk are

fully integrated into the Awqaf Core Principals, the

business processes and accountability of awqaf-

linked sukuk will become more professional, on

target, transparent and accountable. Consequently,

congruent with a stronger people’s economy

and growing public confidence nationally and

internationally, the flow of waqf funds will surge.

Moreover, when the awqaf-linked sukuk can provide

tangible benefits, the confidence of national and

international waqif will soar. Currently, this scheme is

merely one instrument that is driving capital inflows,

accelerating economic growth and economic equality

as well as deepening the financial markets. In turn,

such favourable developments will be accompanied

by a stronger position of reserve assets, balance of

payments (BOP) and rupiah exchange rate.





203BANK INDONESIA 203BANK INDONESIA 203

THE IMPACT OF DOMESTIC GOVERNMENT FINANCING ON DEPOSITS IN THE BANKING INDUSTRY

Article 1

Ndari Surjaningsih1, Moh. Nuryazidi2, Laura G. Gabriella3

KAJIAN STABILITAS KEUANGANNo. 29, September 2017

204 BANK INDONESIA

205BANK INDONESIA





Rp1,931.22 trillion at the end of 2014 (74% share

of the total).

The surge of SBN issuances has been observed to

erode deposits in the banking industry. In addition

to slower GDP growth, sluggish deposit growth

in the banking industry has also been linked to

stronger SBN growth, primarily since 2013 (Article

Graph 1.1). There are two factors suspected of

affecting the relationship between deposits and

SBN. First, the benchmark 10-year SBN yield is more

attractive to investors than the interest rates offered

on 1-month term deposits. Second, promulgation

of OJK Regulation (POJK) No. 01/POJK.05/2016

concerning Investment in Securities for Nonbank

Financial Services Institutions, dated 11th January

2016, which requires insurance and pension fund

companies to place a minimum of 30% of their

funds in SBN (Article Table 1.1) has also increased

the SBN placements of financial institutions.

Based on the previous considerations, in addition to

economic moderation in Indonesia, sluggish deposit

growth is suspected to have stemmed from a shift

in fund placements by investors, moving away from

deposits in favour of tradeable government securities

(SBN). One mandate of Bank Indonesia is to maintain

The expansive fiscal policy of the Indonesian

Government since 2014, with a focus on

infrastructure development, has increased the

budget deficit. Seeking to reduce the deficit,

the Government’s financing strategy has been

to increase issuances of tradeable government

securities (SBN), while maintaining a sound debt-

to-GDP ratio. The Government has deepened

the availability of debt instruments by increasing

the frequency of issuances to weekly as well as

diversifying the variety of instruments in order to

boost SBN issuances. The Government released

conventional government debt securities (SUN),

consisting of Government Bonds (ON) and treasury

bills (SPN). In terms of sharia-compliant instruments,

the Government has released Government Islamic

Securities (SBSN), Project-Based Sukuk (PBS), Retail

Sukuk (SUKRI), Hajj Fund Sukuk (SDHI) and Islamic

Treasury Bills (SPNS). The fruits of government efforts

to expand SBN issuances were already evident by

the end of 2016, with the position of SBN recorded

at Rp2,733.83 trillion, accounting for a 78.90%

share of total government debt and increasing from

1.1. Background

1. INTRODUCTION

Article Graph 1.1 SBN, Deposit and GDP Growth

% (y

oy)

% (y

oy)

30

25

20

15

10

5

0

8

7.5

7

6.5

6

5.5

5

4.5

4

3.5

3

2010 2011 2012 2013 2014 2015 2016

I II III IV I II III IV I II III IVI II III IV I II III IV I II III IV I II III IV

SBN (lhs) Deposits (lhs) GDP (rhs)

1 Senior Economic Researcher, Macroprudential Policy Department, Bank Indonesia. E-mail: [email protected] Economic Researcher, Macroprudential Policy Department, Bank Indonesia. E-mail: [email protected] Research Fellow, Macroprudential Policy Department, Bank Indonesia. E-mail: [email protected]


206 BANK INDONESIA


The Government has continued to increase SBN

issuances to fund the infrastructure development

program. Accordingly, Government SBN have

increased by 41.47% from Rp1,931.22 trillion in

2014 to Rp2,732.16 trillion at the end of 2016.

Nevertheless, the share of SBN holdings attributable

1.2. Tradeable Government Securities (SBN) and Deposits

Article Table 1.1 Summary of OJK Regulations concerning Nonbank SBN Holdings

Respondent NewExisting

31 Dec ‘16 31 Dec ‘17

Life Insurance min. 30 % min. 20 % min. 30 %

General Insurance and Reinsurance min. 20 % min. 10 % min. 20 %

Guarantee Company min. 20 % min. 10 % min. 20 %

Pension Funds min. 30 % min. 10 % min. 20 %

Social Security Management Agency (BPJS) Employment

• Social Guarantee Funds• BPJS Investments

min. 50 %min. 30 %

min. 50 %min. 30 %

min. 50 %min. 30 %

Social Security Management Agency (BPJS) Health min. 30 % min. 30 % min. 30 %

financial system stability, therefore slower deposit

growth demands attention before it is given the

chance to undermine the bank intermediation

function. Furthermore, weaker deposit growth could

also compromise the liquid assets in the banking

industry, which would impair repayment capacity for

the banks’ short-term obligations. Consequently, in-

depth research is required concerning the impact of

the government deficit on deposits in the banking

industry of Indonesia.

Article Graph 1.2 SBN Holdings by Financial Institution (December 2014 and December 2016)

38%

3%

3%

12%

31%

4%

4%5%

Foreign SBN

Insurance SBN

Banking Industry SBN

Bank Indonesia SBN

Pension Funds SBN

Individual SBN

Other SBN

Mutual Funds SBN

December 2014 December 2016

43%9%

2%

12%

18%

5%

5%6%


207BANK INDONESIA





to banks and nonbank financial institutions has not

really changed, other than a slight decline in bank

holdings coupled with a corresponding increase of

Bank Indonesia holdings in line with the change

in monetary policy instruments. In general, non-

resident investors are the dominant holders of SBN

from Indonesia, accounting for more than 43%,

followed by the banking industry with 18% and the

insurance industry with 12%.

Meanwhile, the impact of the OJK regulation issued

in 2016 is also suspected of eroding deposits.

Article Graph 1.3 shows an inverse correlation

between deposits and SBN in the nonbank financial

industry from the middle of 2015 through to

the end of 2016, especially in the insurance and

pension funds industries. At the end of 2016, SBN

holdings in the insurance industry had increased by

38.82% from Rp171.62 trillion at the end of 2015

Article Graph 1.3 Holdings of SBN and Deposits by Nonbanks (Rp, billions)

100000

80000

60000

40000

20000

0

800000

600000

400000

200000

0

Foreign Deposits and SBN

2010

M01

2010

M05

2010

M09

2011

M01

2011

M05

2011

M09

2012

M01

2012

M05

2012

M09

2013

M01

2013

M05

2013

M09

2014

M01

2014

M05

2014

M09

2015

M01

2015

M05

2015

M09

2016

M01

2016

M05

2016

M09

Foreign SBN (rhs)

Foreign Deposits (lhs)

100000

80000

60000

40000

20000

0

800000

600000

400000

200000

0

Insurance Industry Deposits and SBN

2010

M01

2010

M06

2010

M11

2011

M04

2011

M09

2012

M02

2012

M07

2013

M12

2013

M05

2013

M10

2014

M03

2014

M08

2015

M01

2015

M06

2015

M11

2016

M04

2016

M09

Insurance Industry Deposits (rhs)

Insurance Industry Deposits (lhs)

100000

80000

60000

40000

20000

0

Pension Funds Deposits and SBN

2010

M01

2010

M05

2010

M09

2011

M01

2011

M05

2011

M09

2012

M01

2012

M05

2012

M09

2013

M01

2013

M05

2013

M09

2014

M01

2014

M05

2014

M09

2015

M01

2015

M05

2015

M09

2016

M01

2016

M05

2016

M09

Pension Funds Deposits (rhs)

Pension Funds SBN (lhs)

100000

80000

60000

40000

20000

0

3000000

2500000

2000000

1500000

1000000

500000

0

Individual Deposits and SBN

2010

M01

2010

M06

2010

M11

2011

M04

2011

M09

2012

M02

2012

M07

2013

M12

2013

M05

2013

M10

2014

M03

2014

M08

2015

M01

2015

M06

2015

M11

2016

M04

2016

M09

Individual Deposits (rhs)

Individual SBN (lhs)

100000

80000

60000

40000

20000

0

Source: Ministry of Finance, Bank Indonesia

Mutual Funds Deposits and SBN

2010

M01

2010

M04

2010

M07

2010

M10

2011

M01

2011

M04

2011

M07

2011

M10

2012

M01

2012

M04

2012

M07

2012

M10

2013

M01

2013

M04

2013

M07

2013

M10

2014

M01

2014

M04

2014

M07

2014

M10

2015

M01

2015

M04

2015

M07

2015

M10

2016

M01

2016

M04

2016

M07

2016

M10

Mutual Funds Deposits (rhs)

Mutual Funds SBN (lhs)

90000

80000

70000

60000

50000

40000

30000

20000

10000

0

40000

35000

30000

25000

20000

15000

10000

5000

0

208 BANK INDONESIA


to Rp238.24 trillion. During the same period, the

insurance industry’s deposits declined by 10.97%

from Rp61.73 trillion to Rp54.96 trillion. Following

suit, SBN holdings in the pension funds industry

increased by 75.10% from Rp49.83 trillion to

Rp87.28 trillion over the same period.

One factor thought to play an important role in the

decline of deposits has been more attractive SBN

yields than deposit rates, which has encouraged

investors to shift their portfolios from deposits to

SBN. Article Graph 1.4 shows that the yield of the

benchmark 10-year SBN, as the most popular SBN

tenor sought by investors, has remained higher than

the 1-month deposit rate (as the most popular term

deposit tenor amongst the public).

Article Graph 1.4 SBN Yield and Deposit Rate Developments

1-Month Term Deposit Rate 1-Year Term Deposit Rate

10-Year SBN Yield

2010 2011 2012 2013 2014 2015 2016

10

9

8

7

6

5

Source: CEICData

1. Investigate the impact of government domestic

financing on deposit growth; and

2. Investigate how changes in investor behaviour

due to increasing government domestic

financing affect deposit placements and SBN

purchases.

1.3. Research Objectives

2.1. Demand for Money Theories

2. LITERATURE REVIEW

This chapter explores theories to explain factors

that influence deposits and a literature review to

discuss how the impact of a government budget

deficit affects bond yields and banking indictors.

Specifically, the theory discusses the determinants

of deposits that are not straight forward. One such

approach uses demand for money theories.

a. Quantity Theory of Money

The quantity theory of money shows the amount

of wealth in the form of money an individual is

inclined to hold at a certain time. The individual

faces several choices of where to place the wealth,

for instance in savings deposits, term deposits,

securities, cash or property. The selection process is

based on the opportunity cost of holding money

because there is a return on placements in securities

that would be lost if the individual chooses to hold

cash. In addition, an individual holding cash would

be exposed to a loss of purchasing power as the

nominal value is eroded by inflation.

An important theory in terms of demand for money

is the Liquidity Preference Theory. According to

the theory, Keynes rejects the classical theory

which states that the velocity of money is constant

and interest rates do not influence the demand

for money. According to Keynes, there are three

motives for an individual holding cash, namely to

transact, rainy-day savings and speculation. Keynes

grouped demand for money into two types, namely

the transactions demand for money (including

demand for savings), L_T, and speculative demand

for money, L_S.

209BANK INDONESIA





Transactions demand for money correlates

positively with nominal output (GDP), while

speculative demand correlates inversely with

interest rates. Therefore, higher interest rates

will be accompanied by dwindling demand for

money as economic players prefer to place their

wealth in portfolios that provide returns on

interest rates, such as savings and term deposits.

Under equilibrium, money supply (M) has the same

value as real money demand, namely M/P=L.

LT=Lt (Y)= kY , dengan ∂LT ⁄ ∂Y>0 danLS = LS (r) = R - dr, dengan ∂LS ⁄ ∂r < 0 dan (∂2 LS ⁄ ∂r2 < 0

Dimana,k = income balance coefficientY = Nominal outputR = Autonomous speculative balance,

r = representative interest rated = interest rate elasticity

(1)(2)

L = LT + Ls = kY + LS (r)

Furthermore, there is a critical market yield, r, that

makes investors indifferent to specifying their fund

choice. When the market rate is above the critical

market yield, investors will choose to place their

wealth in bonds because the interest income will be

higher than the expected capital loss. In contrast,

if the market rate is below the critical market yield,

the investor would choose to release their bonds

and hold cash.

Therefore, speculative demand is a process that

specifies whether an economic agent will hold

bonds or cash. Assuming that each individual

estimates normal yield (and critical yield) differently,

demand can be amalgamated into aggregate

speculative demand. The aggregate demand has a

negative slope because a reduction in the market

rate would cause more investors to hold bonds.

According to the liquidity preference theory, demand

for bonds will be the same as money supply, thus

Bd = Ms, which shows the presence of speculative

demand.

Dimana,BP = Bond market price,n = nominal coupon dari obligasi,

r = effective yield di pasar obligasi. NV = nominal value dari obligasi.

BP = – . NVnr

An increase in the number of bonds available would

shift the liquidity preference curve upwards, until

the same level of money supply would raise interest

rates (a change in the position r_0 to r_1. Therefore,

if the central bank undertook monetary operations

that changed money supply, it would also influence

the equilibrium of the liquidity preference function.

LS=LS (r,W), = > 0∂LS

∂LS

Consistent with the quantity theory of money,

transaction balances emphasise the importance of

money as a payment instrument, thus demand is

predicated on current public income. Meanwhile,

the store of value function proves the speculation

motive of demand for money. According to Keynes

theory (1973), the choice of portfolio by an agent is

based on expectations of future bond prices (bond

yields for instance). The public will continue to hold

bonds if the expected total return remains positive.

The function in the bond market can be expressed

as follows:

210 BANK INDONESIA


Article Graph 1.5 Keynesian Liquidity Preference

r

r1

BD=Ms

100b0.Pb

BS1=Ls1

BS0=Ls0

r0

Theories on the relationship between government

bond yields and the fiscal deficit remain a point of

contention. Gale and Orzag (2002) concluded that

from 60 research papers regarding the impact of

a fiscal deficit on interest rates the results were

contradictory. Half of the research found a positive

correlation, while the other half found a negative

correlation or mixed impact. The paper concluded

that a narrower government surplus would erode

national savings and reduce national income

irrespective of whether interest rates increased

or not. Specifically, the research stated that if a

larger fiscal deficit was not offset by an increase

in domestic savings, the budget deficit would

undermine domestic investment and exacerbate

the current account deficit.

Research by Ardagna (2009) analysed the behaviour

of government bond yields during a change of fiscal

stance in several OECD countries from 1960-2002.

2.2. Impact of a Government Deficit on Bond Yields and Banking Indicators

Ardagna found that 10-year government bond

yields experienced a hike of more than 180bps in

the current year when the fiscal deficit increased

by more than 1.5% of GDP in one year or by 1%

of GDP per annum for two consecutive years.

Consequently, the research recommended using

the 10-year SBN yield as a reference in response to

an increase in the fiscal deficit.

Research by Baldacci and Kumar (2010) found

a nonlinear relationship between a government

deficit and bond yields. The research looked at the

impact of a fiscal deficit and government debt on

interest rates from 1980-2008 using panel data

from 31 advanced and developing economies. The

results showed that increases in the fiscal deficit

and government debt would significantly influence

long-term interest rates, the magnitude of which

was determined by several factors, including

initial fiscal conditions, institutional conditions and

other structural factors, as well as global financial

dynamics. If the initial conditions consisted of a

large fiscal deficit, the increase in long-term bond

yields would be greater. A large fiscal deficit and

high government debt would place additional

upside pressures on bond yields, thereby rising in

the medium term.

Research in Indonesia concerning the impact of SBN

issuances has been conducted by Utari, et al. (2010),

who tested the impact of SUN on the crowding

out phenomenon using an Error Correction Model

and monthly data from 2003-2009. The research

concluded that the presence of domestic SUN had

no significant effect on increasing total credit.

Furthermore, relative changes in SUN stock to GDP

also had no significant impact on changes in the

long-term interest rate. These findings contradict

211BANK INDONESIA





a. The Impact of SBN on Bank Deposits

Long Term:

Model 1 : DPKt = ß0 + ß1 PDB Riilt + ß2 RDep1t + ß3SBNt + Zt

Model 2 : DPKt = ß0 + ß1 PDB Riilt + ß2 Spreadt + Zt

Short Term:

Model 1:

∆DPK = ß0 + ß1 ECMDPKt-1 + ß2∆PDB Riil +

ß3PDB Riilt-1 + ß4∆RDEP1MTt + ß5 RDEP1MTt-1 + ß4 ∆SBNt + ß5 SBNt-1

Model 2:

∆DPK = ß0 + ß1 ECMDPKt-1 + ß2∆PDB Riil +

ß3PDB Riilt-1 + ß4∆Spreadt + ß5Spreadt-1

b. The Impact of Individual and Nonbank

Portfolio Investment Behaviour

Y_t=SBN, DPK

X_t=Yield SBN, RDep1Yr, Gov_Deficit

Using the VECM method, each nonbank financial

institution is analysed, consisting of: (i) foreign; (ii)

insurance; (iii) pension funds; (iv) individuals; and (v)

mutual funds.

the research of Detragiache, et al (2005), which

analysed data from 89 low-income countries and

found that government bond yields were inversely

correlated with the loan-to-GDP ratio and deposit-

to-GDP ratio.

Excessive government bond issuances could

precipitate the lazy bank phenomenon, namely

a condition that disrupts the bank intermediation

function, causing a decline in bank loans. This

phenomenon was supported by Hauner (2006),

who showed that a high fixed-rate bond coupon,

classified as a risk-free asset, would cause the

banks to receive a constant flow of earnings from

domestic government bond holdings, thus reducing

the incentive for such banks to lend to the private

sector, which would be considered higher risk than

government bonds.

This research seeks to find a relationship between

the impact of a fiscal deficit and deposits in the

banking industry using an Error Correction Model

(ECM) and Vector Error Correction Model (VECM).

The equations tested in this research are detailed as

follows:

3.1. Methodology

3. METHODOLOGY AND DATA

Notes:Spread is the 10-year SBN yield deducted by the 1-month deposit rate.

n n ni i i∆Yt = αt + Σ = 0 ßi ∆Yt-i + Σ = 0δi ∆Xt-i + Σ = 0γi ∆Zt-i + p1 ei

∆Xt = αt + Σ = 0 ßi ∆Yt-i + Σ = 0δi ∆Xt-i + Σ = 0γi ∆Zt-i + p1 ei-1

n n ni i i

212 BANK INDONESIA


The data used for the research sample is quarterly

banking and macroeconomic data from Q1/2008

to Q4/2016 for the ECM method and monthly data

from January 2013 to December 2016 for the VECM

method.

3.2. Data

Based on a unit root test, it was concluded that

nearly all variables are not stationary at level. ADF

tests with a trend and intercept showed that most

of the data used was not stationary at level but

stationary at the first difference. The stationarity

testing revealed that the ECM and VECM methods

were in line with econometric theory.

The effect of declining deposits due to increased

government domestic financing was subsequently

tested using the ECM method in the long and short

term. The impact on deposits due to increasing SBN

issuances and SBN yields is presented in Article Table

1.4 and Article Table 1.5.

4.1. Stationarity Test

4.2. Impact Analysis of SBN on Deposits

4. RESULTS

Article Table 1.3 Unit Root with an Augmented Dicky Fuller (ADF) Test

Article Table 1.4 Long-Term Equation

Article Table 1.2 Data Summary for the ECM and VECM Methods

ECM Method

*) SBN and Deposit data from each respective institution

*) Significance level of 90%**) Significance level of 95%***) Significance level of 99%

VECM Method

Variable Level First Difference

Deposits

- Foreign 0.1132 0.0000

- Insurance 0.6406 0.0000

- Pension Funds 0.2973 0.0000

- Individual 0.0000 0.0000

- Mutual Funds

SBN

- Foreign 0.9184 0.0000

- Insurance 0.9739 0.0000

- Pension Funds 0.997 0.0000

- Individual 0.0001 0.0004

- Mutual Funds 1.0000 0.0000

Inflation 0.3078 0.0000

Real GDP 0.9961 0.8730

1-month Term Deposit Rate 0.7328 0.0506

10-year SBN yield 0.2985 0.0000

Variable (1) (2)

C -29.679*** -20.345***

Real GDP 3.408*** 2.436***

Term Deposit Rate 0.016*** -

SBN -0.344*** -

Spread - -0.016**

Adjusted R-Squared 0.996 0.988

Variable Data Source

DPK Total Deposits (rupiah and foreign currency) SEKI Bank Indonesia

PDBRL Real GDP CEIC Data

RDEP1 1-Month Term Deposit Rate SEKI Bank Indonesia

SBN Nominal SBN Ministry of Finance

YSBN_10YR 10-Year SBN Yield Bloomberg

Variable Data Source

DPK Total Deposits (rupiah and foreign currency) SEKI Bank Indonesia

PDBRL Real GDP CEICData

RDEP1 1-Month Term Deposit Rate SEKI Bank Indonesia

SBN Nominal SBN Ministry of Finance

YSBN_10YR 10-Year SBN Yield Bloomberg

213BANK INDONESIA





To observe changes in investor behaviour attributable

to government domestic financing in terms of placing

deposits and buying SBN, this research applied the

Vector Error Correction Model (VECM) method to

each respective investor, namely foreign, insurance,

pension fund, mutual fund and individual investors,

using monthly data from 2013 to 2016. The VECM

method was applied in this research because the

variables were not stationary at level but stationary

at the first difference. The variables used in the VECM

equations were government deficit, SBN, deposits

and spread between the 10-year SBN and 1-month

term deposit rate. Of the five VECM equations for

each respective investor, the results showed that the

optimum lag is 2. Meanwhile, all VECM equations

indicated cointegration, except mutual funds. This

implies that investment decision-making in the

mutual funds industry is more complex compared

to the other investors.

Hal ini mengindikasikan pengambilan keputusan

investasi reksadana lebih kompleks dibandingkan

dengan keempat investor lainnya.

4.3. Changes in Investor Behaviour due to Domestic Financing

Article Table 1.5 Short-Term Equation

*) Significance level of 90%**) Significance level of 95%***) Significance level of 99%

Variable (1) (2)

C -0.976 -0.0796

ECM -0.2369*** -0.293**

D(Real GDP) 0.272 1.864

Real GDP(-1) 0.1596** 0.0067

D(Term Deposit Rate) 0.0024 -

Term Deposit Rate (-1) 0.0003 -

D(SBN(-1)) -0.186* -

SBN(-2) -0.092*** -

D(Spread(-3) - -0.0072**

Spread(-4) - -0.0059

T>2014 Q1 0.015 -

T>2015 Q1 - -0.0211***

T=2015 Q3 -0.033*** -0.0337***

Adjusted R-Squared 0.653 0.799

In the long term, an increase of deposits is affected

by changes in real GDP, the 1-month term deposits

rate, nominal SBN and yield spread between the 10-

year SBN and 1-month term deposit rate. Stronger

economic performance would also accelerate

deposit growth, as indicated by a 3.4% bump

in deposits in the event of a 1% increase in real

GDP. In addition, a 1% hike in the term deposit

rate would also precipitate a 0.016% increase in

banking industry deposits.

Based on the first equation, in addition to the effect

of economic growth and deposit rates, deposit

growth would also be influenced by SBN volume

in the long term. An increase in SBN issuances

would reduce total deposits, indicating a shift in

the allocation of funds by the public from bank

deposits to SBN. The second equation pointed to an

inverse and significant correlation with deposits and

spread between the 10-year SBN and 1-month term

deposit rate (spread), indicating that depositors also

consider SBN yields and spread when placing their

funds. A higher SBN yield and broader spread would

lead to fewer deposits.

Estimations using the short-term equation

produced results consistent with the long-term

equation. According to the first equation, deposits

were inversely and significantly correlated with

SBN, indicating a shift in the allocation of funds by

the public from deposits to SBN. Meanwhile, the

second equation showed an inverse correlation

between deposits and spread between the 10-year

SBN and 1-month term deposit rate, revealing the

same trend as the long-term equation.

214 BANK INDONESIA


4.3.1. Foreign Investors

The VECM impulse response function for foreign

investors demonstrated that a shock in the form of

an increase in the government deficit would trigger

an increase in foreign SBN holdings. Moreover,

the foreign investor response would return to

equilibrium in the 10th month. Considering

that foreign investors dominate SBN holdings,

accounting for a 43% share, the results of the

impulse response function already explained most

SBN movements due to a larger government deficit.

On the other hand, foreign investors would also

respond to a wider government deficit by reducing

their deposits in the banking industry.

4.3.2 Insurance Investors

The VECM impulse response function for

insurance investors showed that an increase in the

government deficit would again prompt a surge of

SBN holdings and a decline in deposits held in the

banking industry. The results are consistent with

the ECM estimations, which showed a shift away

from deposit placements to SBN. An increase of

SBN holdings by the insurance industry was also

affected.

4.3.3 Pension Fund Investors

The VECM impulse response function for pension

fund investors showed disparate results compared

to foreign and insurance investors. Pension fund

investors would respond to a broader government

deficit by reducing SBN holdings and increasing

placements of deposits in the banking industry.

Considering that pension fund investors only

account for around 5% of total SBN holdings, the

aggregate shift would be negligible.

1200

800

400

0

-400

-8005 10 15 20 25 30

0

-100

-200

-300

-400

-500

-6005 10 15 20 25 30

Response to Cholesky One S. D. Innovations


-600

-700

-800

-900

-1000

-11005 10 15 20 25 30

Response of SBN_ASING to GOV_DEFICIT

Response of SBN_INSURANCE to GOV_DEFICIT

450

400

350

300

250

200

1505 10 15 20 25 30

Response of DPK_ASING to GOV_DEFICIT

Response of DPK_INSURANCE to GOV_DEFICIT

215BANK INDONESIA





4.3.4 Mutual Fund Investors

The VECM impulse response function for mutual

fund investors revealed that an increase in the

government deficit would again spur an uptick of

SBN holdings and a decline in deposits held in the

banking industry. The results are consistent with the

ECM estimations, which showed a shift away from

deposit placements to SBN.

4.3.5 Individual Investors

The VECM impulse response function for

individual investors showed similar results as

pension fund investors, namely that an increase

in the government deficit would induce a decline

of SBN holdings and an increase of deposits held

in the banking industry. As the investors with the

smallest share of SBN holdings, accounting for

just 2% of the total, the decline of SBN holdings

would not affect the aggregate shift towards SBN.

In addition, the alternative investment options

available to individual investors are considerably

broader compared to the other investors, for

example investment through the capital market

and real sector.

400

200

0

-200

-400

-6005 10 15 20 25 30

400

0

-400

-800

-1200

-1160

-20005 10 15 20 25 30


Response of SBN_PENSIONFUNDS to GOV_DEFICIT Response of DPK_PENSIONFUNDS to GOV_DEFICIT

600

500

400

300

200

100

1000

800

600

400

200

05 510 1015 1520 2040 4025 2545 4530 3050 50


Response of SBN_MUTUALFUNDS to GOV_DEFICIT Response of DPK_ MUTUALFUNDS to GOV_DEFICIT

5 10 15 20 25 30

1000

0

-1000

-2000

-3000

30000

25000

20000

15000

10000

5000

05 10 15 20 25 30


Response of SBN_INDIVIDUAL to GOV_DEFICIT Response of DPK_INDIVIDUAL to GOV_DEFICIT

216 BANK INDONESIA


The unit root testing showed that nearly all variables

were not stationary at level. ADF tests with a trend

and intercept showed that most of the data used

was not stationary at level but stationary at the

first difference. The stationarity testing revealed

that the ECM and VECM methods were in line with

econometric theory.

Estimations using two Error Correction Model

(ECM) equations revealed that in addition to

economic growth, deposits were significantly and

inversely correlated with SBN issuance volume and

yield spread between the 10-year SBN and 1-month

term deposit rate. Such dynamics indicated that the

customers’ decision to place funds in bank deposits

was influenced by the investment return on SBN

yields as well as term deposit rates. Furthermore,

ECM estimations also substantiated a shift in the

public’s funds from bank deposits to tradeable

government securities (SBN).

1. Based on estimations using a Vector Error

Correction Model (VECM), an increase in

government domestic financing would induce

a mixed response amongst the various investors

tested.

a. Foreign, insurance industry and mutual

fund investors, accounting for 43%, 12%

and 5% of total SBN holdings respectively,

would respond to an increase in government

domestic financing by increasing SBN

purchases and reducing placements in bank

deposits.

5.1. Conclusion

5.2 Policy Implications

5. CONCLUSION AND POLICY IMPLICATIONS b. In contrast, an increase in government

domestic financing would induce a decline

of SBN holdings and prompt a surge of

bank deposits amongst pension fund

investors (5% share of total SBN holdings)

and individual investors (2% share).

c. Despite contradicting the direction of

the foreign, insurance and mutual fund

investors, the response of the pension fund

and individual investors would not influence

aggregate demand considering the share

of SBN holdings attributable to both types

of investors is relatively small. In addition,

individual and pension fund investors

have many alternative investment options

available through the real sector.

Considering that the future direction of government

fiscal financing is oriented towards domestic

financing, Bank Indonesia must remain vigilant of

financial system stability because an increase in

SBN issuance volume and spread between the 10-

year SBN and 1-month term deposit rate will erode

bank deposits and ultimately undermine the bank

intermediation function.

217BANK INDONESIA





BIBLIOGRAPHY

Ardagna, Silvia. 2009. Financial Markets’ Behavior Around Episodes of Large Changes in the Fiscal Stance.

European Economic Reviews

Baldacci, E. dan Kumar, M. 2010. Fiscal Deficits, Public Debt, and Sovereign Bond Yields. IMF Working

Paper.

Belke, A dan Polleit T. 2009. Monetary Economics in Globalized Financial Markets. Springers.

Detragiache, E, et al. 2005. Finance in Lower Income Countries: An Empirical Exploration. IMF Working

Paper.

Gale, W dan Orszag, P. 2002. The Economic Effects of Long-Term Fiscal Discipline, Tax Policy Center

Discussion Paper. December.

Hauner, D. dan Kumar, M. 2009. Fiscal Policy and Interest Rates: How Sustainable is the New Economy? IMF

Working Paper 06/112 (Washington: IMF).

Parkin, M. 2012. Macroeconomics. Prentice Hall: USA.

218 BANK INDONESIA


THE IMPACT OF INTERCONNECTEDNESS IN THE INTERBANK MONEY MARKET ON BANKING INDUSTRY EFFICIENCY IN INDONESIA

Article 2

Ndari Surjaningsih4, Januar Hafidz5, Justina Adamanti6, Maulana Haris Muhajir7,

M. Sahirul Alim8

218 BANK INDONESIA

KAJIAN STABILITAS KEUANGANNo. 29, September 2017

219BANK INDONESIA





is the result of bank efforts to maintain adequate

liquidity through short-term funds that are disbursed

as long-term loans/financing. Bank default and/or

illiquid banks can propagate with rapidity to other

banks in the system.

Despite the adverse effects that may arise,

interconnectedness also provides a means to

manage liquidity and transfer risk more efficiently

(Liu, Qulet and Roth, 2015). The benefits, however,

of interconnectedness in the banking industry are

also influenced by the structure of the interbank

market. Allen and Gale (2000) found that resilience

to unexpected liquidity shocks would increase in a

more complex market, namely a market where all

banks are interconnected. Therefore, it has become

a salient issue to analyse the descriptive statistics of

bank interconnectedness in Indonesia.

Interconnectedness can also affect the level of

efficiency achieved at a particular bank because the

interbank money market represents an alternative

source of financing and a means to place bank funds,

which would influence the cost and profit efficiency

of the bank. Consequently, how the benefits of the

interbank money market, as an alternative source

of financing and means to place bank funds, affect

bank efficiency should also be reviewed.

Against that backdrop, this research has two

apposite goals, namely to analyse interbank

transactions in the interbank money market using

network statistics as well as to analyse the impact of

interconnectedness in the banking industry on cost

and profit efficiency.

Against a backdrop of increasing competition in

the financial markets, accompanied by dynamic

technological change in banking operations,

efficiency has become an important factor for the

banks to consider in terms of business sustainability.

In addition, the banks are not only competing

amongst themselves but also with nonbank

financial institutions, which is placing more pressure

than ever on the banking industry to operate more

efficiently (Spong, et al., 1995).

Increasing competition undermines the market

power of a particular bank, which can affect

efficiency. Market power refers to individual

corporate behaviour in terms of controlling the

pricing strategy, while competition deals more with

the interactions between market members as an

aggregate (developing economies Rozas, 2007).

Competition between banks could compel one

bank to raise deposit rates and ultimately create

inefficiencies. Furthermore, less efficiency has also

been linked to an increase in excessive risk-taking

behaviour. An inefficient bank generally faces

operational, lending, market and reputational

problems, which create a high risk profile (Fiordelisi,

Ibanez and Molyneux, 2010).

In terms of financial system stability, potential shocks/

pressures from excessive risk-taking behaviour could

spill over and affect other banks through contagion

or the domino effect due to interconnectedness

in the banking industry that exposes the financial

system. Interconnectedness in the banking industry

1. INTRODUCTION

4 Senior Researcher, Macroprudential Policy Department, Bank Indonesia. E-mail: [email protected] Senior Researcher, Macroprudential Policy Department, Bank Indonesia. E-mail: [email protected] Researcher, Macroprudential Policy Department, Bank Indonesia. E-mail: [email protected] Researcher, Macroprudential Policy Department, Bank Indonesia. E-mail: [email protected] Research Fellow, Macroprudential Policy Department, Bank Indonesia. E-mail: [email protected]

220 BANK INDONESIA


2.1. Efficiency

2. LITERATURE REVIEW

Efficiency is often considered synonymous with

productivity but the two are quite different. The

Production Possibility Curve (PPC), which illustrates

the relationship between output and input, is used

to explain the differences between efficiency and

production. PPC shows the maximum output that

can be produced at a firm in combination with a

certain input. A firm is considered efficient when

producing output along the PPC and, conversely,

is considered inefficient when producing output

below the PPC. Meanwhile, productivity is measured

using the ratio between output and input. In other

words, an efficient company could still raise its level

of productivity (Coelli, et al., 2005).

Bank efficiency is measured using several indicators,

including the BOPO efficiency ratio, cost-to-

income ratio (CIR) and net interest margin (NIM).

A lower BOPO efficiency ratio indicates greater

efficiency because the bank can minimise costs

and maximise operating income. The cost-to-

income ratio (CIR) is the ratio of overhead costs

to interest and non-interest income, therefore a

higher CIR is indicative of greater inefficiency or

less efficiency. Meanwhile, the net interest margin

(NIM) illustrates the performance of the respective

bank’s primary business lines, reflecting how well

asset management can generate interest income

and liabilities can incur interest expenses (Hafidz

and Astuti, 2013).

In the economic literature, bank efficiency is

typically influenced by several factors, including

the organisational structure, prevailing regulations

and level of competition (Hughes, 2008).

Empirically, a number of studies have discussed the

various determinants of bank efficiency. Repkova

(2015) found that capital as well as liquidity and

portfolio risks were inversely correlated with bank

efficiency in the Czech Republic. In contrast, the

return on assets (ROA), interest rates and GDP

were found to correlate positively with bank

efficiency. In the European Union, Mesa, et al.

(2014) found that size, the wholesale funding

ratio and sources of income had a positive effect

on bank efficiency, while the level of competition

and loan diversification were inversely correlated.

In the case of Indonesia, Viverita and Ariff (2011)

showed that size and non-performing loans (NPL)

were inversely correlated with cost and profit

efficiency in the banking industry.

There are two hypotheses that entertain the

relationship between bank competition and

efficiency, namely the competition-efficiency

hypothesis and the competition-inefficiency

hypothesis. On one hand, the competition-

efficiency hypothesis states that an increasing level

of competition would enhance efficiency because

competition would force a bank to minimise costs,

offer lower cost services and simultaneously raise

profits. On the other hand, the competition-

inefficiency hypothesis opines the opposite, namely

that increasing competition would actually reduce

bank efficiency (Shaeck and Cihak, 2008).

221BANK INDONESIA





3.1. Network Statistics

3. RESEARCH METHODOLOGY AND DATA

Network theory is indispensable when measuring

interconnectedness. A network consists of clusters

of nodes (representing financial institutions) and

edges (reflecting the assets and liabilities of a

financial institution as a measure of interbank

contractual liabilities). In a directed network, as the

dominant network structure used in this research

paper, one node is connected to a second node

but the second node is not necessarily connected

to the first. In other words, the relationship is not

reciprocal or mutual. Conversely, in an undirected

network there is a mutual relationship between all

connected nodes (Article Figure 2.1).

Financial interconnectedness benefits the financial

system through greater risk management efficiency.

Nevertheless, Allen and Gale (2000) found that

the structure of the interbank money market

network also has a significant impact on shock

propagation. In the interbank money market,

where all banks are interconnected with a complete

network structure, the respective asset share of

each individual bank is comparatively small and no

single bank is dominant. Consequently, credit risk

is more diversified in comparison to an incomplete

or segmented network structure. Nonetheless,

a complete network structure tends to amplify

contagion risk compared to a segmented structure,

where the risk is isolated and contained only in the

specific segment or cluster.

In general, the interbank money market offers

an alternative means to place funds in terms of

managing liquidity and maximising idle funds to

generate profit. Interconnectedness in the interbank

money market could enhance efficiency but also

exacerbate inefficiency for the banks, depending

on the costs and goals of utilising interbank

funds. In their research concerning the impact

of interconnectedness in the banking industry

on bank efficiency in Brazil, Guerra, et al. (2014)

found that interconnectedness improves bank cost

efficiency. Notwithstanding, interconnectedness

was not significant in terms of improving bank

2.2. Interconnectedness

profit efficiency. Therefore, banking industry

interconnectedness in Brazil was focused more on

managing liquidity rather than as an alternative

source of bank income. The paper by Guerra, et

al. (2014) serves as the primary reference for this

research.

Article Figure 2.1 Network Types

Directed Network

edge edge

node node

Undirected Network

222 BANK INDONESIA


According to network theory, there are several

basic terms used to explain the primary goal of this

research. The degree of node i is the number of edges

that start and end at node i. A bank with a higher

degree implies a greater number of connections with

other banks. The indegree of node i in the number

of edges that end at node i, while the outdegree is

the number of edges that originate from node i. A

bank with a higher indegree and outdegree shows

a higher frequency of lending and borrowing with

other banks. A weighted network calculates the

value of interbank transactions, thus revealing the

dominance, either as lender dominance (weighted

outdegree) or borrower dominance (weighted

indegree). A path is a cluster of nodes connected

through several edges. In a weighted network, the

weight of the path is the total of all weighted edges

between the first node and the last in the path.

Based on the terms explained above, network

centrality can be calculated, namely the importance

of one node relative to the network. Closeness

is a measure of the average distance from one

node to another in a network, thus reflecting the

closeness of one node to the others. Betweenness

is a measure of the extent to which a node acts as

an intermediary by connecting to the other nodes

that are not connected to each other, as measured

by the number of shortest paths that pass through

the given node.

Network density is measured using the clustering

coefficient. A higher clustering coefficient indicates

a denser network or more connected nodes in the

network. Meanwhile, the degree distribution is

used to observe the degree of connectivity between

the nodes, either concentrated or not. The measure

is the degree frequency distribution of a node in

a network. A concentrated network implies a few

nodes with a high degree and many nodes with a

low degree. In contrast, a complete network occurs

when most nodes have a relatively consistent degree.

One distribution that meets the characteristics of

degree distribution is the scale-free (power law)

distribution, which has fewer highly connected

nodes, leading to a relatively concentrated degree

distribution.

In response to the second research question, the

Stochastic Frontier Analysis (SFA) methodology

developed by Battese and Coelli (1995) was used to

generate efficiency measures/data. The inefficiency

variables were subsequently used as dependent

variables to observe whether the interconnectedness

variables, along with the other independent/

explanatory variables, influenced bank efficiency.

This was adapted from the method used by Guerra,

et al. (2014), consisting of two equations, namely

the SFA equation and the inefficiency determinant

equation.

Efficiency frontier analysis was conducted from two

perspectives, namely cost efficiency and profit efficiency.

In terms of cost efficiency, the banks strive to minimise

the costs, while profit efficiency implies that the banks

seek to maximise profits. Such characteristics have

different implications when formulating the Stochastic

Frontier Analysis (SFA).

The frontier cost function can be expressed as

follows:

3.2. Efficiency Measurement

αt ln ( – )it + – ln ( – )it + Σ = 1 δj ln ( – )it ln ( – )it + uit + vit

w1 3w1 yj w11w2 jw2 z w22

ln (C/w2 z)it = ß0 + Σ = 1ßj ln ( – )it + – Σ =1 Σ =1 ßjk In ( – )it In ( – ) +3 3 3y3 yj yk1j j k j z z2

223BANK INDONESIA





Based on the Stochastic Frontier Analysis (SFA) and

network statistics described in the previous chapter,

Article Table 2.1 summarises the 18 equations

estimated to analyse the impact of banking industry

interconnectedness on bank efficiency, which

have been grouped into two categories, namely

the inefficiency equations using the frontier cost

approach and the frontier profit approach. Each

category will utilise explanatory variables added

gradually.

3.3. Research Model

Equation (1) was estimated as a translog functional

form, where i is the bank and t is the period, while j

= k = 1, 2, 3 are the three output variables. Output

(y), as used in this model, consist of credit, securities

and placements at another bank. In addition, there

are two input variables (w), namely the interest

expense on total deposits and non-interest income

on total assets, as well as one fixed input variable (z),

namely total earning assets. Output to total earning

assets was normalised to reduce heteroscedasticity

and facilitate a residual comparison of each

bank estimated to calculate the inefficiency.

Normalisation by input price, w_2, aimed to achieve

price homogeneity. v-it is the random error term,

while u_it represents the level of inefficiency.

The notation of the cost function is positive in the

inefficiency variable because the cost is considered

inefficient when above its frontier. Oppositely, in the

profit function, inefficiency is negative. Therefore, a

company is considered inefficient when below its

frontier. The profit function equation is expressed

as follows:

uit = θ0+θit xit+θt bt+mit

αt ln ( – )it + – ln ( – )it In ( – )it + Σ = 1 δj ln ( – )it ln ( – )it - uit + vit

w1 w1 w1 w13 yj1w2 w2 w2 w2j z2

ln (π/w2 z)it = ß0 + Σ = 1ßj ln ( – )it + – Σ =1 Σ =1 ßjk In ( – )it In ( – )it +3 3 3yj yj yk1

j j k z z z2

Equation (2) Meanwhile, the determinant of

inefficiency, per Battese and Coelli (1995), was

formulated as follows:

consisting of the equity-to-asset ratio (ETA),

assets, the Herfindahl-Hirschman Index (HHI) and

a dummy bank group. ETA represents the bank’s

ability to optimise its resources. Assets are a proxy

of bank size and the Herfindahl-Hirschman Index

(HHI) represents the level of bank competition.

Vector bt represents interconnectedness in the

banking industry using several network statistics

indicators.

The three equations above were estimated

simultaneously with the maximum likelihood

method using STATA software and an sfpanel

similar to Belotti, et al. (2012). Referring to Guerra,

et al. (2014) as well as Bos and Koetter (2007), this

research utilises negative performance indicators as

additional variables in the frontier profit equation

to overcome the possibility of a negative profit

variable that could not be transformed in the form

of a logarithm.

Equation (3) Where mit is defined as a truncation

of the normal distribution with a average of zero

and variance 𝜎2. Vector xit is the control variable,

224 BANK INDONESIA


Article Table 2.1 Inefficiency Equations

Article Table 2.2 Data

Model Independent Variable

C P VCB

C1 P1 VCB, Clustering

C2 P2 VCB, Clustering, Degree, Closeness, Betweenness

C3 P3 VCB, Clustering, Indegree, Outdegree

C4 P4 VCB, Clustering, W_Indegree, W_Outdegree

C5 P5 VCB, Alpha

C6 P6 VCB, Alpha, Degree, Closeness, Betweenness

C7 P7 VCB, Alpha, Indegree, Outdegree

C8 P8 VCB, Alpha, W_Indegree, W_Outdegree

Data Definition Source

Credit (Rp) Total outstanding bank loans at nonbanks

Monthly Commercial Bank Reports,Bank Indonesia

Liquid assets (Rp) Total liquid assets held by a bank for a given period

Placements at another bank Total bank placements at another bank

Earning Aset Total bank placements in the form of credit, securities investments and other fund placements

Interest expense (Rp) Total interest expenses

Not Interest expense (Rp) Total non-interest expenses

Assets (Rp) Total assets

Equity (Rp) Total capital

Deposits (Rp) Total deposits

Profit (Rp) Earnings before interest and tax (EBIT)

Costs (Rp) Operating costs

Call money interbank transactions recorded on the LBU form

Interbank call money placements at another bank

This research utilised data from the Monthly

Commercial Bank Reports (LBU) covering the period

from Q3/2010 to Q4/2015. The sample includes 93

banks, excluding Islamic banks and several banks

with incomplete data. Article Table 2.2 presents a

summary of the variables used.

3.4. Data

4.1. Network Statistics

4. RESULTS

Private banks tended to dominate interbank money

market transactions (Article Graph 2.2) and that trend

did not change during the observation period. In terms

of weighted degree, consistent with market share,

private banks and regional banks initiated the largest

total of transactions, primarily because both bank

groups are populated by the most members. Based on

average transactions per bank by bank type, however,

state-owned banks, joint venture banks and foreign

banks transacted more frequently in the interbank

money market.

According to the weighted indegree, private national

and regional banks were dominant. In terms of the

average per bank, state-owned banks were more

dominant as borrowers compared to the other bank

225BANK INDONESIA





Foreign

Joint Venture

Regional Banks

State-Owned Banks

Private26%

4%

48%

6%

9%

Article Graph 2.1 Composition of Banks Transacting in the Interbank Money Market

Article Graph 2.2 Weighted Degree by Bank Type and Average per Bank by Bank Type

Joint Venture

Joint Venture

State-Owned Banks

State-Owned Banks

Foreign

Foreign

Regional Banks

Regional Banks

Private

Private

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Weighted Degree by Bank Type

2010 2011 2012 2013 2014 2015 Rata2

15%

12%

27%

14%

37%

14%

11%

21%

17%

37%

11%

12%

25%

16%

37%

9%

10%

33%

15%

35%

11%

10%

31%

14%

33%

11%

10%

33%

10%

36%

12%

11%

27%

14%

36%

4E+13

3SE+13

3E+13

2SE+13

2E+13

1SE+13

1E+13

5E+12

0

Average Weighted Degree per Bank by Type

2010 2011 2012 2013 2014 2015

groups (Article Graph 2.4 – Weighted Indegree by

Bank Type). Regarding weighted outdegree, state-

owned banks and regional banks were dominant.

On the other hand, based on the average per

bank by bank type, state-owned banks remained

dominant as lenders in the interbank money market

(Article Graph 2.5). In general, private national

banks played a large role in lending transactions in

Article Graph 2.3 Weighted Indegree by Bank Type

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Weighted Indegree by Bank Type

2010 2011 2012 2013 2014 2015 Rata-rata

24%

16%

15%

10%

34%

22%

14%

16%

13%

36%

15%

17%

15%

14%

39%

11%

13%

25%

14%

36%

13%

14%

27%

12%

35%

12%

14%

21%

9%

45%

16%

15%

20%

12%

37%

1.8E+13

1.6E+13

1.4E+13

1.2E+13

1E+13

8E+12

6E+12

4E+12

2E+12

0

Average Weighted Indegree per Bank by Type

2010 2011 2012 2013 2014 2015

226 BANK INDONESIA


Article Graph 2.4 Weighted Outdegree by Bank Type

Article Graph 2.5 Large and Small Bank Interaction Article Graph 2.6 Interbank Rate Interaction between Large and Small Banksl

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Weighted Outdegree by Bank Type

2010 2011 2012 2013 2014 2015 Rata-rata

6%7%

28%

18%

40%

7%7%

27%

22%

37%

7%6%

34%

18%

34%

6%6%

40%

15%

33%

10%

7%

34%

17%

32%

11%

6%

45%

11%

28%

8%

7%

35%

17%

34%

2.5E+13

2E+13

1SE+13

1E+13

5E+12

0

Average Weighted Outdegree per Bank by Type

2010 2011 2012 2013 2014 2015

the interbank money market in terms of intensity

and transaction volume.

To investigate the presence of segmentation between

bank clusters, the banks were categorised based on

specific criteria, asset size for instance. There were

four interbank interaction groups9, namely big bank

to big bank, big bank to small bank, small bank to big

bank and small bank to small bank. Article Graph 2.6

shows that the interactions between big banks were

dominant in the interbank money market, followed

by small banks to big banks and small banks to small

banks. Such conditions reflect lending prudence at

the big banks, namely by favouring other large banks

rather than the small banks, which is indicative of

segmentation in the interbank money market. In

terms of interest rates, transactions between small

banks consistently applied the highest interest rates

(Article Graph 2.7).

Average closeness between the banks continued to

increase year on year (Article Graph 2.8). Meanwhile,

the role of banks as intermediaries also expanded, as

evidenced by the increase in betweenness, despite

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Weighted Degree Interaksi Bank Besar & Kecil

2010 2011 2012 2013 2014 2015

15%

12%

27%

14%

14%

11%

21%

17%

11%

12%

25%

16%

9%

10%

33%

15%

11%

10%

31%

14%

11%

10%

33%

10%

B-K K-KB-B K-B

5.0

4.0

3.0

2.0

1.0

0.0

Suku Bunga PUAB (%)

2010 2011 2012 2013 2014 2015 2016

9 Banks considered first as lenders and second as borrowers.

Joint Venture

State-Owned Banks

Foreign Regional Banks

Private

Joint Venture State-Owned BanksForeign Regional Banks Private

227BANK INDONESIA





moderating slightly in 2015 (Article Graph 2.9). The

average clustering value, however, remained relatively

stable for the duration of the observation period

(Article Graph 2.10), indicating no significant changes

in the segmentation structure of the banking industry.

Based on Article Graph 2.11, the distribution

degree of interbank money market transactions

tended to concentrate on the left side of the

graph, implying a low degree. This was confirmed

by the alpha coefficient (power law), for which

the value remained relatively stable at around 0.3

for the last six years of the period (Article Graph

2.12). A stable alpha value showed that the level

of transaction concentration did not change

significantly.

100%

90%

80%

70%

60%

50%

40%

30%

0.009

0.008

0.008

0.007

0.007

0.006

0.006

0.005

0.005

0.004

2010 20102011 20112012 20122013 20132014 20142015 2015

Average Closeness Average Betweeness

Article Graph 2.7 Average Closeness Article Graph 2.8 Industry Betweenness

0.210

0.205

0.200

0.195

0.190

0.185

0.36

0.35

0.34

0.33

0.32

0.31

0.30

0.29

0.28

0.203

0.35

0.188 0.190

0.192

0.206

0.198

2010

2010

2011

2011

2012

2012

2013

2013

2014

2014

2015

2015

Average Clustering

Alpha (Power law)

Article Graph 2.9 Industry Average Clustering Coefficient

Article Graph 2.10 Degree Distribution Article Graph 2.11 Alpha Coefficient (Power Law)

0.32

0.30

0.31

0.32 0.33

0 10 20 30 40 50 60 70 80 90 100

Degree Distribution

100%

90%

80%

70%

60%

50%

40%

30%

228 BANK INDONESIA


The results of the impact analysis of

interconnectedness on inefficiency from the cost

and profit perspectives are explained in this chapter.

In both equations, inefficiency is the dependent

variable. Therefore, a negative coefficient of the

dependent variable implies that the impact will be a

reduction of inefficiency or, in other words, greater

efficiency and vice versa, a positive coefficient would

imply increasing inefficiency. As a test of robustness,

each frontier was estimated twice, namely using the

clustering coefficient and alpha coefficient (power

law).

Cost Frontier Inefficiency Equation

The left panel of Article Table 2.3 summarises

the results of the cost frontier equation using the

clustering coefficient. On the cost side, the banks

were more efficient as borrowers, as evidenced by

the Windegree variable in the C4 model, which was

negative and significant. In contrast, inefficiencies

appeared when the banks acted as lenders, as

4.2. Interconnectedness and Efficiency

demonstrated by the outdegree and Woutdegree

variables in models C3 and C4, which were positive

and significant. Such results are explained by

lower interbank rates compared to other types of

placements, especially credit.

The banks were inefficient as intermediaries, as

indicated by the betweenness variable in the C2

model, which was significant. Furthermore, the

closeness of one bank to another also exacerbated

inefficiency, as shown by the positive and significant

closeness variable in model C2. This was possibly

due to segmentation, thereby limiting bank access

to other banks in terms of obtaining lower interest

rates.

The robustness of the models was tested by

estimating the cost frontier by substituting the

clustering coefficient with the alpha coefficient

(power law), the results of which are presented

in the right panel of Article Table 2.3. Although

the alpha variable was not significant, the models

were shown to be robust because no changes

were identified in the direction or significance in all

models.

Article Table 2.3 Cost Frontier Estimation Results

Variable Model C Model C1 Model C2 Model C3 Model C4 c Model C5 Model C6 Model C7 Model C8

HHI 3.240*** 3.318*** 3.307*** 3.358*** 3.222*** HHI 2.690*** 3.097*** 3.160*** 3.065***

ETA -0.367*** -0.376*** -0.394*** -0.402*** -0.393*** ETA -0348*** -0.377*** -0.381*** -0.379***

Size -0.084*** -0.091*** -0.105*** -0.103*** -0.091*** Size -0.70*** -0.088*** -0.088*** -0.080***

State-Owned Banks -0.120 -0.112 -0.167 -0.115 -0.109 Persero -0.078 -0.125 -0.074 -0.075

Foreign -0.314 -0.337 -0.313 -0.349 -0.330 Asing -0.249 -0.253 -0.286 -0.283

Joint Venture -0.082** -0.088** -0.081** 3.240*** 3.240*** Campuran -0.086** -0.082** -0.091** -0.087**

Regional Banks -0.453*** -0.465*** -0.421*** -0.431*** -0.401*** BPD -0.483*** -0.458** -0.471*** -0443***

Clustering 0.115 -0.001 -0.028 - 0.036 Alpha -0.050 -0.040 -0.023 -0.039

Degree -0.013 Degree -0.017

Closeness 0.309*** Closeness 0.274***

Betweenness 2.823*** Betweenness 2.601***

Indegree - 0.006 Indegree -0.003

Outdegree 0.042*** Outdegree 0.029**

Windegree - 0.002** Windegree -0.002**

Woutdegree 0.004*** Woutdegree 0.004***

_cons -18.352*** - 18.741*** - 18.459*** -18.779*** -18.110*** _cons -16.860*** -17.424*** -17.784*** -17.328***

t 22 22 22 22 22 t 22 22 22 22

observations 2046 2046 2046 2046 2046 observations 2046 2046 2046 2046

Total Banks 93 93 93 93 93 Jumla Bank 93 93 93 93

229BANK INDONESIA





Profit Frontier

Concerning profit inefficiency (left panel of Article

Table 2.4), the banks became inefficient in terms of

maximising profit as transaction intensity increased

in the interbank money market. Such developments

were confirmed by the positive and significant

degree variable in model P2. More specifically, the

banks became inefficient as lenders, as indicated

by the indegree and windegree variables in models

P3 and P4. The same conclusion was drawn by

Tabak, et al. (2014), namely that the interbank

money market is not an optimal means to enhance

profit efficiency. Meanwhile, the banks were

efficient in maximising profit when close to another

bank because the idle funds could be lent to the

other bank. The same robustness test showed no

significant changes in the independent variables but

the alpha coefficient was negative and significant

(right side of Article Table 2.4), indicating that the

banks were more efficient in terms of maximising

profit when they transacted less in the interbank

money market. Those findings corroborate the

previous conclusion that relates to degree.

Control Variable

The control variable was similar to the cost inefficiency

and profit inefficiency variables in terms of direction and

significance. The Herfindahl-Hirschman Index (HHI), as

a proxy of competition, was positive and significant.

The results can be interpreted as a higher HHI implies

a higher level of inefficiency. A higher HHI points to

lower competition due to increasing concentration,

which ultimately made the banks inefficient. The ETA

variable was negative and significant, indicating that

more equity made the banks more efficient because

they could mitigate the potential maturity mismatch,

which would incur a higher cost for the bank in terms

of seeking other funding sources. Meanwhile, the

size variable was negative and significant, meaning

that the larger banks were more efficient. Such

dynamics are consistent with economies of scale in the

microeconomic literature.

Article Table 2.4 Profit Frontier Estimation Results

Variable Model C Model C1 Model C2 Model C3 Model C4 c Model C5 Model C6 Model C7 Model C8

profit inefficiency (u) profit inefficiency (u)

HHI 20.508*** 20.512*** 19.407*** 19.345*** 19.509*** HHI 21.718*** 20.271*** 20.270*** 20.933***

ETA -0.161*** -1.061*** -0.975*** -0.976*** -0.955*** ETA -1.015*** -0.931*** -0.937*** -0.912***

Size -0.233*** -0.232*** -0.284*** -0.281*** -0.254*** Size -0.258*** -0.314*** -0.307*** -0.279***

State-Owned Banks -0.791*** -0.794*** -0.597 -0.609*** -0.684*** Persero -0.278*** -0.942 -0.074 -1.019

Foreign 0.018 -0.020 -0.006 -0.043 -0.062 Asing -0.159 0,124 -0.286 0.061

Joint Venture 0.162** -0.164** -0.023 0.018 0.069 Campuran -0.374*** 0.197 -0.091** 0.257**

Regional Banks -1.712*** -1.714*** -1.572*** -1.583*** -1.617*** BPD -1.483*** -1.354*** -0.471*** -1.395***

Clustering 0.024 -0.083 -0.085 - 0.104 Alpha -1.043*** -0.897*** -0.908 -0.925***

Degree -0.219 *** Degree 0.233

Closeness -1.271*** Closeness 0.274***

Betweenness 2.358 Betweenness 2.601***

Indegree -0.157*** Indegree 0.158***

Outdegree -0.026 Outdegree -0.021**

Windegree 0.013** Windegree 0.013**

Woutdegree -0.005*** Woutdegree -0.005***

_cons -123.833*** -123.868*** - 116.112*** -116.366*** 116.307*** _cons -133.126*** -1223912*** -123.017*** -124.365***

t 22 22 22 22 22 t 22 22 22 22

observations 2046 2046 2046 2046 2046 observations 2046 2046 2046 2046

Total Banks 93 93 93 93 93 Jumla Bank 93 93 93 93

230 BANK INDONESIA


5.1. Conclusion

5. CONCLUSION AND RECOMMENDATIONS

• In terms of network statistics, there are tendencies

toward concentration and segmentation in the

interbank money market. Such conditions are

evidenced by a lower clustering value and a low

degree of scale-free distribution.

• Interbank transactions by borrower banks

increased cost efficiency but also caused

inefficiency in terms of maximising profit as

lender banks because interbank transactions

were utilised more for short-term liquidity

management rather than to maximise profits,

such as placements in other earning assets.

• The presence of betweenness when seeking

funds from the interbank money market could

undermine efficiency.

• A greater degree of closeness caused cost

inefficiency. This was possibly due to interbank

• Measures are required to encourage banks with

a low degree distribution to interact mutually in

order to minimise the concentration risk, while

simultaneously increasing interbank money

market access to other clusters.

• Incentives should be considered for banks with

a low degree distribution to open new credit

lines to other banks in order to stimulate more

efficient interbank transactions in terms of costs

and profits.

5.2. Recommendations

money market segmentation that influences

the interest rates. In contrast, a higher degree

of closeness created efficiency in terms of

maximising profit because interbank money

market activities encouraged the banks to

maximise idle fund placements.

231BANK INDONESIA





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232 BANK INDONESIA


Information and Orders:

Publisher :Bank Indonesia

Jl. MH Thamrin No.2, Jakarta

Indonesia

This edition is published in September 2017 dan didasarkan pada data dan informasi per and is based on

data and information available as of Juni 2017, unless stated otherwise.

The PDF format is downloaded from

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Source : Bank Indonesia, unless stated otherwise.

For inquiries, comment and feedback please contact :Bank Indonesia

Departemen Kebijakan Makroprudensial

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Email : [email protected]

The preparation of the Financial Stability Review is one of the avenues through which

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monetary and financial system stability for sustainable national economic development”

FSR is published biannually with the objectives :

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Director Erwin Rijanto - Filianingsih Hendarta - Linda Maulidina - Farida Peranginangin

Coordinator and Editor Rozidyanti – Theresia Silitonga - Agus Fadjar Setiawan - Riza Putera – Agung Bayu Purwoko

Drafting Team Retno Ponco Windarti, M. Firdaus Muttaqin, Kurniawan Agung, Ita Rulina, Indra Gunawan, Ndari

Suryaningsih, Cicilia A. Harun, Sri Noerhidajati, Mirza Yuniar, Januar Hafidz, Viana Sari, Khairani

Syafitri, Bayu Adi Gunawan, Susana Wibisana, Heny Sulistyaningsih, Hero Wonida, Vienella

Zarmida, Lisa Rienellda, Arifatul Khorida, Zulfia Fathma, Anita, Sagita Rachmanira, Astrid Fiona

H., Annisaa Prima Astuti, Maulana Harris Muhajir, Ibrahim Adrian Nugroho, Anindhita Kemala D,

Apsari Anindita N.P, Rani Wijayanti, Harris Dwi Putra, Pita Pratita, Vergina Hapsari, Ardo Prayoga,

Kartina Eka Darmawanti, Aski Catranti, Saraswati, Prayudhi Azwar, Mario Simatupang, Noviati,

Rakhma Fatmaningrum, Tri Siwi Permadi Astuti, Fransiskus Xaverius Tyas Prasaja, Martha K. Pratiwi,

Muhammad Adrianto Eko Budhi Setiyanto, Donny Ananta, Lely Yudha Prasetyaningsih,Taufik

Saleh, I Gede Arnawa.

Translated by Matthew Burrows.

OTHER DEPARTMENT CONTRIBUTION ON SELECTED ANALYSIS Economic and Monetary Policy Department

Financial System Surveillance Department

SME Development Department

Islamic Economics and Finance Department

Statistics Department

Financial Market Development Department

Payment System Policy and Oversight Department

Payment System Management Department

East Java Representative Office Bank Indonesia

PRODUCTION AND DISSEMINATION TEAM Saprudin, Elsa Puspa Silfia, I Made Yogi


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