Financial Stability Review (FSR) · The PDF format is downloadable from: ... [email protected] ......

The preparation of the Financial Stability Review (FSR) is one of the avenues

through which Bank Indonesia achieves its mission “to safeguard the stability of the Indonesian

Rupiah by maintaining monetary and financial system stability for sustainable national

economic development”.

Publisher:

Bank Indonesia

Information and Orders:

This edition is published in September 2014 and is based on data and information available as of June 2014,unless stated otherwise.

Source: Bank Indonesia, unless stated otherwise.

The PDF format is downloadable from: http://www.bi.go.id

For inquiries, comments and feedback please contact:

Bank Indonesia

Macroprudential Policy Department (DKMP)

Jl.MH Thamrin No.2, Jakarta, Indonesia

Email: [email protected]

FSR is published biannually with the objectives:

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

To evaluate potential 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 stability.

Financial Stability Review( No.23, September 2014)

MACROPRUDENTIAL POLICY DEPARTMENT

ii

“Maintaining Financial Stabilityamid Economic Slowdown”

iii

Table of Contents ........... ................................................................................................................................................. iii

Glossary ............ ............................................................................................................................................................... vii

Foreword.......... ................................................................................................................................................................ ix

......................................................................................................................................................... 3 Chapter 1. Financial System Stability ................................................................................................................................ 9 1.1. Development of Risks on Global and Regional Financial Markets .................................................................. 9

........................................................................................... 12 1.3. Financial System Stability in Indonesia ........................................................................................................... 14 1.4. The Financial Cycle of Indonesia .................................................................................................................... 15 1.5. Sources of Financial Imbalances .................................................................................................................... 17 1.6. Sources of Vulnerability ................................................................................................................................. 24 Box 1.1. Financial Cycle of Indonesia ................................................................................................................... 32

........................................................................................ 36.......................................................... 38

Chapter 2. Financial Markets ........................................................................................................................................... 43 2.1. Financial Market Risks .................................................................................................................................... 43 2.2. The Financial Market as a Source of Non-Bank Financing ............................................................................. 55

.................................................................................... 59 Box 2.2. Shadow Banking in Indonesia ................................................................................................................. 63 Chapter 3. The Household and Corporate Sectors ........................................................................................................... 69 3.1. Household Sector Assessment ....................................................................................................................... 69 3.2. Corporate Sector Assessment ........................................................................................................................ 76

................................................................................. 85 ................................................................................. 86

............................................................................ 91 4.1. The Banking Sector ......................................................................................................................................... 91

......................................................................................................... 114 ........................................................................... 118

........................... 120

Chapter 5. Financial System Infrastructure ...................................................................................................................... 125 ....................................................................................................................... 126

................................................................................................... 127 ............................................................................................................................ 128

.................................................................................................. 130 .......................................................................................... 131

.............................................................................................................................................................. 133 .......................................................................................... 135

............................................................................................................... 145

Bibliography ..... ................................................................................................................................................................ 153

able ntent

iv

i t able a an Fi e

able1.1. . 101.2. .. 161.3. Stress/Crisis ........................................................ 171.4. Several Countries with the Strongest

............................ 28Box Table 1.1.1. Concordance Index of Financial Cycle Variables (Narrow Credit) ..................................... 33Box Table 1.1.2. Concordance Index of Financial Cycle Variables (Broad Credit) ..................................... 33

Business Cycle ................................................... 34

onset of Crisis/Stress ......................................... 34

2.1. 10-Year SBN Yield and Regional Yields ............. 482.2. .. 48

............. 512.4. Bank and Non-Bank Financing ......................... 552.5. .. 562.6. Volume of Bank Funding based on

........................... 57Box Table 2.1.1. Funding through the Capital Market

.................................... 60

......... 703.2. and Savings based on Monthly Income .............. 73

............................................ 733.4. .. 74

.................................... 793.6. by Sector ........................................................... 79

............ 823.8. Corporate Credit by Economic Sector .............. 82

Economic Sector ............................................... 83

Direct Investment by Economic Sector ............ 84Box Table

................ 87Box Table

................. 87

Box Table 3.2.3 Altman Z-score ................................... 88Box Table

Exchange Rates ................................................ 88

....................... 93 ............................... 93

........................ 94 ... 95

........................ 95 ............................... 96

.............. 98 ..................... 99

........................................ 101 ............. 101

4.11. Deposit Rates .................................................. 103 ......................... 104

the Banking Sector ........................................... 1054.14. SBN Holdings in the Banking Sector ................. 106

(in trillions of rupiah) ....................................... 1064.16. Breakdown of Income Accounts (in trillions of rupiah) ....................................... 1074.17. Breakdown of Cost Accounts (in trillions of rupiah) ....................................... 107

...................... 108 ............................... 110

........ 116 .......................... 117

Box Table 4.1.1. Granger Causality Test ....................... 118Box Table 4.1.2. Regression of MSME Credit Risk ............ 118

and Electronic Money ...................................... 127

v

a .......................... 11

............... 11 ......... 12

........................................ 131.5. External Debt ................................................... 131.6. Financial System Stability Index ....................... 14

in June 2014 ....................................................... 141.8. Financial Cycle of Indonesia ............................. 15

............................. 18 ........................... 18

...................... 19

............................ 19

.............................................. 201.14. ............ 20

................. 21 ..................... 23

1.17. Sources of Funds and Instruments of ..... 23

1.18. External Debt by Tenor ..................................... 231.19. External Debt by Economic Sector ................... 241.20. Fed Fund Survey: .................. 251.21. Growth in Emerging Market Countries ............ 251.22. CDS in Advanced Countries .............................. 261.23. CDS in Neighbouring Countries ........................ 261.24. CDS in Several Emerging Market Countries ...... 27

Emerging Market Countries ............................. 27

and SBN ............................................................ 281.27. Financial Account ............................................. 291.28. Current Account and Exchange Rate ............... 29

............................ 301.30. RI Counterpart Exports in 2013 ........................ 30

........................................... 311.32. Value of Bond Issuances ................................... 311.33. Growth of Deposits and Credit as well as

................................ 31Box Graph 1.1.1. A Common Cycle of the Financial Cycle (Narrow Credit) and Business Cycle ........ 33Box Graph 1.1.2. A Common Cycle of the Financial Cycle (Broad Credit) and Business Cycle .......... 33Box Graph 1.2.1.Macroeconomic Indicators of Indonesia during the 2008 Crisis and Current .. 36Box Graph 1.2.2 Credit Imbalances ............................. 37Box Graph 1.2.3 Deposit Imbalances ........................... 37

2.1. Non-Resident Flows: Shares, SBN & SBI .......... 442.2. .. 44

..................... 44....................... 45

...... 452.6. Foreign Exchange Interbank Money Market .... 45

.... 45 ...... 46

Behaviour ......................................................... 46 ........................... 46 ............................ 46

......... 47 ............................... 47

.... 47 ... 47

2.16. Foreign Net Flow to SBN and IDMA Index ....... 482.17. SBN Holdings .................................................... 40

..................................... 492.19. Rebased SBN Yield by Tenor ............................. 49

.................. 502.21. Rebased Corporate Bond Yield by Tenor .......... 502.22. Corporate Bond Yield Curve ............................. 50

.................... 502.24. Foreign Net Flow and Holdings of Corporate Bonds.. 50

............... 51 ...................... 51

2.27. Flow to Shares and JCI ...................................... 51 ............................... 52

............................. 52 ...................... 52

................. 522.32. Growth of Mutual Funds (yoy) ........................ 53

................................ 532.34. NAV trend of Mutual Funds by Type ............... 532.35. NAV of Mutual Funds by Type ......................... 54

............... 542.37. Nominal Value of Bonds ................................... 552.38. Capital Market Financing ................................. 56

..... 59 ..... 59

....... 60 ....... 60

2013-Semester I 2014 ........................................ 61

2013-Semester I 2014 ...................................... 61 ..................................... 61

................................... 61

vi

aBox Graph 2.1.9. JCI, Yield and the Rupiah in 2014 ..... 62Box Graph 2.1.10. Actual and Forecasted Indicators ... 62Box Graph 2.2.1. Exposure of Non-Bank Financial

Intermediaries .................................................. 64Box Graph 2.2.2. Growth of Non-Bank Financial

Intermediaries .................................................. 64

3.1. .. 70 .................................................... 70

3.3. Retail Sales Growth .......................................... 713.4. .. 723.5. .. 72

............... 73 ......................... 74

......... 75

(per June) ......................................................... 75 .......... 76

... 76 .... 76

3.13. Total Number of Companies ............................ 76 .... 77

................................. 77

..................................................... 783.17. .. 79

Z-score .............................................................. 80 ... 80

................................ 80 .... 81 .... 81

................................. 82Box Graph 3.1.1. Non-Regional Commercial Bank Credit

.............................. 85Box Graph 3.2.1 . 87

.................................................. 924.2. . 92

.... 924.4. Deposit Growth (yoy) ....................................... 944.5. .... 94

......................... 94 ..................... 96

4.8. Increases in Interest Rates ............................... 964.9. Credit Growth .................................................. 974.10. Credit Growth by Currency .............................. 97

............................. 974.12. Credit Growth by Economic Sector .................. 98

.............................. 99

4.14. Annual MSME Credit Growth by Economic Sector 99 ............... 100 ................ 100

......................... 100

............................................................ 101 ............ 102

Semester I-2014 ............................................... 104 ......................................................... 105

............ 108 .................... 108

........................................ 109 ......... 109

................................. 110 .................... 110

4.28. ...................... 111

................................................. 111 ................. 112

Higher Interest Rates ........................................ 112 .................. 112

......................................... 113 ....................... 113

.............................................. 1134.36. Finance Company Financing by Business Sector . 114

....................... 114 ..................... 114

4.39. Sources of Funds .............................................. 115 ...... 116

in Semester I-2014 ........................................... 1164.42. Share of Industry Assets by Business Sector (per December 2013) ....................................... 1164.43. Insurance Industry Assets and Investments ...... 1164.44. . 1164.45. Insurance Industry Growth and Density........... 117Box Graph 4.1.1. Credit Risk and Economic Growth .... 119

5.1. .. 128 ......................... 129

.......................... 129 ....................... 129

vii

GlossaryAFS: Available for SaleUS: United StatesAPMK: Card-based payment instrumentsASEAN: AssociationofSoutheastAsianNationsATM: AutomaticTellerMachineATMR: Risk-weightedassetsBCBS: BaselCommitteeonBankingSupervisionBIS: BankforInternationalSettlementsBI-RTGS: BankIndonesia–RealTimeGross

Settlement(BI-RTGS)systemBI-SSSS: BankIndonesiaScriplessSecurities

SettlementSystemBOPO: Efficiencyratioofoperatingcoststo

operatingincomeBPD: Regional bankBPR: Rural Bankbps: basis pointBUKU: Classificationofcommercialbanksbasedon

businessactivityBUS: Islamic bankCAR: CapitalAdequacyRatioCCB: CountercyclicalcounterbufferCDS: Credit Default SwapCPO: Crude palm oilDER: DebttoequityratioDTI: DebttoincomeratioDPK: DepositsD-SIB: Domestic–SystemicallyImportantBankDP: DownpaymentDRC: Disaster Recovery CentreDSR: DebtServiceRatioEM: EmergingMarketFDI: Foreign Direct InvestmentFKSSK: FinancialSystemStabilityCoordination

ForumFSAP: Financial Sector Assessment ProgramFSB: Financial Stability BoardFSI: Financial Stability IndexG20: TheGroupofTwentyGDP: GrossDomesticProductIDMA: InterdealerMarketAssociationIHK: ConsumerPriceIndex(CPI)IHSG: IDX Composite IndexIKK: ConsumerConfidenceIndex(CCI):IKNB: Non-bankfinancialinstitutionIMF: InternationalMonetaryFundISIK: FinancialInstitutionStabilityIndexISPK: FinancialMarketStabilityIndexISSK: Indonesia Financial Stability Index

KI: Investment CreditKIK: Consumer LoansKMK: Working Capital CreditKPMM: MinimumStatutoryCapitalRequirementKPR: MortgageloanLCR: LiquidityCoverageRatioLDR: LoantodepositratioLKD: Digital Financial ServicesLTV: Loan to valueLPS: TheDepositInsuranceCorporationL/R: Profit/lossMinerba: MineralandCoalMiningNAB: NetAssetValueNFA: NetForeignAssetsNFL: NetForeignLiabilitiesNII: NetInterestIncomeNIM: NetInterestMarginNPF: Non-performingfinancingNPI: Indonesia Balance of PaymentsNPL: Non-performingloansOJK: TheFinancialServicesAuthority(OJK)OTC: OverthecounterPUAB: TheInterbankMoneyMarketPD: Probability of DefaultPDB: GrossDomesticProductPDN: NetOpenPositionPMK: MinisterofFinanceRegulationPLN: External debtPP: Finance CompanyRBB: Bank Business PlanROA: Return on assetsROE: Return on equitySBDK: Prime lending rateSBI: BankIndonesiaCertificateSBN: TradeableGovernmentSecuritiesSBT: NetweightedbalanceSKDU: Business SurveySKNBI: BankIndonesia-NationalClearingSystemSUN: GovernmentbondTOR: TurnoverratioTPT: TextilesandtextileproductsUMKM: Micro,SmallandMediumEnterprises

(MSMEs)

viii

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ix

rd

2014. The Financial Stability Review represents one form of transparency and accountability to the public in terms of

an expansionary period as well as provide space to absorb risk during an economic downturn.

the forms of spiralling private external debt, uncertainty surrounding the economic recovery in advanced countries as

amongst others.

In closing, this 23rd

of the Financial Stability Review.

Foreword

Jakarta, September 2014

Martowardo o

1

ec ve S ary

3

ec ve S ary

7

Chapter 1. Financial System Stability

Financial System Stability

Chapter 1

8


9


1.1 DEVELOPMENT OF RISKS ON GLOBAL AND

REGIONAL FINANCIAL MARKETS

Financial System StabilityChapter1


Advanced Countries

United States 1.80 (16.44) (41.98) (43.65) 22.04 6.05 - -

UK 9.29 (11.65) (61.51) (31.85) 8.50 (0.08) (11.07) (3.53)

Japan -33.65 (23.62) (53.28) (7.11) 10.86 45.86 2.21 (3.63)

Germany -27.95 (35.46) (38.05) (19.74) 23.54 38.46 (4.97) 0.83

East Asia

China 13.30 (11.47) (44.32) (3.54) 3.49 (3.20) 1.07 2.32

Hong Kong -0.10 (12.63) - - 11.48 (0.50) (0.08) (0.06)

Indonesia 15.17 (2.83) (22.37) (32.15) 1.24 13.02 18.70 (2.74)

South Korea -6.72 (11.79) (50.84) (19.38) 7.45 (0.03) (11.40) (4.14)

Malaysia 12.58 (2.02) (28.45) (22.48) 6.16 0.84 1.60 (2.53)

the Philippines - - (30.91) (23.03) 5.86 16.78 1.21 (1.67)

Singapore -1.20 (9.68) - - 3.34 2.79 (1.68) (1.66)

Thailand 2.20 (2.31) (14.30) (13.84) 2.33 5.67 4.47 (1.14)

Source: Bloomberg

(%)

(%)

Exchange RateStock IndexYield of 10-yearGovernment

Bonds (%)

5-year CDS (%)

y-o-y y-t-d y-o-y y-t-d y-o-y y-t-d y-o-y y-t-d


45

Dow Jones

40

35

30

25

20

15

10

5

0

Jan

-13

Feb

-13

Mar

-13

Ap

r-13

May

-13

Jun

-13

Jul-

13

Au

g-13

Sep

-13

Oct

-13

No

v-13

Dec

-13

Jan

-14

Feb

-14

Mar

-14

Ap

r-14

May

-14

Jun

-14

MSCI AsiaMSCI EuroMSCI World

160

150

140

130

120

110

100

90

80Jan-10 Jul-10 Jul-11Jan-11 Jul-12Jan-12 Jul-13Jan-13 Jul-14Jan-14

80

90

100

110

120

130Index

Composite Stock Index Performance(Rebased 1/1/2010=100)

EM Asia

World

G7

Asia P

Index


1.2 DEVELOPMENT OF RISKS IN THE DOMESTIC

ECONOMY

13.0

11.0

9.0

7.0

5.0

3.0

1.0

GDP Growth (%. yoy) Interest Rate Spread (%)

-1.0

Mar

-07

Sep

t-07

Mar

-08

Sep

t-08

Mar

-09

Sep

t-09

Mar

-10

Sep

t-10

Mar

-11

Sep

t-11

Mar

-12

Sep

t-12

Mar

-13

Mar

-14

Sep

t-13


20.0M

ar-0

7

Sep

-07

Mar

-08

Sep

-08

Mar

-09

Sep

-09

Mar

-10

Sep

-10

Mar

-11

Sep

-11

Mar

-12

Sep

-12

Mar

-13

Mar

-14

Sep

-13

15.0

10.0

5.0

-5.0

0.0

-10.0

Current Account (billions of US$)

-15.0

Capital and Financial Account (billions of US$)

Overall Balance (billions of US$)

300.0

millions US$

Private – Non bank

250.0

200.0

150.0

100.0

50.0

0.02009 2010 2011 2012 2013 June 2014

Private – Bank Government andCentral Bank


1.3. FINANCIAL SYSTEM STABILITY IN INDONESIA

nd

nd

3,0

2,5

1,5

0,5

2,0

1,0

2002

M01

2002

M05

2002

M09

2003

M01

2003

M05

2003

M09

2004

M01

2004

M05

2004

M09

2005

M01

2005

M05

2005

M09

2006

M01

2006

M05

2006

M09

2007

M01

2007

M05

2007

M09

2008

M01

2008

M05

2008

M09

2009

M01

2009

M05

2009

M09

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

1.2%

10.5%

2.6%6.4%

0.1%

0.5%

Banks

78.6%

Rural Banks

Insurers

Pension Funds

Finance Companies

Guarantors

Pawnbrokers


1.4 THE FINANCIAL CYCLE OF INDONESIA

0.25 0.02

0.02

0.01

0.01

(0.01)

(0.01)

(0.02)

(0.02)

2007Q2

0.20

0.15

0.10

0.05

-

(0.05)

19

92

Q1

19

93

Q4

19

94

Q3

19

95

Q2

19

96

Q1

19

96

Q4

19

97

Q3

19

98

Q2

19

99

Q1

19

99

Q4

20

00

Q3

20

01

Q2

20

02

Q1

20

02

Q4

20

03

Q3

20

04

Q2

20

05

Q1

20

05

Q4

20

06

Q3

20

07

Q2

20

08

Q1

20

08

Q4

20

09

Q3

20

10

Q2

20

11

Q1

20

11

Q4

20

12

Q3

20

13

Q2

20

14

Q1

20

14

Q4

20

15

Q3

(0.10)

(0.15)

(0.20)

(0.25)

1995Q1

2000Q2

2009Q4

2013Q3

2005Q2

1998Q2

1999Q2

(FBF/RHS)

2009Q3

(FBF/LHS) (TP)rough

(TP)


Peak to peak 24 41 15 36 19 39

Trough to trough 21 38 14 41 17 40

Cycle 22 40 15 39 18 39Financial Cycle/Business Cycle

BusinessCycle (PDB)

FinancialCycle

1.79 2.66 2.13

Cycle

Average Dura onFrequency Based Filter Turning Point Analysis AverageBusiness

Cycle (PDB)Financial

CycleBusiness

Cycle (PDB)Financial

Cycle


7

8

Frequency based lter

Turning point

analysis

1997Q3 -10 3Economic crisis and

2005Q3 -1 - Mini economic crisis2008Q4 -14 -6 Economic crisis

Crisis Descrip on

Peak (Quarterly)

1.5 SOURCES OF FINANCIAL IMBALANCES

1.5.1 Banking Procyclicality


40.0 8.0

7.0

5.0

4.0

3.0

2.0

1.0

6.0

35.0

30.0

25.0

20.0

15.0

10.0

5.0

0.0

Sep-

01M

ar-0

2Se

p-02

Credit Growth (%. yoy) GDP Growth (%. RHS)

Mar

-03

Sep-

03M

ar-0

4Se

p-04

Mar

-05

Sep-

05M

ar-0

6Se

p-06

Mar

-07

Sep-

07M

ar-0

8Se

p-08

Mar

-09

Sep-

09M

ar-1

0Se

p-10

Mar

-11

Sep-

11M

ar-1

2Se

p-12

Mar

-13

Sep-

13M

ar-1

4Se

p-14

1.5.2 Rising Property Prices

9

40.0 3.0

2.5

1.5

1.0

0.5

0.0

-0.5

-1.0

-1.5

-2.0

2.035.0

30.0

25.0

20.0

15.0

10.0

Sep-

01M

ar-0

2Se

p-02

Credit/GDP Gap (%. RHS) Credit/GDP (%) Trend

Mar

-03

Sep-

03M

ar-0

4Se

p-04

Mar

-05

Sep-

05M

ar-0

6Se

p-06

Mar

-07

Sep-

07M

ar-0

8Se

p-08

Mar

-09

Sep-

09M

ar-1

0Se

p-10

Mar

-11

Sep-

11M

ar-1

2Se

p-12

Mar

-13

Sep-

13M

ar-1

4Se

p-14

40%

Overheated Overheated

Overheated

Overheated

35

30

25

20

15

Sep-

01M

ar-0

2Se

p-02

Mar

-03

Sep-

03M

ar-0

4Se

p-04

Mar

-05

Sep-

05M

ar-0

6Se

p-06

Mar

-07

Sep-

07M

ar-0

8Se

p-08

Mar

-09

Sep-

09M

ar-1

0Se

p-10

Mar

-11

Sep-

11M

ar-1

2Se

p-12

Mar

-13

Sep-

13M

ar-1

4Se

p-14

Credit/GDP (%) Trend


180.00

170.00

160.00

150.00

140.00

130.00

120.00

110.00

100.00

2007 2008 2009 2010 2011 2012 2013 2014

240.00

220.00

200.00

180.00

160.00

140.00

120.00

2007 2008 2009 2010 2011 2012 2013 2014

Bandung Jabotabek-Banten

220.00

200.00

180.00

160.00

140.00

120.00

100.00

2007 2008 2009 2010 2011 2012 2013 2014

Palembang Bandar Lampung

240.00

220.00

200.00

180.00

160.00

140.00

120.00

100.00

2007 2008 2009 2010 2011 2012 2013 2014


0.00

50.00

100.00

150.00

200.00

250.00

300.00

350.00

400.00

2007 2008 2009 2010 2011 2012 2013 2014

200

180

SUMATERA

Medan

Padang

Palembang

Lampung

160

140

120

100

80

60

40

20

2007 2008 2009 2010 2011 2012 2013 2014

0

250

200

150

100

50

02007 2008 2009 2010 2011 2012 2013 2014

JAWA-BALI

Bandung

Semarang

Surabaya

Jabotabek

Yogyakarta

Denpasar

250

200

150

100

50

02007 2008 2009 2010 2011 2012 2013 2014

KALIMANTAN

Banjarmasin


180

160

140

120

100

80

60

40

20

02007 2008 2009 2010 2011 2012 2013 2014

Menado Makasar

2007 2008 2009 2010 2011 2012 2013 2014

1.20

1.10

1.00

0.90

0.80

0.70

0.60

Tw I Tw II Tw IIITw IV Tw I Tw II Tw IIITw IV Tw I Tw II Tw IIITw IV Tw I Tw II Tw IIITw IV Tw I Tw II Tw IIITw IV Tw I Tw II Tw IIITw IV Tw I Tw II Tw IIITw IV Tw I Tw II

Jabodetabek


1.5.3 Growing Non-Bank Private External Debt

180

billion USD billion USD

25

20

15

10

5

0

Government + Central Bankand Private

Government + Central Bank

Private

Private

160

140

120

100

80

60

40

20

0

Government + Central Bank

Government

Central Bank (RHS)

Non Bank

Bank (RHS)

Dec’02

Dec’06

Dec’08

Dec’10

Dec’12

Dec’13

Jun’14

Dec’04

Dec’06

Dec’08

Dec’10

Dec’12

Mar

’14

Dec’03

Dec’05

Dec’07

Dec’09

Dec’11

Dec’13

Jun’14

2007

Jabodetabek

Bandung

Tw I

Tw III

2008

Tw I

Tw III

2009

Tw I

Tw III

2010

Tw I

Tw III

2011

Tw I

Tw III

2012

Tw I

Tw III

Tw I

Tw III

Tw I

1.20

1.10

1.00

0.90

0.80

0.70

0.60

2013 2014

Surabaya

Yogyakarta

Semarang

Denpasar

2007

Bandar Lampung

Palembang

Tw I

Tw III

2008

Tw I

Tw III

2009

Tw I

Tw III

2010

Tw I

Tw III

2011

Tw I

Tw III

2012

Tw I

Tw III

Tw I

Tw III

Tw I

1.20

1.05

1.00

0.95

0.85

0.90

0.80

0.70

0.75

0.60

0.65

2013 2014

Padang

Medan

2007

Banjarmasin

Tw I

Tw III

2008

Tw I

Tw III

2009

Tw I

Tw III

2010

Tw I

Tw III

2011

Tw I

Tw III

2012

Tw I

Tw III

Tw I

Tw III

Tw I

1.20

1.00

0.80

0.60

0.40

0.20

-

2013 2014

2007

Makassar Menado

Tw I

Tw III

2008

Tw I

Tw III

2009

Tw I

Tw III

2010

Tw I

Tw III

2011

Tw I

Tw III

2012

Tw I

Tw III

Tw I

Tw III

Tw I

1.30

1.20

1.10

1.00

0.90

0.80

0.70

0.60

2013 2014


Government and Central Bank

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Dec

09

Dec

10

Dec

11

Dec

12

Dec

13

Jan

14

Feb1

4

Mar

14

Apr

14

May

14

Jun

14

Stocks16%

Bonds10%

ExternalDebt29%

Credit45%

LOANAGREEMENT

73.4%

BONDS19.9%

OTHERS0.4%

PAYABLES6.4%

Short Term20%

Long Term80%

24


Source: External Debt Statistics of Indonesia, Bank Indonesia

*) June 2014

Source: Bank Indonesia

Graph 1.19.External Debt by Economic Sector

The Asian Financial Crisis in 1997/1998 confirmed

that an increase in private external debt in the period

before a crisis is a contributor to inflationary pressures,

which exacerbate financial instability and undermine the

economy through increased leverage. An assessment of

risk mitigation using a sample of 2,164 private corporate

respondents holding external debt for the period from

2008-2013 revealed that exchange rate depreciation risk

impacts corporations with short-term external debt from

non-affiliates12 that are domestic oriented13 more than

export-oriented corporations with long-term external debt

from affiliates14. The upward tends of the leverage ratio

and the debt-to-equity ratio (DER) of affiliated corporations

indicate potential exchange rate risk on private external

debt.

The results of stress testing corporate resilience to

exchange rate depreciation revealed that six of the 53

public listed corporations with external debt, as part of

the observation sample, have the potential to become

insolvent if the rupiah slides to Rp16,000 per US dollar.

12) Non-affiliate: corporations with external debt exceeding 50% from non-affiliated parties.

13) Domestic oriented: corporations with a position of net imports for the past two years or those that do not engage in import-export activity.

14) Affiliate: Corporations with external debt exceeding 50% from the parent company or affiliated parties.

Meanwhile, simulating the impact of exchange rate

depreciation on bank credit through integrated stress tests

regarding the probability of default of 271 corporations

with external debt and using several scenarios (refer to

the Box, Corporate Risk to External Debt and Share Price

Valuation) showed that the impact of rupiah depreciation

was relatively minimal.

1.6 SOURCES OF VULNERABILITY

1.6.1 External Sources of Vulnerability

Global Economic Contagion

An increasingly integrated global economy has led

to greater contagion between economies, implying that

the economy of one country will influence that of another

country. Such contagion can affect the domestic economy,

including financial system stability, through the trade and

financial channels.

Uncertainty surrounding the normalisation policy

of the U.S. Federal Reserves is one source of vulnerability

in the global economy, including Indonesia. This risk is

associated with the policy response of the Federal Reserves

in terms of normalising its policy stance in line with

indications of improving U.S. economic conditions. The

Federal Reserves’ policy of Quantitative Easing (QE) III will

120

Billions of USD

100

80

60

40

20

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014*-

Short Term Long Term

- 50 100 150

44.6%

10.8%

9.5%

7.8%

6.7%

5.9%

4.3%

3.9%

3.4%

3.1%

billions of USD

Economic Sector

Trade. Hotels And Restaurants (THR) Sector

Agriculture. Livestock. Forestry and Fisheries

Construction

Transportation and Communication

Other Sectors

Services

Utilities (Electricity. Gas and Sanitary Water)

Mining and Quarrying

Manufacturing Industry

Financial. Leasing and Corporate Services

25


14.0

12.0

10.0

8.0

6.0

4.0

2.0

-

INDI IND0 CHN KOR TUR

Q1 Q2

2010

Q3 Q4 Q1 Q2

2011

Q3 Q4 Q1 Q2

2012

Q3 Q4 Q1 Q2

2013

Q3 Q4 Q1 Q2

2014

Q3 Q4

2014 2015 2016

PercentAppropriate pace of policy firming

Target federal funds rate at year-end6

5

4

3

2

1

0

Longer Run

be discontinued by the Federal Open Market Committee in

October 2014 and the federal funds rate (FFR) is expected

to increase thereafter in the second or third quarter of

2015 in line with the ongoing U.S. economic recovery. In

addition, the median survey of FOMC members revealed

that the FFR will increase from 1% at the end of 2015

(FOMC March 2014) to 1-1.25% (FOMC June 2014). Such

conditions were further confirmed by the slightly hawkish

statement issued by the chairman of the Federal Reserves

at the FOMC on 30-31st July 2014.

In addition to uncertainty surrounding the

normalisation policy of the Federal Reserves, the economy

will also confront risk linked to vulnerabilities in emerging

market countries, an economic downswing in China

as well as global growth spillover and spillback. Risk in

Indonesia stemming from vulnerabilities in emerging

market countries is moderate compared to peer countries.

Improving conditions are the result of lower inflation,

burgeoning foreign exchange reserves and a relatively

strong exchange rate. Risk stemming from vulnerabilities

in emerging market countries will also be mitigated

as concerns are allayed regarding the banking crisis in

Portugal. Meanwhile, the impact of Argentina defaulting

will be limited as the episode is seen as a temporary

interruption rather than a permanent default. On the

other hand, risk associated with the economic rebalancing

process in China requires attention due to the large role

China plays as a trade partner of Indonesia. Furthermore,

the economic downturn in China also has an impact on

commodity prices, growth (investment) and the financial

system (shadow banking). Meanwhile, there is also the risk

of global growth spillover and spillback between advanced

countries and emerging market countries through four

channels, namely the trade channel, commodity prices,

the global financial system and the neighbourhood effect.

Although external vulnerabilities require vigilance,

the risk premium improved as evidenced by a decline in

credit default swaps (CDS). Meanwhile, persistent investor

interest was maintained after a number of authorities

in advanced countries instituted economic stabilisation

policy. China relaxed taxes for small and medium

enterprises (SME) and is accelerating infrastructure

spending during the second half of 2014. The Bank of

Japan projects a rebound in terms of GDP commencing in

the second semester of 2014. Furthermore, the European

Central Bank (ECB) vowed to provide cheap loans for banks

to extend to small and medium enterprises and implement

the ECB’s version of quantitative easing if required. Market

Source: FOMC

Graph 1.20.Fed Fund Survey: FOMC June 2014


Graph 1.21.Growth in Emerging Market Countries


100

90

80

70

60

50

40

30

20

10

0

Jan-

13

Feb-

13

Mar

-13

Apr-

13

May

-13

Jun-

13

Feb-

14

Mar

-14

Apr-

14

May

-14

Jun-

14

Jul-1

3

Aug-

13

Sep-

13

Oct

-13

Nov

-13

Dec

-13

Jan-

14

USA UK GER JAP

i o n al

300

250

200

150

100

50

INDO

Jan-

13

Feb-

13

Mar

-13

Apr-

13

May

-13

Jun-

13

Feb-

14

Mar

-14

Apr-

14

May

-14

Jun-

14

Jul-1

3

Aug-

13

Sep-

13

Oct

-13

Nov

-13

Dec

-13

Jan-

14

THAI KOR PHI


-150

-100

-50

0

50

100

150

200

250

20

05

Q1

20

05

Q2

20

05

Q3

20

05

Q4

20

06

Q1

20

06

Q2

20

06

Q3

20

06

Q4

20

07

Q1

20

07

Q2

20

07

Q3

20

07

Q4

20

08

Q1

20

08

Q2

20

08

Q3

20

08

Q4

20

09

Q1

20

09

Q2

20

09

Q3

20

09

Q4

20

10

Q1

20

10

Q2

20

10

Q3

20

10

Q4

20

11

Q1

20

11

Q2

20

11

Q3

20

11

Q4

20

12

Q1

20

12

Q2

20

12

Q3

20

12

Q4

20

13

Q1

20

13

Q2

20

13

Q3

20

13

Q4

Billion USD2

0000

8Q

1

20

08

QQ22

20

08

QQ33

20

08

Q4

20

12

Q4

20

13

Q1

20

13

Q2

20

13

Q3

GlobalFinancialCrisis

TaperingIssue

0

100

200

300

400

500

600

700

800

2005

Q1

2005

Q2

2005

Q3

2005

Q4

2006

Q1

2006

Q2

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

2010

Q1

2010

Q2

2010

Q3

2010

Q4

2011

Q1

2011

Q2

2011

Q3

2011

Q4

2012

Q1

2012

Q2

2012

Q3

2012

Q4

2013

Q1

2013

Q2

2013

Q3

2013

Q4

2014

Q1

2014

Q2

2014

Q3

BrazilSouth Africa

TurkeyIndonesia

MexicoSouth Korea

3 4 1 2

GlobalFinancialCrisis

TaperingIssue

2 3 4 1

TaperingIssue


Period (T=Quarter) Country Sample

Prior to GlobalFinancial Crisis

T1 2007 –T2 2008 India, Hong Kong, South Korea Brazil, Russia, India,Hong Kong,South Africa,Turkey, Indonesia,Mexico andSouth Korea

Prior toTapering Issue

T1 2012 – T1 2013 India, South Korea, Turkey

T3 2013 – T4 2013 Indonesia, Hong Kong, Russia

50Trillions of Rp Shares

40

30

2010

2011

2012

2013

2014

20

10

0

-10

-20

2010

2011

2012

2013

2014

110

90

70

50

30

10

-10

Trillions of Rp


Billions of USD

20

15

10

5

0

2010 2011 2012 2013-5

up to Q2 2014

Direct Investment

Other Investment

4,000

2,000

0

-2,000

-4,000

-6,000

-8,000

-10,000

-12,000

Current Account (million of US$) (LHS)

12,500

12,000

11,500

11,000

10,500

10,000

9,500

9,000

8,500

8,000

2010

Q1

2010

Q2

2010

Q3

2010

Q4

2011

Q1

2011

Q2

2011

Q3

2011

Q4

2012

Q1

2012

Q2

2012

Q3

2012

Q4

2013

Q1

2013

Q2

2014

Q1

2014

Q2

2013

Q3

2013

Q4

Exchange Rate (Rp/$) (RHS)


1.6.2 Internal Sources of Vulnerability

130 rebased 1/1/2013

125

120

115

110

105

100

95

90

85

80

Indonesia

Jan-

13

Feb-

13

Mar

-13

Apr

-13

May

-13

Jun-

13

Feb-

14

Mar

-14

Apr

-14

May

-14

Jun-

14

Jul-1

3

Aug

-13

Sep-

13

Oct

-13

Nov

-13

Dec

-13

Jan-

14

Thailand South Korea the Philippines

Japan13.7%Others

44.4%

China15.0%

US9.0%

Europe8.8%

Singa-pore


1.6.3 Domes c Risks that could Undermine Financial

System Intermedia on

8

7

6

5

4

3

2

1

02009

Right Issue (RHS) Real GDPIPO (RHS)

Trillions of Rp

2010 2011 2012 2013 2014

90

80

70

60

50

40

30

20

10

0

9

Bonds (RHS) BI Rate

8

7

6

5

4

3

2

1

02009 2010 2011 2012 2013 2014

70

60

50

4

30

20

10

0

28.0 92.0

90.0

88.0

86.0

84.0

82.0

80.0

78.0

26.0

24.0

22.0

20.0

18.0

16.0

14.0Ja

n-12

Feb-

12M

ar-1

2A

pr-1

2M

ay-1

2Ju

n-12

Jul-1

2A

ug-1

2Se

p-12

Oct

-12

Nov

-12

Dec

-12

Jan-

13Fe

b-13

Mar

-13

Apr

-13

May

-13

Jun-

13Ju

l-13

Aug

-13

Sep-

13O

ct-1

3N

ov-1

3D

ec-1

3Ja

n-14

Feb-

14M

ar-1

4A

pr-1

4M

ay-1

4Ju

n-14

12.0

10.0

Credit Growth (%, yoy)Deposit Growth (%, yoy) LDR (%, RHS)


Box 1.1 Financial Cycle of Indonesia

= 1 [ + (1 )(1 )]=1


i. The nancial cycle to business cycle ra o.

IHSG

Credit/GDP IHSG IHPR IHSG IHPR IHPR


89% 84% 25% 80% 38% 36%Credit-

Credit/GDP-IHSG

Turning point analysis

59% 22% 17% 26% 55% 61%Credit-

Credit/GDP

Narrow Credit Narrow Credit/GDP Common Cycle

Broad Credit/GDP

Credit/GDP IHSG IHSG


77% 51% 52%Credit-

Credit/GDP

Turning point analysis

72% 2% 31%Credit-

Credit/GDP

Broad Credit Common Cycle

2007Q2

0.10

0.12

0.08

0.06

0.04

0.02

-

(0.02)

(0.04)

(0.06)

(0.08)

(0.10)

1996Q4

2002Q2

2007Q3

0.02

0.02

0.01

0.01

(0.01)

(0.01)

(0.02)

(0.02)

19

93

Q1

19

93

Q4

19

94

Q3

19

95

Q2

19

96

Q1

19

96

Q4

19

97

Q3

19

98

Q2

19

99

Q1

19

99

Q4

20

00

Q3

20

01

Q2

20

02

Q1

20

02

Q4

20

03

Q3

20

04

Q2

20

05

Q1

20

05

Q4

20

06

Q3

20

07

Q2

20

08

Q1

20

08

Q4

20

09

Q3

20

10

Q2

20

11

Q1

20

11

Q4

20

12

Q3

20

13

Q2

20

14

Q1

1998Q2

1999Q2 2009Q3

2009Q3

Financial Cycle(FBF/RHS)

Business Cycle(FBF/LHS)

FC Peak(TP)

FC Trough(TP)

Crisis

0.10 0.02

0.02

0.01

0.01

(0.01)

(0.01)

(0.02)

(0.02)

2007Q2

0.08

0.06

0.04

0.02

-

(0.02)

19

92

Q1

19

93

Q4

19

94

Q3

19

95

Q2

19

96

Q1

19

96

Q4

19

97

Q3

19

98

Q2

19

99

Q1

19

99

Q4

20

00

Q3

20

01

Q2

20

02

Q1

20

02

Q4

20

03

Q3

20

04

Q2

20

05

Q1

20

05

Q4

20

06

Q3

20

07

Q2

20

08

Q1

20

08

Q4

20

09

Q3

20

10

Q2

20

11

Q1

20

11

Q4

20

12

Q3

20

13

Q2

20

14

Q1

20

14

Q4

20

15

Q3

(0.04)

(0.06)

(0.08)

(0.10)

1995Q1

2000Q2

2009Q3

2005Q2

1998Q2

1999Q2 2009Q3

Financial Cycle(FBF/RHS)

Business Cycle(FBF/LHS)

FC Peak(TP)

FC Trough(TP)

Crisis


ii. Financial cycle and nancial crisis/stress in the

nancial system.

iii. Financial cycle amplitude

Peak to peak 19 38 40Trough to trough 17 39 35Cycle 18 39 37Financial cycle/Business cycle

2.10 2.04

Average Dura on (in quarters)

Cycle BusinessCycle (GDP)

Financial Cycle(Narrow Credit)

Financial Cycle(Broad Credit)

FBF TP FBF TP

1997Q3 -9 3 -3 3 Economic Crisis and Financial Crisis

2005Q3 -1 - - - Mini Economic Crisis2008Q4 -14 -6 -5 -6 Economic Crisis

FBF = frequency-based ter , TP = turning-point

Crisis/Stress

Narrow CreditFinancial Cycle

Broad CreditFinancial Cycle Descrip on


Box 1.2 Macropruden al and Monetary Policy Nexus

13.0 12000

11000

10000

9000

8000

12.0

11.0

10.0

9.0

8.0

7.0

6.0

5.0

4.03.0

GDP Growth (%, yoy) Exchange Rate ($/Rp, RHS)BI Rate (%)

Mar

-07

Sep-

07

Mar

-08

Sep-

08

Mar

-09

Sep-

09

Mar

-10

Sep-

10

Mar

-11

Sep-

11

Mar

-12

Mar

-13

Sep-

13

Mar

-14

Sep-

12

3.0

4.0

Exchange Rate ($/Rp. RHS)

Mar

-07

Sep

-07

Mar

-08

Sep

-08

Mar

-09

Sep

-09

Mar

-10

Sep

-10

Mar

-11

Sep

-11

Mar

-12

Mar

-13

Sep

-13

Mar

-14

Sep

-12

2.0

1.0

0.0

-1.0

-2.0

-3.0

-4.0

-5.0

12000

11000

10000

9000

8000


40.0 3.0

2.5

1.5

1.0

0.5

0.0

-0.5

-1.0

-1.5

-2.0

2.035.0

30.0

25.0

20.0

15.0

10.0

Sep-

01M

ar-0

2Se

p-02

Credit/GDP Gap (%, RHS) Credit/GDP (%) Trend

Mar

-03

Sep-

03M

ar-0

4Se

p-04

Mar

-05

Sep-

05M

ar-0

6Se

p-06

Mar

-07

Sep-

07M

ar-0

8Se

p-08

Mar

-09

Sep-

09M

ar-1

0Se

p-10

Mar

-11

Sep-

11M

ar-1

2Se

p-12

Mar

-13

Sep-

13M

ar-1

4Se

p-14

218

6

4

2

0

-2

-4

-6

-8

16

11

6

Deposit Growth Gap (%, RHS) Deposit Growth (%, yoy) Tren

1

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


Box 1.3 The Importance of Macropruden al Regula on and Supervision


st

41

Chapter 2. Financial Markets

Financial Markets

Chapter 2

42



43


2.1 FINANCIAL MARKET RISKS

Domestic economic growth, which outpaced the

global economy, garnered investor confidence and

catalysed domestic financial market activity, coupled with

less intense financial market risks during the first semester

of 2014. Nonetheless, several potential risks continued to

demand vigilance in light of macroeconomic fundamentals

vulnerable to external imbalances. Furthermore,

uncertainty surrounding the global economy and domestic

political conditions affected near-term financial market

performance. Potential financial market risks emerged in

the guise of foreign capital flows as well as risks on the

money market, foreign exchange market, bond market,

stock market and mutual fund market.

National economic growth, which outperformed the global economy, helped stimulate domestic

financial market activity throughout the first semester of 2014. Such conditions were mirrored by a

maintained influx of foreign capital, greater transaction volume on the interbank money market (PUAB),

escalating interbank repurchase agreements (repo) and foreign exchange transactions, an increase in

outstanding tradeable government securities (SBN) and corporate bonds, gains on the IDX Composite

index as well as growth in managed investment funds. Furthermore, surging financial market activity

was accompanied by relatively well-mitigated risk, evidenced by declines in the interbank rate and its

volatility, a narrower spread between non-deliverable forwards and one-month onshore forwards,

lower SBN yields and volatility, less volatility on the stock market, an increase in net asset value

(NAV) as well as less volatility (beta coefficient) of mutual funds. Nevertheless, financial markets in

Indonesia remained vulnerable to potential risk stemming from external imbalances, primarily linked

to a possible sudden capital reversal.

2.1.1 Foreign Capital Flows

Growing investor confidence in the domestic

economy and financial markets was indicated by an

inflow of foreign purchases of domestic financial market

instruments, including Bank Indonesia Certificates (SBI),

tradable government securities (SBN), corporate bonds

and shares. On the SBI market, foreign holdings increased

from the beginning of the reporting semester to reach

Rp8.57 trillion in May 2014 before subsequently returning

to record an outflow of Rp3.87 trillion in June. In general,

however, foreign SBI holdings registered a net inflow

of Rp10.96 trillion. On the SBN market, foreign inflows

peaked at Rp20.15 trillion in May 2014, with a total value

for the reporting semester of Rp79.95 trillion. Concerning

the stock market, foreign inflows peaked in April 2014 at

Rp11.48 trillion, with a total inflow value of Rp48.07 trillion

Chapter2

Financial Markets

44


Source: Bloomberg, Bank Indonesia

Graph 2.1Non-Resident Flows: Shares, SBN & SBI


Graph 2.2Rupiah Interbank Money Market Performance


Graph 2.3Overnight Rupiah Interbank Rate

during the reporting semester. Overall, total foreign inflow

to domestic financial markets amounted to Rp138.98

trillion during the reporting semester, up 4.4 times that

of the previous semester.

during the reporting semester was the result of a large

requirement for short-term funds from the banking sector

in the run up to the holiday season and Eid-ul-Fitr. By bank

group (BUKU1) and transactional behaviour, BUKU 4 banks

tended to lend and BUKU 2 and 3 banks tended to borrow.

2.1.2 Money Market

The money market encompasses uncollateralised

markets (the interbank money market) and collateralised

markets (the repo market). The performance and risks

associated with each respective market can be summarised

as follows:

2.1.2.1 The Interbank Money Market (PUAB)

During the reporting semester, risk on the rupiah

interbank money market tended to ease, demonstrable

by the average daily overnight interbank rate as well as

the average daily rate on all tenors in the range of 5.85%

- 5.90% and 6.09% - 6.19% respectively. A narrower max-

min spread along with less volatility also indicated easing

risk. In addition, average daily overnight rupiah interbank

transaction volume and the average daily rate on all tenors

increased correspondingly by Rp1.23 trillion and Rp1.69

trillion on the preceding semester to Rp13.30 trillion and

Rp22.27 trillion at the end of the first semester of 2014.

The increase in rupiah interbank transaction volume

-60

-40

-20

0

20

40

60

80

100

120

140

2009

2010

2011

2012

2013

Jan-

14

Feb-

14

Mar

-14

Apr-

14

Mei

-14

Jun-

14

Trillion of Rp

Shares Tradeable Government Securities Bank Indonesia Certificates

7.0 35

30

25

20

15

10

5

--

6.0

5.0

4.0

3.0

2.0

1.0

2010

/Jan

2010

/Apr

2010

/Jul

2010

/Okt

2011

/Jan

2011

/Apr

2011

/Jul

2011

/Okt

2012

/Jan

2012

/Apr

2012

/Jul

2012

/Okt

2010

/Jan

2010

/Apr

2010

/Jul

2010

/Okt

2010

/Jan

2010

/Apr

Percent Trillion of Rp

Average Daily non-overnight volumeWeighted average overnight rate

Average Daily overnight volumeWeighted average of all rates

Ags - 08

Jan - 09

Jun - 09

Nov - 09

Apr - 10

Sep - 10

Feb - 11

Jul - 11

Dec - 11

Mar - 12

Oct - 12

Mar - 13

Ags - 13

Jan - 14

Jun - 14

512

10

8

6

4

2

4

3

2

1

0

Max-min Spread (RHS) Weighted average rate (%)Highest Lending Rate (%)

1) BUKU is grouping of commercial banks by their business activities according to their licenses. BUKU 4 banks are licensed to operate the most activities within the banking business, while BUKU 1 banks are licensed to operate the least activites.

45


foreign exchange interbank money market volume

increased moderately by US$3.3 million to US$492.22

million. The large decline in average daily transaction

volume on the foreign exchange interbank money market,

accompanied by an increase on the rupiah interbank

money market, demonstrated that the banking sector

favoured the rupiah interbank money market to manage

its short-term funds. By bank group and transactional

behaviour, BUKU 3 and 4 banks were lenders, while BUKU

2 banks were borrowers.


Graph 2.4Rupiah Interbank Rate Volatility


Graph 2.5Rupiah Interbank Transactional Behaviour


Graph 2.6Foreign Exchange Interbank Money Market


Graph 2.7Overnight Foreign Exchange Interbank Rate

Congruent with less risk on the rupiah interbank

money market, risk on the foreign exchange interbank

money market also eased, reflected by the average daily

overnight foreign exchange interbank rate and the average

daily rate on all tenors in the range of 0.12% - 0.15% and

0.14% - 0.18% respectively. Narrower spread between

the max-min overnight interbank rate, coupled with less

volatility, was also evidence of less risk. Average daily

foreign exchange interbank money market transaction

volume of all tenors dropped US$77.40 million on the

preceding semester to US$667.43 million at the end of the

first semester of 2014. Meanwhile, average daily overnight

Jan-

13Fe

b-13

Mar

-13

Apr-1

3

May

-13

Jun-

13Ju

l-13

Aug-

13

Sep-

13

Oct

-13

Nov

-13

Dec-

13

Jan-

14Fe

b-14

Mar

-14

Apr-1

4

May

-14

Jun-

14

90% 8.0

7.5

7.0

6.5

6.0

5.5

5.0

4.5

4.0

80%

70%

60%

50%

40%

30%

20%

10%

0%

BI Rate (RHS)

Lending Facility (RHS)

O/N Interbank Rate (RHS)O/N Rp Interbank VolatilityDeposit Facility (RHS)

2012/Jan

2012/Mar

2012/May

2012/Jul

2012/Sep

2012/Nov

2013/Jan

2013/Mar

2013/May

2013/Jul

2013/Sep

2013/Nov

2014/Jan

2014/Mar

2014/May

150

100

50

0

-50

-100

-150

Buku 4

Trillions of Rp

Buku 3 Buku 2 Buku 1

1,6000.35

Average Daily Non-O/N Volume

0.30

0.25

0.20

0.15

0.10

0.05

-

1,400

1,200

1,000

800

600

400

200

-

Millions of USDPercent

naJ/0102

rpA/0102

l uJ/0102

tgA/0102naJ/1102

r pA/1102

l uJ/1102

tgA/1102naJ/2102

r pA/2102

l uJ/2102

tgA/2102naJ/3102

r pA/3102

l uJ/3102

tgA/3102naJ/4102

r pA/4102

Weighted Average O/N RateAverage Daily O/N VolumeWeighted Average of All Rates

Max-min Spread (RHS) Weighted average rate (%)

0.50 1.8

1.6

1.4

1.2

1

0.8

0.6

0.4

0.2

0

0.45

0.40

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00Nov - 08Feb - 09M

ay - 09Ags- 09Nov - 09Feb - 10M

ay - 10Ags- 10Nov - 10Feb - 11M

ay - 11Ags- 11Nov - 11Feb - 12M

ay - 12Ags- 12Nov - 12Feb - 13M

ay - 13

Feb - 14M

ay - 14

Ags- 13Nov - 13

Highest Lending Rate (%)

46


2.1.2.2 Bank Repo Market

Repo market activityincludes repurchase agreements

between banks and those with Bank Indonesia, namely

through the lending facility. During the reporting semester,

interbank repo market risk tended to subside, as indicated

by a narrower average daily repo rate range for all tenors

from 5.59% - 7.82% in the previous semester to 6.82%

- 7.25%. Additionally, average daily transaction volume

for all tenors increased Rp135 billion on the preceding

semester to Rp1.12 trillion at the end of first semester

of 2014. The increase in repo transaction volume during

the reporting semester commenced in the wake of the


Graph 2.8.Foreign Exchange Interbank Rate Volatility


Graph 2.9.Foreign Exchange Interbank Transactional Behaviour


Graph 2.10.Interbank Repo Transactions


Graph 2.11.Lending Facility Transactions

Mini Master Repo Agreement (MRA) signed by banks in

December 2013, which aims to provide additional sources

of funds for banks other than third-party deposits.

Repo activity at Bank Indonesia declined during the

reporting semester. Total repo transaction volume at Bank

Indonesia amounted to Rp0.14 trillion in the reporting

period, which is down on the Rp5.5 trillion reported in

the preceding semester. The increase in interbank repo

transactions, coupled with a decline in repo transactions

at Bank Indonesia, illustrates a relatively liquid financial

market and confirms the effectiveness of the Mini MRA

in terms of financial market deepening.

O/N Forex Interbank Rate (RHS) Federal Funds rateO/N Forex Interbank Volatility

Jan -

13

Feb -

13M

ar - 1

3

Apr -

13M

ay - 1

3

Jun -

13

Jan -

14

Feb -

14M

ar - 1

4

Apr -

14M

ay - 1

4

Jun -

14

Jul -

13

Aug -

13

Sep -

13Oc

t - 13

Nov -

13

Dec -

13

400% 0.25

0.20

0.15

0.10

0.05

0.00

350%

300%

250%

200%

150%

100%

50%

0%

6Billions of USD

4

2

0

-2

-4

-6

2012

/Jan

2012

/Mar

2012

/May

2012

/Jul

2012

/Sep

2012

/Nov

2013

/Jan

2013

/Mar

2013

/May

2014

/Jan

2014

/Mar

2014

/May

2013

/Jul

2013

/Sep

2013

/Nov

Buku 4 Buku 3 Buku 2 Buku 1

35Trillions of Rp Percent

9

10

8

7

6

5

4

3

2

1

0

30

25

20

15

10

5

0

2 4 7 9 11 1 3 5 7 9 11 1 3 5 8 1012 3 5 7 9 11 1 3 5 7 9 11 1 3 5

2009 2010 2011 2012 2013 2014

Repo Volume Repo Rate (RHS)

3.5Trillions of Rp Percent

9.0

8.5

8.0

7.5

7.0

6.5

6.0

5.5

5.0

4.5

4.0

3.0

2.5

2.0

1.5

1.0

0.5

0.0

1 4 7 10 1 4 7 10 1 4 7 10 1 4 7 10 1 4 10 1 4

2009 2010 2011 2012 2013 2014

Total Volume LF Rate (RHS)

47


3.1.3 Foreign Exchange Market

Risk also eased on the foreign exchange market,

amongst others reflected by a narrower spread between

non-deliverable forwards and one-month onshore

forwards. Furthermore, adequate liquidity on the foreign

exchange market also signalled less risk. Total foreign

exchange transaction volume increased from US$262.03

billion in the second semester of 2013 to USD322.17 in

the reporting period.

In terms of composition, spot transactions

dominated the domestic foreign exchange market with a

volume accounting for 67.31% of total foreign exchange

transactions. Meanwhile, the portion of forward and swap

transactions amounted to 5.45% and 27.24% respectively.

The relatively small share of forward and swap transactions

in comparison to spot transactions is an indicator of a

shallow domestic foreign exchange market that requires

further financial deepening efforts.

Source: Bank Indonesia, Bloomberg, processed

Graph 2.12.Foreign Exchange Market Risk Premium

Source: Bank Indonesia, Bloomberg, processed

Graph 2.13.Swap Transaction Volume


Graph 2.14.Domestic Foreign Exchange Market Volume


Graph 2.15.Foreign Exchange Transaction Volume Trend

800Point Rp

13,000

12,500

12,000

11,500

11,000

10,500

10,000

9,500

9,000

8,500

8,000

600

400

200

-200

-400

-600

-800

Jan-

12

Mar

-12

May

-12

Jul-1

2

Sep-

12

Nov

-12

Jan-

13

Mar

-13

May

-13

Jan-

14

Mar

-14

May

-14

Jul-1

3

Sep-

13

Nop

-13

0

Spread NDF-FWD 1B RRH 10D Spread NDF 1B (RHS)

8.0%

7.0%120

100

80

60

40

20

Jun-12 Dec-12 Dec-13Jun-13 Jun-14

6.0%

5.0%

4.0%

3.0%

2.0%

1.0%

0.0%

Total Vol. Semesteran (RHS) Premi Swap Broker O/N

Billions of USD

Premi Swap Broker 1B Premi Swap Broker 3BPremi Swap Broker 6B

70

60

50

40

30

20

10

OPTION

0

2010

/Jan

2010

/Mar

2010

/May

2010

/Jul

2010

/Sep

2010

/Nov

2011

/Jan

2011

/Mar

2011

/May

2011

/Jul

2011

/Sep

2011

/Nov

2012

/Jan

2012

/Mar

2012

/May

2012

/Jul

2012

/Sep

2012

/Nov

2013

/Jan

2013

/Mar

2013

/May

2013

/Jul

2013

/Sep

2013

/Nov

2014

/Jan

2014

/Mar

2014

/May

Billions of USD

FORWARD SWAP SPOT

65

60

55

50

45

40

35

301 2 3 4 5 6 7 8 9 10 11 12

Billions of USD

2011 2012 2013 2014

48


2.1.4 Bond Market

On the bond market, economic stimulus packages

and low interest rates in a number of advanced countries

were important factors leading to an influx of foreign

capital into government securities (SBN), increasing from

Rp44.46 trillion in the second semester of 2013 to Rp79.95

trillion in the reporting semester. Foreign purchases of SBN

occurred on the secondary market as well as issuances on

the primary market by the government. Accordingly, the

portion of foreign SBN holdings increased from 32.54% on

the preceding semester to 35.66%.


Graph 2.16.Foreign Net Flow to SBN and IDMA Index

Source: CEIC

Graph 2.17.SBN Holdings

The surge in foreign inflow to SBN prompted higher

SBN prices, with the IDMA index rallying to 96.65 points

from 95.46 points in the previous semester. Meanwhile,

SBN market risk eased as yield and volatility decreased.

SBN yield for tenors of 10 years dropped 28 bps to 8.09%,

accompanied by a 46 bps decline in volatility to 2.18%,

one of the lowest in Asia.

Source: Bloomberg, processed


Table 2.1.10-Year SBN Yield and Regional Yields

Table 2.2.10-Year SBN Volatility and Regional Volatility (%)

INDO INDI THAI MAL PHILJun-13 7.06 7.69 3.63 3.72 4.07Jul-13 8.52 8.86 4.13 4.04 3.18

Aug-13 8.32 8.97 3.87 3.76 3.61Sep-13 5.93 8.31 3.50 3.55 4.65Oct-13 5.65 8.33 3.30 3.43 4.67

Nov-13 8.59 9.09 3.91 4.30 3.35Dec-13 8.37 9.17 3.80 4.20 3.42Jan-14 8.81 8.86 3.78 4.22 4.24Feb-14 8.34 9.06 3.54 4.10 4.38Mar-14 7.99 9.11 3.51 4.01 3.85Apr-14 7.86 9.02 3.42 3.95 3.98

May-14 7.95 8.77 3.57 3.96 3.61Jun-14 8.09 8.58 3.57 3.93 3.78

INDO IND THAI MAL PHIJun-13 8.69 5.36 9.56 8.19 16.13 Jul-13 17.47 26.20 3.16 7.53 8.99

Aug-13 11.78 10.63 7.24 2.78 1.77 Sep-13 12.97 5.38 8.23 6.41 6.51 Oct-13 17.04 2.81 3.02 4.22 6.46 Nov-13 4.22 8.23 5.78 6.88 2.74 Dec-13 2.64 7.95 2.62 3.03 14.06 Jan-14 9.93 8.78 1.77 4.91 12.75 Feb-14 5.23 5.66 3.22 2.41 3.70 Mar-14 4.03 3.11 3.37 2.65 5.74 Apr-14 1.64 5.19 3.35 1.39 2.09

May-14 2.17 6.12 3.20 3.31 2.82 Jun-14 2.18 5.32 1.50 0.98 3.23

90Trillions of Rp Point

115

80

70

60

50

40

30

20

10

2009

2010

2011

2012

2013

Jan-

14

Feb-

14

Mar

-14

Apr-1

4

May

-14

Jun-

14

0

110

105

100

95

90

85

80

SBN IDMA (RHS)

1200Trillions of Rp

1000

800

600

400

200

0Jun-11 Dec-11 Jun-12 Dec-12 Jun-13 Jun-14Dec-13

Others Securities Pension Funds Foreign

Insurers Mutual Funds Central Bank Banks

49


Based on SBN tenor, risk on long and medium-

tenor SBN tended to ease in comparison to short-term

tenors towards the end of the reporting semester. Such

conditions were reflected by yield volatility on medium

and long tenors, which consistently subsided. Conversely,

short-tenor volatility, which had previously eased, started

to climb again. Such developments indicate solid foreign

investor confidence in the long-term economic outlook

of Indonesia.


Graph 2.18.SBN Volatility by Tenor


Graph 2.19.Rebased SBN Yield by Tenor

Similar to SBN, corporate bonds outstanding and risk

were both observed to decline. Investor proclivity towards

corporate bonds held to maturity (HTM) prompted a

decline in volatility. At the end of the first semester of

2014, average yield volatility of bonds of all tenors was

5.56%, down on the 9.87% posted in the previous period.

An increase in foreign holdings on the corporate bond

market also spurred a decrease in volatility. At the end

of the reporting semester, foreign held corporate bonds

increased by Rp2.69 trillion, or 19.45%, on the preceding

semester. In total, corporate bonds outstanding increased

at the end of the first semester from Rp184.11 trillion to

Rp217.41 trillion. In terms of trade, the trade frequency

of corporate bonds was relatively stable in the range of

1,125 – 2,035 times since the beginning of the semester,

which is in line with the propensity of investors to hold

corporate bonds to maturity (HTM).

Based on rating, bonds with an average BBB rating

experienced a decline in yield of 50 bps during June

2014 for each tenor compared to the previous semester.

Meanwhile, bonds with an average AAA rating remained

stable as the majority were held to maturity by investors.

Such conditions indicate profit-taking behaviour by foreign

investors through placements in corporate bonds with

a lower rating, which are more vulnerable to a sudden

reversal.

200Point

rebased 1/1/2013

1-5 years 6-10 years 11-30 years

180

160

140

120

100

80

Jun-13Jul-1

3

Ags-13

Sep-13

Oct-13

Nov-13

Dec-13

Jan-14

Feb-14

Mar-14

Apr-14

May-14

Jun-14

Short Term Medium Term Long Term

40(%)

35

30

25

20

15

10

5

0

Ags-13

Sep-13

Oct-13

Nov-13

Dec-13

Jan-14

Feb-14

Mar-14

Apr-14

May-14

Jun-14Jun-13

Jul-13


50


2.1.5 Stock Market

On the stock market during the reporting period,

the JCI (Indonesian Stock Market composite index) rallied

while risk eased as volatility declined both as an aggregate

and by sector. Optimism surrounding a surge in economic

activity linked to the presidential election as well as sound

financial statements of domestic issuers helped stabilise

foreign capital inflows throughout the first semester.

Stock indices in Indonesia and the Philippines, which

share similar economic structures and issues in the eyes

of foreign investors, led gains on regional stock exchanges.


Graph 2.20.Corporate Bond Volatility by Tenor

Source: Financial Services Authority (OJK)

Graph 2.23.Corporate Bond Trade Frequency


Graph 2.21.Rebased Corporate Bond Yield by Tenor

Source: CEIC, processed

Graph 2.24.Foreign Net Flow and Holdings of Corporate Bonds

Source: Indonesia Bond Pricing Agency (IBPA)

Graph 2.22.Corporate Bond Yield Curve

40(%)

35

30

25

20

15

10

5

0

Ags-13

Sep-13

Oct-13

Nov-13

Dec-13

Jan-14

Feb-14

Mar-14

Apr-14

May-14

Jun-14Jun-13

Jul-13


Short Term: 1-5 yearsMedium Term: 6-10 yearsLong Term: 11-30 years

145Point

135

140

130

125

120

115

105

100

Jun-13Jul-1

3

Ags-13

Sep-13

Oct-13

Nov-13

Dec-13

Jan-14

Feb-14

Mar-14

Apr-14

May-14

Jun-14

110


16(%)

15

14

13

12

11

10

9

8

7

61

SBN Jun14

AAA Dec13

2 3 4 5 6 7 8 9 10

SBN Dec13

BBB Jun14

AAA Jun14

BBB Dec13

180 230Trillions of Rp

2007 2008 2009 2010 2011 2012 2013 2014

1 2 3 4 5 6

thousand times

Corporate Bond Frequency

210

190

170

150

130

110

90

70

50

30

160

140

120

100

80

60

40

20

0

SUN Frequency Outstanding Corporate Bonds (RHS)

7

2010 2011 2012 2013 2014

1 2 3 4 5 6

18

16

14

12

10

8

6

4

2

0

Trillions of Rp Trillions of Rp

6

5

4

3

2

1

0

(1)

Outstanding Foreign Holdings (RHS)Net Flow

51


Less risk on the domestic stock market was also

inextricably tied to less risk on regional and global stock

markets. As presented in subsection 1.1 concerning

Regional and Global Market Performance, the volatility of

several global stock market indices was observed to decline

at the end of the first semester compared to yearend 2013

despite escalating due to heightened political tensions

along the Russia-Ukraine border. A decrease in global

volatility primarily stemmed from improved investor

sentiment regarding the crisis in Europe after sources of

the crisis, such as Greece, Ireland, Spain, Portugal and Italy

enjoyed a bump in their respective credit rating. In the case

of Greece, government securities were reissuedfor the

first time since 2010. Meanwhile, stock market volatility

in Indonesia also eased in line with a number of other

markets in the region.


Graph 2.25.Regional Stock Market Performance


Graph 2.27.Flow to Shares and JCI


Graph 2.26.Regional Stock Market Volatility


Table 2.3.Heat Map of Index Volatility by Sector

2012TW 4 TW 1 TW 2 TW 3 TW 4 TW 1 TW 2

IDX Composite 9.39 12.78 22.75 31.04 17.63 18.13 14.30Financial 15.76 17.28 25.58 37.01 23.24 24.66 18.60Agriculture 16.65 14.65 22.79 32.19 19.01 24.91 17.13Basic Industry 14.06 17.20 28.94 43.96 25.15 25.30 22.35Consumption 19.56 16.57 30.87 40.22 21.32 18.81 15.28Property 12.90 22.29 31.57 43.93 23.11 28.19 20.16Mining 14.64 22.75 22.22 31.85 19.48 18.58 17.10Infrastructure 14.13 15.97 28.22 31.29 20.63 20.98 17.29Trade 11.15 14.61 23.40 27.69 13.76 12.99 14.18Miscellaneous Industries 28.06 23.78 37.45 45.79 31.39 31.02 22.14

2013 2014

Indonesia Thailand Malaysia the Philippines

Jan-

13

Feb-

13

Mar

-13

Apr

-13

May

-13

Jun-

13

Jul-1

3

Ags

-13

Sept

-13

Jan-

14

Feb-

14

Mar

-14

Apr

-14

May

-14

Jun-

14

Oct

-13

Nov

-13

Dec

-13

130Point

125

120

115

110

105

100

95

9085

80

Indonesia Thailand the PhilippinesMalaysia Singapore

Jun-

13

Jul-1

3

Aug-

13

Sep-

13

Jan-

14

Feb-

14

Mar

-14

Apr-

14

May

-14

Jun-

14

Oct

-13

Nov

-13

Dec

-13

90Trillions

80

70

60

50

40

30

20

10

0

5000PoinRp (T)

4500

4000

3500

3000

2500

2000

30

25

10

0

-10

-20

-30

Saham JCI (skala kanan)

2009

2010

2011

2012

2013

Jan-

14

Feb-

14

Mar

-14

Apr-

14

Mei

-14

Jun-

14

52


Based on share type, the role of non-LQ45 shares

expanded in comparison to the shares of LQ45 companies,

as demonstrated by the portion of LQ45 that shrank to 65%

in June 2014 from 80% at the end of 2009. Nevertheless,

compared to the portion at yearend 2013, little change

has occurred. As derivatives increasingly crowd the stock

market, for instance mutual funds, their contribution helps

extend the market share of non-LQ45 shares. Furthermore,

the expanding role of non-LQ45 shares is also attributable

to the market’s view that such shares are under-priced and

therefore attractive to foreign investors. Such conditions

demand vigilance in order to prevent a sudden reversal.

2.1.6 Mutual Funds

During the reporting period, risk on the three main

investment fund markets (money market, stock market and

SBN market) was observed to decline as the risk associated

with each respective underlying asset also eased, as

reflected by less volatility. Less risk was accompanied by

stronger growth of managed funds. On the other hand,

Net Asset Value (NAV) increased in the first semester by

9.06% to Rp209.98 trillion compared to Rp192.54 trillion in

the preceding period. Year on year, NAV growth remained

positive during the first semester of 2014.Source: Bloomberg, processed

Graph 2.28.JCI Share Trade Frequency


Graph 2.29.JCI and LQ45 Capitalisation

Source: Financial Services Authority (OJK) report

Graph 2.31.Mutual Fund NAV Volatility by Type


Graph 2.30.JCI and LQ45 Price Performance

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Feb-

08

Jun-

08O

ct-0

8Fe

b-09

Jun-

09O

ct-0

9Fe

b-10

Jun-

10O

ct-1

0Fe

b-11

Jun-

11O

ct-1

1Fe

b-12

Jun-

12O

ct-1

2Fe

b-13

Jun-

13O

ct-1

3Fe

b-14

Jun-

14

Non LQ45 LQ45

6.000Trillions of Rp

80%

75%

70%

65%

60%

55%

50%

45%

40%

5.000

4.000

3.000

2.000

1.000

IDX Composite Capitalisation

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

LQ45 Capitalisation LQ45 Share (RHS)

1400

1200

1000

800

600

400

200

Spread (RHS) JCI

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

0

rebased 1/1/2000 500bps

400

300

200

100

0

-100

-200

LQ45

60(%)

50

40

30

20

10

Fixed-income funds

0

Jan-13

Feb-13

Mar-13

Apr-13

May-13

Jun-13

Jan-14

Feb-14

Mar-14

Apr-14

May-14

Jun-14

Jul-1

3

Aug-13

Sep-13

Oct-13

Nov

-13

Dec-13

Discretionary funds Equity funds

53


50

48

46

44

42

40

38

36

34

32

30

1 2 3 4 5 6 7 8 9 10 11 12

2011 2012 2013 2014

Trillions of Rp45

40

35

30

25

20

1 2 3 4 5 6 7 8 9 10 11 12

2011 2012 2013 2014

Trillions of Rp

Total Mutual Funds (RHS) NAV (trillions of Rp) Units in Circulation (millions)

1 4 7 10

2008

250 900

800

700

600

500

400

300

200

100

0

200

150

100

50

01 4 7 10

2009

1 4 7 10

2010

1 4 7 10

2011

1 4 7 10

2012

1 4 7 10

2013

1 4

2014

A favourable mutual fund market was also evidenced

in the first semester by a tendency that followed seasonal

trends over the past three years. By type, equity funds

continued to dominate the NAV of mutual funds with a

43.39% share, followed by protected funds with 20.38%.


Graph 2.32.Growth of Mutual Funds (yoy)

Graph 2.34.NAV trend ofMutual Funds by Type


Graph 2.33.Position of Mutual Funds

40%

35%

30%

25%

20%

15%

10%

5%

0%

-5%

-10%

NAV Units in Circulation Total Mutual Funds

1 2 3 4 5 6 7 8 9 10 1112

2012

1 2 3 4 5 6 7 8 9 10 1112

2013

1 2 3 4 5 6

2014

Trillions of Rp100

90

80

70

60

50

40

1 2 3 4 5 6 7 8 9 10 11 12

2011 2012 2013 2014

16

15

14

13

12

11

10

9

8

7

6

1 2 3 4 5 6 7 8 9 10 11 12

2011 2012 2013 2014

Trillions of RpEquity funds Money market funds

Protected funds Fixed-income funds

The market share of equity funds increased compared to

the previous semester, indicating growing investor interest

in equity funds as share performance increased. Nominally,

the net asset value of nearly all types of investment funds

increased.

Source: Financial Services Authority (OJK) report, processed

54


pushing up returns on equity funds and balanced funds.

Such conditions were reflected in the majority of equity

funds with positive excess returns at the end of the first

semester. Maintained SBN prices offset further gains in

discretionary funds and ensured relatively stable returns

on fixed-income funds.

Concerning individual investment fund products, a

significant decline in risk was experienced by equity funds

as the beta coefficient for the majority of equity funds

dropped, which precipitated JCI gains along with less NAV

volatility. Concerning balanced funds, fixed-income funds

and money market funds, the majority of beta coefficients

remained below 1 in line with the natural characteristics of

short-term bonds and securities as underlying assets with

low price volatility compared to equity funds.

Sumber : Bloomberg, diolah

In general, mutual funds experienced higher

returns and less risk during the reporting semester. The

JCI rallied 12.7% during the first semester of 2014, hence

Graph 2.36.Risk Profile of Mutual Fund Products


Graph 2.35.NAV of Mutual Funds by Type

Trillions of Rp

220200

180160140120100

80

604020

0

Jan

Apr

Jul

Oct

2009

Jan

Apr

Jul

Oct

2010

Jan

Apr

Jul

Oct

2011

Jan

Apr

Jul

Oct

2012

Jan

Apr

Jul

Oct

2013

Jan

Apr

2014

Equity funds Money market funds Discretionary FundsFixed-income funds Protected funds Others

Money Market Funds Fixed-income Funds

Discretionary Funds Equity Funds

55


2.2 THE FINANCIAL MARKET AS A SOURCE OF NON-BANK FINANCING

Financing activity through non-bank financial

institutions, in general, increased from Rp65.77 trillion at

the end of the second semester of 2013 to Rp71.51 trillion

in the reporting period. The increase primarily affected the

capital market, which is observable from the number of

issuers instituting initial public offerings (IPO) and rights

issues in the first semester of 2014 with a nominal value of

Rp30.43 trillion. Correspondingly, issuances of corporate

bonds also increased during the first semester, totalling

Rp28.18 trillion compared to just Rp13.37 trillion in the

previous period.

Tenacious investor interest in domestic financial

market assets along with sustained economic growth

provided momentum for the corporate sector to seek

alternative sources of financing outside of the banking

sector. Furthermore, a wide spread between bank lending

rates and the reference rate also boosted corporate

interest in terms of issuing bonds. The government also

responded by implementing continuous bond policy in

2010, which simplified the issuance of bonds and reduced

dependence on bank financing.


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

Graph 2.37.Nominal Value of Bonds

Trillions of RP2014

sem I sem II sem I

A. Bank Credit 327.92 434.25 507.77 251.26 333.75 175.29B. Non-Bank Financing 156.76 158.96 154.32 95.25 65.77 71.51 B1. Capital Market 112.95 100.01 97.57 76.48 38.56 58.61

- IPO and Rights Issues 76.35 54.28 30.10 32.35 25.19 30.43 - Corporate Bonds 36.60 45.74 67.46 44.13 13.37 28.18

B2. Finance Companies 43.81 58.95 56.75 18.77 27.21 12.90Total 484.68 593.21 662.09 346.51 399.52 246.79

2010 2011 20122013

Description

Table 2.4.Bank and Non-Bank Financing

Concerning initial public offerings (IPO), there are

typically between 12 and 30 new issuers each year. During

the first semester of 2014, however, share issuances only

totalled Rp16.75 trillion, less than half the total issued in

2013 (Rp57.54 trillion). On the other hand, slower bank

credit growth did not seem to trigger a substitution of bank

credit for shares, reflecting increasingly limited domestic

sources of funds.

14 30

25

20

15

10

5

0

(%)Trillions of Rp

12

10

8

6

4

2

0

-2

Corporate bonds (trillions of Rp)

BI Rate (%)

Working Capital Credit (%)

YOY Exchange Rate (RHS)

-4

Jan-13

Feb-13

Mar-13

Apr-13

May-13

Jun-13

Jan-14

Feb-14

Mar-14

Apr-14

May-14

Jun-14

Jul-1

3

Ags-13

Sep-13

Oct-13

Nov

-13

Dec-13

56


2.3 THE IMPORTANCE OF FINANCIAL MARKETS FOR

THE BANKING INDUSTRY

Financial markets, as explained previously, are

critical to the banking sector as the dominant industry in

the financial system of Indonesia. This is because bank

business activity, in addition to directly accumulating

and disbursing third-party funds, also operates through

Source: Financial Services Authority (OJK)

Graph 2.38.Capital Market Financing

60 8

7

6

5

4

3

2

1

0

50

40

30

20

10

02007 2008 2009 2010 2011 2012 2013 2014

Trillions of Rp Percent

IPORights Issues GDP (RHS)

Working Capital Credit (yoy)New Issuers

financial markets, therefore interconnectedness between

financial markets and the banking industry is vital.

Bank activity through financial markets encompasses

the management of short and long-term funds. In

general, short-term funds are used to optimise liquidity

management in the form of lending and borrowing

through the interbank money market, bond market

and other money market activity such as open market

operations conducted by Bank Indonesia (purchases and

redemptions of Bank Indonesia Certificates (SBI), the

deposit facility, repo transactions and the lending facility).

Meanwhile, long-term fund management ordinarily aims

to maintain credit allocation and/or raise capital, which

can be achieved through the capital market, bond market

and offshore loans. Amidst a slowdown in deposit and

credit growth during the reporting semester, financial

markets played an increasingly significant role for the

banking industry in terms of optimising short-term fund

management (liquidity) or as an alternative source of long-

term funds used to extend credit or raise capital.

Table 2.5.Total Banks using Alternative Sources of Funding

2014Sem I Sem II Sem I Sem II Sem I

Fund AccumulationI. DomesticInterbank Rupiah Loans 54 79 74 81 81 Interbank Foreign Currency Lending 51 51 50 48 47 Repo at Bank Indonesia / LF 3 4 3 10 1 Repo by banks 6 7 7 10 16 Bond Market 7 6 8 3 2 - Bonds 2 2 3 1 - Continuous Bonds 4 4 4 3 1 - Sukuk Bonds 1 1 Stock Market 3 4 7 9 3 - IPO 4 2 1 - Rights Issues 3 4 3 7 2 II. InternationalBonds (USD) 1 1

Fund DisbursementsI. DomesticInterbank Rupiah Lending 89 95 93 95 94 Interbank Foreign Currency Lending 48 47 48 49 45 Deposit Facility 107 105 110 100 107 Term Deposit 51 65 39 - - Bank Indonesia Deposit Certificates - - - 43 50 Bank Indonesia Certificates 95 86 91 98 98 SUN Reverse Repo 38 30 31 25 36 SBN 43 51 52 58 50

Source of Funds 2012 2013

Source: Bank Indonesia, Financial Services Authority (OJK)

57


In terms of short-term fund management during

the first semester of 2014, the number of banks with

loans and placements on the interbank money market

totalled 81 and 94 banks respectively, with a average daily

volume of Rp12.2 trillion compared to Rp10.7 trillion in the

preceding semester. Bank placements at Bank Indonesia

in the form of Bank Indonesia Certificates and the deposit

facility increased on the previous semester. Meanwhile,

bank redemptions at Bank Indonesia in the form of

repo transactions and the lending facility experienced a

dramatic decline due to a shift away from transactions

at Bank Indonesia towards interbank transactions in

the form of repurchase agreements. The Mini Master

Repo Agreement (MRA) signed by the banking industry

in December 2013, which was expanded in February

2014, successfully boosted collateral-based interbank

transactions, providing a private solution to bank liquidity

management while concomitantly reducing dependence

on Bank Indonesia. As many as 16 banks made use of

interbank repo transactions, more than 1.5 times the

number in the previous semester. In harmony with the

proliferation of repo transactions in the banking sector,

the repo rate has also dropped.

On the bond market, issuances of corporate bonds

by the banking sector increased during the first semester

of 2014, primarily due to issuances of continuous bonds.

Nevertheless, only one bank issued regular corporate

bonds and one bank issued continuous corporate

bonds. Total volume of corporate bonds issued by the

banking sector amounted to Rp5.0 trillion, up 35% on the

previous semester but still well below issuances in the

same semester of the preceding year. Corporate bonds

Table 2.6.Volume of Bank Funding based on Alternative Sources of Funds

Trillions of Rp2014

Sem I Sem II Sem I Sem II Sem IFund Accumulation

I. DomesticInterbank Money Market - Vol. RRH Pinjam Rp 8.5 10.2 10.3 10.7 12.2 - Vol. RRH Pinjam Vls (US Jt) 633.2 408.9 346.7 371.7 359.9 Repo at Bank Indonesia/ LF 0.4 1.1 0.5 5.5 0.1 Repo by banks 32.7 41.0 31.1 32.3 113.4 Bond Market 6.8 7.1 8.5 3.7 5.0 - Bonds 0.5 0.3 1.2 1.0 - Continuous Bonds 5.5 6.8 6.6 3.7 4.0 - Sukuk Bonds 0.8 0.7 Stock Market 1.9 4.7 4.2 9.4 1.5 - IPO 1.7 0.6 0.1 - Rights Issues 1.9 4.7 2.4 8.8 1.5 II. InternationalBonds (millions of USD) 500 500 Offshore Loans (billions of USD) 21.5 23.0 23.3 24.1 27.2

Fund DisbursementsI. DomesticInterbank Rupiah Lending - Vol. RRH Beri Rp 8.5 10.2 10.3 10.7 12.2 - Vol. RRH Beri Vls (US Jt) 633.2 408.9 346.7 371.7 359.9 Deposit Facility 118.3 81.6 121.1 123.5 125.3 Term Deposit 88.7 180.9 51.7 - - Bank Indonesia Deposit Certificates - - - 26.5 23.3 Bank Indonesia Certificates 89.9 79.4 82.1 89.6 98.6 SUN Reverse Repo 60.3 81.4 73.5 74.6 74.4 SBN 244.5 233.2 226.6 228.7 253.5

Source of Fund 2012 2013

Source: Bank Indonesia, Financial Services Authority (OJK)

58


issued by the banking sector in the first semester of 2014

accounted for 22.70% of total corporate bond issuances,

which is a slightly larger portion than that recorded in

2013 at 20.45%.

Sources of long-term bank funding through the stock

market tended to decline as a result of escalating risk in

the run up to the presidential election, thus banks delayed

entering the capital market or expedited the issuance in

the previous semester. Share issuances by the banking

sector slumped significantly in the first semester of 2014,

namely by 84.04% to just Rp1.5 trillion. The dramatic

decline was attributed to merely one bank implementing

an initial public offering (IPO) and only two banks initiating

a rights issue. Such circumstances were the result of

general conditions on the Indonesia stock market, where

only 13 additional companies were listed as of the end of

June 2014 without any delisted. The total volume of IPO

and rights issues initiated by the banking sector accounted

for just 2.61% of total share issuances in the first semester

of 2014.

In addition to the aforementioned sources of

funding, the position of external (offshore) debt in the

banking industry also increased as elaborated in Chapter

1 concerning an increase in corporate exposure to external

debt. Total external debt in the banking sector jumped

significantly by Rp3 trillion in the reporting semester,

compared to just Rp800 billion in the preceding period, as

a consequence of a cheaper cost of funds internationally

despite exchange rate risk that must be mitigated by the

banking sector.

59


Box 2.1. Impact of the Election on Financial Market Risk

Financing and Financial Market Activity during the

Election Period

The periods prior to and after an election are

critical times for the economy of any country. Economic

contractions are often experienced in a number of

sectors and on financial markets as uncertainty mounts

amongst economic participants. Nonetheless, an

election can also trigger a proliferation of economic

and financial market activity if the winning candidate

is in line with expectations and expected to institute

policies conducive to economic growth.

Election periods in 2004 and 2009 indicated a

trend of increased trade activity on the stock market

and JCI in line with positive market perception

concerning the selected candidate. In terms of

funding, however, investor behaviour was mixed, with

an increase in initial public offerings but fewer rights

issues and issuances of corporate bonds. In general,

during both aforementioned election periods, pre-

election funding exceeded post-election funding,

which is indicative of risk aversion amongst investors

who sought funding earlier before uncertainty spread

in the post-election period.


Box Graph 2.1.1.Stock Market Activity 2003-2005


Box Graph 2.1.2.Aktivitas Pasar Saham 2008 - 2010

1,400Point Jt Lbr

12,000

10,000

8,000

6,000

4,000

2,000

1,200

1,200

1,200

1,200

1,200

1,200

Jan-03 Jul-04

Average Annual Volume (Jt Lbr)

Jan-04 Jul-04 Jan-05 Jul-05

JCI Transaction Volume (RHS)

7,000

6,000

5,000

4,000

3,000

2,000

1,000

Jan-08 Jul-08 Jan-09 Jul-09 Jan-10 Jul-10

30,000

25,000

20,000

15,000

10,000

5,000

Jt LbrPoint

Average Annual Volume (Jt Lbr) JCI Transaction Volume (RHS)

60


Trade activity in the SBN market increased after

the 2009 Election as issuances of SBN increased and

foreign investor inflow surged. In addition to the

fact that the election was orderly and the result was

in line with expectations, growing investor interest

in emerging market assets, which provided higher

returns, further supported the SBN market.

During the first half of 2014, share trade activity

declined in comparison to the same period of the

preceding year despite continued gains on the JCI. The

decline in trade activity was the result of global factors,

such as geopolitical issues in the Middle East and

Russia, an economic downswing in China and a weak

economic outlook for advanced countries. Meanwhile,

domestic conditions were shrouded with uncertainty

regarding the results of the presidential election,

concerns over high inflation and the burgeoning

current account deficit.

Box Table 2.1.1.Funding through the Capital Market during Election Periods

Billions of Rp

IPO Right Issue Bond Total

Before 909 3,047 11,570 15,525 After 1,287 1,295 7,600 10,182 Total 2,195 4,342 19,170 25,707 Before 635 4,995 15,260 20,890 After 3,083 4,330 11,955 19,368

3,718 9,325 27,215 40,258 Before 5,001 30,811 18,033 53,845 Target 13,500 22,500 56,430 92,430 % to Target 37% 137% 32% 58%

2014

Election Period

2004

2009

ource: Bloomberg, processed


Box Graph 2.1.3.SBN Market Activity 2004-2005


Box Graph 2.1.4.Pasar SBN 2008 – 2010

570

560

550

540

530

520

510

500Feb-04 Jun-04 Oct-04 Feb-050 Jun-05

101

100

99

98

97

96

95

94

93

92

Trillions of Rp Point

Average Annual Nominal IDMA index (RHS)Nominal

1,050

1,000

950

900

850

800

750

700

650

600Jan-08 May-08 Sep-08 Jan-09 May-09 Jan-10 May-10Sep-09

110

105

100

95

90

85

80

75

70

65

60


Average Annual Nominal IDMA index (RHS)Nominal

61



Box Graph 2.1.5.Stock Market Activity 2013-Semester I 2014


Box Graph 2.1.7. JCI Volatility


Box Graph 2.1.8.SBN Volatility


Box Graph 2.1.6.SBN Market Activity 2013-Semester I 2014

On the SBN market, a slight drop in the majority

of yields occurred, averaging 17 bps, compared to the

end of 2013. Dissimilar to share trading, SBN trading

expanded as the government continuously issued SBN

from the beginning of the year as part of its front-

loading strategy.

Financial Market Risk during the 2014 Election

During the 2014 Election, risk on the stock market

and SBN market escalated temporarily as JCI volatility

and SBN yield increased. In addition, the increase in

risk was also observed in the yield of SBN auctioned

on the primary market by the government as well as

the coupon rate of corporate bonds. Nevertheless,

the increase in volatility on the stock market and SBN

market was relatively small compared to the period

when concerns arose over the Federal Reserve’s plan

to taper off its monetary policy in the second semester

of 2013 and at the beginning of 2014.

A continued upward JCI trend along with

lower SBN yields also reflected relatively limited

risk despite fluctuations in the wake of a downturn

5500Point Millions

5000

4500

4000

3500

3000

Jan-

13

Feb-

13M

ar-1

3Ap

r-13

May

-13

Jun-

13

Jan-

14

Feb-

14M

ar-1

4Ap

r-14

May

-14

Jun-

14

Jul-1

3

Ags-

13

Sep-

13

Oct

-13

Nov

-13

Dec-

13

14,000

12,000

10,000

8,000

6,000

4,000

2,000

0

Average Annual Volume (millions)JCI Volume (millions) (RHS)

1.500


1.400

1.300

1.200

1.100

1.000

900

Jan-13

Mar-13

May-13

Jan-14

Mar-14

May-14

Jul-13

Sep-13

Nov-13

125

120

115

110

105

100

95

90

85

Nominal Trs IDMA Index

JCI (Rebased 1/1/11=100)

Mar

-12

Jun-

12

Sep-

12

Dec

-12

Mar

-13

Jun-

13

Sep-

13

Dec

-13

Mar

-14

Jun-

14

160Point (%)

50

45

40

3530

2520

15

10

50

JCI Volatility (RHS)

140

120

100

80

60

40

20

0

0

5

10

15

20

25

30

35

4(%)

0

Jan-

13Fe

b-13

Mar

-13

Apr-

13

May

-13

Jun-

13Ju

l-13

Aug-

13Se

p-13

Oct

-13

Nov

-13

Dec

-13

Jan-

14Fe

b-14

Mar

-14

Apr-

14M

ay-1

4Ju

n-14


Series Maturity Jk Pendek

62


during the legislative and presidential elections. The

implementation of an election that was in line with

market expectations bolstered investor confidence

in the increasingly positive economic outlook of

Indonesia.

Positive market perception and optimism were

reflected in the Consensus Forecast published by

Bloomberg regarding several improving domestic

economic indicators. In its Consensus Forecast,

Bloomberg projects inflation to drop to 4.8%, real

GDP at 5.55%, the rupiah at a level of Rp11,775 per

US dollar and the BI rate at 7.5% at the end of 2014.

The improved forecast supports a reduction in risk

on domestic financial markets, thereby prompting an

increase in trade activity.


Box Graph 2.1.9.JCI, Yield and the Rupiah in 2014


Box Graph 2.1.10.Actual and Forecasted Indicators

Jun-13Jul-1

3

Ags-13

Sep-13

Oct-13

Nov-13

Dec-13

Jan-14Fe

b-14

Mar-14

Apr-14

May-14

Jun-14

200Point

180

160

140

120

100

80

60

Rebased 1/1/2013

JCI5-year SBN IDR

9 14000

13000

12000

11000

10000

9000

8000

7000

6000

8

7

6

5

4

3

2 2012Q3

2012Q4

2013Q1

2013Q2

2013Q3

2013Q4

2013Q1

2013Q2

2014Q3

2014Q4

(%) (Rp)

BI Rate CPI Real GDP Exchange Rate (RHS)

63


Box 2.2 Shadow Banking in Indonesia

Shadow banking has recently come under the

spotlight in the financial systems of a number of

countries. The term ‘shadow banking’ itself was coined

at the G-20 Seoul Summit in 2010 and subsequently

defined by the Financial Stability Board (FSB) as the

system of credit intermediation that involves entities

and activities outside, or in ways only partially linked

to, the traditional system of regulated depository

institutions, with salient parameters including the

transformation of liquidity, maturity and credit risk

along with an element of leverage. Consensus among

all FSB members concerning that definition has not

yet been reached, however it is often referenced in

various publications. Furthermore, several publications

replacethe term shadow banking with non-bank

financial intermediaries (NBFI). Rapid unmonitored,

unregulated and unsupervised growth of shadow

banking was cited as a contributing factor to the

global financial crisis in 2008 in advanced countries,

at least in the United States. Concerns over a re-

escalation of systemic risk from the shadow banking

sector on financial stability re-emerged after the

publication of Basel III regulatory recommendations

for the banking sector that called for space for

regulatory arbitrage between banks and non-banks.

Consequently, G-20 leaders mandated the FSB to

cooperate with international standard setting bodies1

and formulate recommendations to strengthen

monitoring and supervision in order to mitigate system

risk stemming from shadow banking. Discussions and

recommendations remain an ongoing concern at a

number of committees and workstreams coordinated

by the FSB. Bank Indonesia, as a member of the

Financial Stability Board (FSB), continues to follow all

developments.

Fundamentally, shadow banking does not

necessarily have to be limited because in the majority

of developing countries, non-bank intermediation

helps broaden public access to the financial system. In

Indonesia, for instance, the presence of microfinance

institutions is considered crucial in the development

of micro, small and medium enterprises (MSMEs).

Nonetheless, shadow banking regulation and

supervision requires attention in line with its dynamics

within the financial system.

There are two main risk transmission channels

of shadow banking, through interconnectedness

with the banking system as well as direct exposure to

shadow banking by market participants. Regulatory

instruments to control interconnectedness can be

implemented through various methods, for example

by limiting exposure of bank funds and placements

to shadow banking or by expanding capital buffers

for bank exposure to shadow banking. Regulatory

instruments to control exposure to shadow banking

can be introduced directly for non-bank entities

and products in accordance with the nature and

characteristics of the products and entities.

There are numerous types of products and

entities that can be categorised as shadow banking,

particularly in countries with developed financial

markets. One classification approach is based on

similar characteristics, namely: (i) collective investment

contracts with the inherent risk of rush/runs, such

as mutual funds; (ii) funds that generally depend 1) BCBS, IOSCO

64


on short-term funding, such as financecompanies;

(iii) market activity intermediation, such as broker-

dealers; (iv) facilitators of credit creation, such as

guarantee companies; and (v) intermediation based

on securitisation trends, such as asset securitisation.

In the context of implementing macroprudential

supervision, Bank Indonesia routinely assesses potential

systemic risk emerging from non-bank financial

institutions. Complementing routine assessments, a

study conducted in 2013 showed that shadow banking

in Indonesia is still at the embryonic stage due to the

relative lack of variation in terms of shadow banking

products, activities and entities compared to practices

in advanced countries. Furthermore, regulation of

shadow banking in Indonesia is considered below

optimal condition with room for improvement for its

supervision. In general, insurers, finance companies,

mutual funds, pension funds and the corporate

sector have been identified as five large entities

with the largest assets. Other additional forms of

shadow banking have also been identified, including

pawnbrokers, venture capital firms and discretionary

funds that also contain transformation risk.

In broader terms, Indonesia has continually

participated in the Global Shadow Banking Monitoring

Exercise since 2012 under the auspices of the Financial

Stability Board (FSB) in order to compare conditions

in Indonesia with those in other countries. Monitoring

on a global scale is not a simple endeavour due to

constraints stemming from the variety of financial

systems, products, activities, data availability and

perceptions of authorities in respondent countries.

In addition to the non-bank financial intermediaries

approach, the FSB also uses the term ‘other financial

intermediaries’ (OFI) as a proxy of shadow banking

size. OFIs consist of NBFI, excluding insurers and

pension funds, namely two industries that are already

relatively well regulated and supervised. Based on

the parameters and survey template issued by the

FSB, relative shadow banking growth in Indonesia

is moderate and decelerating, accounting for a

comparatively small portion of total financial assets.

Source: Financial Stability Board (FSB), processed

Box Graph 2.2.1.Exposure of Non-Bank Financial Intermediaries

Source: Financial Stability Board (FSB), processed

Box Graph 2.2.2.Growth of Non-Bank Financial Intermediaries

0

200

400

600

800

1000

NL UK CH XM HK US KR FR CA ZA DE ES JP BR AU SG IT CL CN MX IN TR ID AR RU SA

Aver

age

Percentage of GDP

Respondent Countries

2011 2012 Bank Assets 2012

-20

-10

0

10

20

30

40

50

CN

AR IN ZA

RU

BR

MX

TR

KR ID US

HK

CA

SG

DE

CH

XM SA JP FR

AU

NL

CL IT

UK

ES

Percentage

2011 2012

65


Moving forward, Indonesia faces the challenge

of mitigating risk that emerges from shadow banking

activity, including potential additional complexity

and variation, as well as accurate and up-to-date

information for monitoring purposes. Notwithstanding,

optimism remains concerning additional guidelines

from the FSB and standard setting bodies that

will complement corrective measures in terms of

monitoring, regulation and supervision as well as

inter-authority coordination in Indonesia. In 2015,

the implementation of Act No 1 of 2013, concerning

micro, small and medium enterprises (MSMEs), will

also provide a little more substance to the development

of shadow banking in Indonesia.

67

Chapter 3. The Household and Corporate Sectors

The Household and Corporate Sectors

Chapter 3

68


69


3.1 HOUSEHOLD SECTOR ASSESSMENT

3.1.1 Household Sector Pro le

In general, the performance of the household and corporate sectors improved despite a moderate

slowdown at the outset of the rst semester of as a result of a sluggish global economy, rupiah

deprecia on and soaring in a on Nevertheless, at the end of the rst semester, lower in a on along

with ac vi es associated with the presiden al elec on boosted household and corporate ac vity

ousehold consump on growth underpinned economic e pansion with mi gated ris denoted by low

leverage The gross N ra o of ban credit e tended to households was also rela vely low despite a

slight increase on the preceding semester oten al ris s that demanded a en on in the household

sector were found to a ect low income households with high leverage and no savings omes c

demand pic ed up in the corporate sector as a result of elec on ac vity as well as prepara ons for

the holy fas ng month of amadan, have s mulated business ac vity oo ing ahead, the corporate

sector will con nue to face poten al ris s emana ng from persistently wea prices of leading non

oil gas e port commodi es

The Household and Corporate SectorsChapter3


346,550.80 18.72% 4,158,609.62

654,494.79 35.35% 7,853,937.54

1,701,099.53 45.93% 20,413,194.42

Low(Lowest 40%)

Medium(Second 40%)

High(Highest 20%)

ExpenditureGroup

MonthlyPer Capita

Expenditure(Rp)

Share ofNa onal

Expenditure

AnnualPer Capita

Expenditure(Rp)

3.1.2 Sources of Vulnerability and Household Sector

Condi ons

1971

119.21

147.49

173.38194.75

206.26

237.64255.46

271.06

5.91%8.57%

21.62%

23.72% 25%

20%

15%

10%

5%

0%

300

250

200

150

100

50

0

6.11%

15.21%

7.50%

19901980 1995 2000 2010 2015 2020

Growth (RHS

Total Households

8%

6%

4%

-6%

2%

-4%

0%

-2%

62.00

Millions

60.00

58.00

56.00

54.00

52.00

50.00

2000

52.01

55.04

56.62

58.25

55.1255.94

57.0157.72

58.42

61.16

5.83%

2.87%

2.88%

-5.38%

1.49%1.90% 1.24% 1.22%

4.69%

201020092008200720062005200420032002

Growth (RHS)

88.76%

89.73%

90.90%

91.60%92.13%

92.86%93.44%

93.87%93.75%

11.24% 10.27% 9.10% 8.39% 7.87% 7.14% 6.56% 6.13% 6.25%

105.86

106.39

109.94111.95

113.83

116.53 117.37 118.05118.19

98100102104106108110112114116118120

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2005 2006 2007 2008 2009 2010 2011 2012 2013

Millions of people

Employed Unemployed Total Labour Force (RHS)


2012

Monthly growth (%, mtm)Note: *Preliminary; **Projected

20.0

14.3

8.011.3

14.9 14.715.3

12.38.6

3.62.6

12.0

15.211.6

4.78.3

2.85.6

Annual growth (%, yoy)

40Percent

30

20

10

-10

-20

-30

0

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7**

2013 2014


200 7.5

6.0

4.5

3.0

0.0

1.5

190

180

170

160

1501 2 3 4 5 6 7 8 9 10 11 127 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1

2011 2012 2013 2014 2015

Percent

3.1.3 Household Financial Performance

2012

140.0

130.0

120.0

110.0

100.0

90.0

80.01 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7

2013 2014


Income Rp 1.22-2.45 juta Rp 2.56-3.65 juta Rp 3.76-4.85 juta Rp 5.03- 6.26 juta > Rp 6.26 juta Average

70.3% 69.3% 68.5% 66.9% 64.3% 67.9%

Loanrepayments

11.6% 12.9% 14.0% 14.6% 15.6% 13.9%

Savings 18.1% 17.8% 17.5% 18.5% 20.1% 18.2%Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Source: Consumer Survey. Bank Indonesia

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

Rp 1.22-2.45 juta 27.97% 17.38% 5.03% 3.44% 2.11%

Rp 2.56-3.65 juta 34.67% 19.64% 7.85% 4.69% 2.48%Rp 3.76-4.85 juta 20.81% 11.37% 4.73% 3.27% 1.44%Rp 5.03- 6.26 juta 8.64% 4.49% 2.03% 1.38% 0.74%

> Rp 6.26 juta 7.91% 4.02% 1.57% 1.35% 0.98%Total 100.00% 56.90% 21.21% 14.13% 7.75%

IncomeDSR

Total

Source: Consumer Survey, Bank Indonesia


Source: Consumer Survey. Bank Indonesia

c

0-10% 10%-20% 20%-30% >30% Inabilityto save

Rp 1.22-2.45 juta 27.97% 6.54% 5.94% 4.42% 4.37% 6.70%

Rp 2.56-3.65 juta 34.67% 9.96% 9.45% 5.67% 4.20% 5.38%Rp 3.76-4.85 juta 20.81% 7.71% 5.82% 3.30% 2.00% 1.99%Rp 5.03- 6.26 juta 8.64% 2.95% 2.58% 1.27% 1.03% 0.82%

> Rp 6.26 juta 7.91% 2.36% 2.44% 1.44% 1.03% 0.66%Total 100.00% 29.51% 26.23% 16.10% 12.62% 15.54%

IncomeSaving

TotalPercent

Property

100

2010

76.72 74.48 79.01 78.47

17.54 16.91 14.10 15.88

5.74 8.61 6.89 5.65

2011 2012 2013

90

80

70

60

50

40

30

20

10

0

Others (motor vehicles. householdequipment and clothing)

Financial Assets

Household Assets

PercentHousehold Financial Assets

Savings held at bank

100

2010

49.81 49.30 50.30 55.29

35.67 40.98 42.76 29.23

10.60 7.01

0.35 2.272.713.92

13.206.59

2011 2012 2013

90

80

70

60

50

40

30

20

10

0

Savings held at non bankInvestment Others (business and non-business receivables)


3.1.4 Bank Exposure to the Household Sector

19.5317.98

18.93

15.54

3.783.04 2.12 2.58

15.75 14.9516.80

12.9613.09 12.3813.46

9.97

0

5

10

15

20

25

2010 2011 2012 2013

Percent

Total debt/income Short-term debt/income

Long-term debt/income Bank debt/income

45.07%

15.25%

0.22%

34.80%

4.67%

43.64%

15.22%

0.22%

37.15%

3.77%

2014

2013

Percent

3.61

3.30

3.33

2.62

4.06

3.81

3.71

2.96

2.00

2.50

3.00

3.50

4.00

4.50

2010 2011 2012 2013

Total debt/total assets

76


3.2 CORPORATE SECTOR ASSESSMENT

3.2.1 Corporate Sector Pro le

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

2.00

100

200

300

400

500

600

700

800

Jan-

12Fe

b-12

Mar

-12

Apr-

12M

ay-1

2Ju

n-12

Jul-1

2Au

g-12

Sep-

12O

ct-1

2N

ov-1

2De

c-12

Jan-

13Fe

b-13

Mar

-13

Apr-

13M

ay-1

3Ju

n-13

Jul-1

3Au

g-13

Sep-

13O

ct-1

3N

ov-1

3De

c-13

Jan-

14Fe

b-14

Mar

-14

Apr-

14M

ay-1

4Ju

n-14

NPL (%)Trillions of Rp

Household credit (LHS) Household NPL (RHS)

Jan-

12Fe

b-12

Mar

-12

Apr-

12M

ay-1

2Ju

n-12

Jul-1

2Au

g-12

Sep-

12O

ct-1

2N

ov-1

2De

c-12

Jan-

13Fe

b-13

Mar

-13

Apr-

13M

ay-1

3Ju

n-13

Jul-1

3Au

g-13

Sep-

13O

ct-1

3N

ov-1

3De

c-13

Jan-

14Fe

b-14

Mar

-14

Apr-

14M

ay-1

4Ju

n-14

-20%

-10%

0%

10%

20%

30%

40%

50%

Growth (yoy)

Housing

3.500.000

2010

Micro

2011 2012 2013

3.000.000

2.500.000

2.000.000

1.500.000

1.000.000

500.000

24.000

23.900

23.800

23.700

23.600

23.500

23.400

23.300

23.200

23.100

23.000

Small Medium and Large (RHS)

Jan-

12Fe

b-12

Mar

-12

Apr-

12M

ay-1

2Ju

n-12

Jul-1

2Au

g-12

Sep-

12O

ct-1

2N

ov-1

2De

c-12

Jan-

13Fe

b-13

Mar

-13

Apr-

13M

ay-1

3Ju

n-13

Jul-1

3Au

g-13

Sep-

13O

ct-1

3N

ov-1

3De

c-13

Jan-

14Fe

b-14

Mar

-14

Apr-

14M

ay-1

4Ju

n-14

0,0%

0,5%

10%

15%

20%

25%

30%

NPL

Housing

Mikro Kecil Besar dan Sedang (skala kanan)

77


3.2.2 Sources of Vulnerability in the Corporate Sector

16.000USD

14.000

12.000

10.000

8.000

6.000

4.000

2.000

Natural Gas (LHS) Crude Oil (RHS) Coal (RHS)

2007

Q1 Q2 Q3 Q420

08Q1 Q2 Q3 Q4

2009

Q1 Q2 Q3 Q420

10Q1 Q2 Q3 Q4

2011

Q1 Q2 Q3 Q420

12Q1 Q2 Q3 Q4

2013

Q1 Q2 Q3 Q420

14Q1 Q2

0

160USD

105,37USD/Barrel

60,05USD/Short Ton

4.461USD/MBTU

140

120

100

80

60

40

20

0

7.000USD

6.000

5.000

4.000

3.000

2.000

1.000

Rubber CPO (RHS)

2007

Q1 Q2 Q3 Q420

08Q1 Q2 Q3 Q4

2009

Q1 Q2 Q3 Q420

10Q1 Q2 Q3 Q4

2011

Q1 Q2 Q3 Q420

12Q1 Q2 Q3 Q4

2013

Q1 Q2 Q3 Q420

14Q1 Q2

1.400

1.200

1.000

800

600

400

200

USD

774,24USD/Metric Ton

2.330USD/Metric Ton

78


3.2.3 Corporate Performance

21.05

29.44

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

TwII

TwI

TwIII*

TwII

TwI

TwIII

TwIV

TwII

TwI

TwIII

TwIV

TwII

TwI

TwIII

TwIV

2011 2012 2013 2014

% qtq NWB (%)

*)

Projected

79


2013 2014 2013 2014 2013 2014 2013 2014 2013 2014 2013 2014Crude Palm Oil 4.80% 3.02% 8.51% 5.84% 0.82 1.06 2.22 1.94 1.13 0.79 8.98 9.85Rubber -1.40% -4.29% -2.61% -8.82% 0.96 1.19 2.04 1.84 1.19 0.73 9.36 12.05Coal -2.53% 1.59% -8.12% 5.31% 2.44 2.39 1.41 1.42 1.09 0.89 17.04 18.09

-0.30% -2.01% -2.25% -13.96% 6.01 6.02 1.17 1.17 0.72 0.70 5.27 5.73

Inventory TOSector

ROA (%) ROE (%) DER TA/TL Current Ra o

2013 2014 2013 2014 2013 2014 2013 2014 2013 2014 2013 20141 Agriculture 4.38% 4.03% 8.15% 7.97% 0.87 1.07 2.14 1.94 1.23 0.90 8.00 8.702 Basic Industries and Chemicals 6.61% 4.90% 14.22% 10.54% 1.14 1.14 1.88 1.88 1.62 1.49 5.58 5.743 Consumer Goods 13.22% 12.14% 25.21% 24.56% 0.94 1.09 2.06 1.91 1.58 1.56 4.68 4.614 5.49% 3.97% 12.51% 9.57% 1.49 1.54 1.67 1.65 0.97 0.97 83.59 70.015 Miscellaneous Industries 8.02% 6.74% 18.39% 15.00% 1.24 1.22 1.80 1.82 1.22 1.18 9.19 8.756 Mining 0.29% 1.77% 0.75% 4.73% 1.75 1.69 1.57 1.59 1.18 1.06 13.07 13.137 7.39% 7.12% 14.79% 14.78% 1.08 1.07 1.92 1.94 1.80 1.72 1.91 1.918 6.83% 1.96% 12.48% 3.48% 0.84 0.89 2.20 2.12 1.69 1.51 7.88 7.61

6.16% 4.87% 13.16% 10.60% 1.18 1.21 1.85 1.82 1.42 1.32 6.86 6.68Aggregate

TA/TL Current Ra o Inventory TONo. Sector

ROA ROE DER

ROA

ROETA/TL


50Share (%) Constant GDP (YOY)

2

3

4

5

6

7

8

Distress Constant GDP (YOY) (RHS)

Dec-

07M

ar-0

8Ju

n-08

Sep-

08De

c-14

Mar

-09

Jun-

09Se

p-09

Dec-

09M

ar-1

0Ju

n-10

Sep-

10De

c-10

Mar

-11

Jun-

11Se

p-11

Dec-

11M

ar-1

2Ju

n-12

Sep-

12De

c-12

Mar

-13

Jun-

13Se

p-13

Dec-

13M

ar-1

4Ju

n-14

45

40

35

30

25

20

50Share (%)

41

43

31

42

DistressSafe Grey

Dec-

07M

ar-0

8Ju

n-08

Sep-

08De

c-14

Mar

-09

Jun-

09Se

p-09

Dec-

09M

ar-1

0Ju

n-10

Sep-

10De

c-10

Mar

-11

Jun-

11Se

p-11

Dec-

11M

ar-1

2Ju

n-12

Sep-

12De

c-12

Mar

-13

Jun-

13Se

p-13

Dec-

13M

ar-1

4Ju

n-14

45

40

35

30

25

20

ROA (%) ROE (%)

25%

20%

15%

10%

5%

0%

Mar

-07

Jun-

07Se

p-07

Dec-

07M

ar-0

8Ju

n-08

Sep-

08De

c-08

Mar

-09

Jun-

09Se

p-09

Dec-

09M

ar-1

0Ju

n-10

Sep-

10De

c-10

Mar

-11

Jun-

11Se

p-11

Dec-

11M

ar-1

2Ju

n-12

Sep-

12De

c-12

Mar

-13

Jun-

13Se

p-13

Dec-

13M

ar-1

4Ju

n-14

DER TA/TL

2,5

2,0

1,5

1,0

0,5

Mar

-07

Jun-

07Se

p-07

Dec-

07M

ar-0

8Ju

n-08

Sep-

08De

c-08

Mar

-09

Jun-

09Se

p-09

Dec-

09M

ar-1

0Ju

n-10

Sep-

10De

c-10

Mar

-11

Jun-

11Se

p-11

Dec-

11M

ar-1

2Ju

n-12

Sep-

12De

c-12

Mar

-13

Jun-

13Se

p-13

Dec-

13M

ar-1

4Ju

n-14


Buku 1 Buku 2 Buku 3 Buku 4

Mar Jun

2010

50.00%

45.00%

40.00%

35.00%

30.00%

25.00%

20.00%

15.00%

10.00%

5.00%

0.00%

2011 2012 2013 2014

Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun

Corporate

Mar Jun

2010

100.00%

90.00%

80.00%

70.00%

60.00%

50.00%

40.00%

30.00%

20.00%

10.00%

0.00%

2011 2012 2013 2014

Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun

Households and Individual Others

3.2.4 Bank Exposure to the Corporate Sector


300USD Miliar

Total

284,88

153,22

131,66

250

200

150

100

50

0

Mar

-07

Jun-

07

Sep-

07

Des-

07

Mar

-06

Jun-

06

Sep-

06

Des-

06

Mar

-05

Jun-

05

Sep-

05

Des-

05

Mar

-04

Jun-

04

Sep-

04

Des-

04

Mar

-08

Jun-

08

Sep-

08

Des-

08

Mar

-09

Jun-

09

Sep-

09

Des-

09

Mar

-10

Jun-

10

Sep-

10

Des-

10

Mar

-11

Jun-

11

Sep-

11

Des-

11

Mar

-12

Jun-

12

Sep-

12

Des-

12

Mar

-13

Jun-

13

Sep-

13

Des-

13

Mar

-14

Jun-

14

Pemerintah Swasta

3.2.5 Private External Debt

Jun-13 Jun-14Jun-13 (yoy)

sem I 2014 (ytd)

Jun-14 (yoy)

Jun-13 Jun-14

Crude Palm Oil 177,87 4,58% 5,10% 26,26% 11,4% 31,3% 1,11% 1,51%Rubber 25,60 0,79% 0,73% 6,70% -0,1% 9,0% 1,08% 2,00%Coal 41,19 1,41% 1,18% 16,37% -5,4% -1,3% 0,72% 2,23%

114,04 3,13% 3,27% 19,28% 7,4% 23,1% 2,29% 2.20%

Commodity

Outstandingcredit as ofJune 2014

(trillions of Rp)

Share of Total Credit Growth

Source: Bank Indon ia

Outstandingcredit as ofJune 2014

(trillions of Rp)

Growth inJune 2014

(ytd)

Growth inJune 2014

(yoy)

GrossNPL inJune2013

GrossNPL inJune2014

Agriculture 129.93 7.36% 6.62% 24.05% 0.68% 1.24%Mining 109.28 6.19% -8.13% 5.32% 0.86% 2.47%Manufacturing 527.76 29.88% -1.91% 27.47% 1.79% 1.88%Utilities (electricity. gas and sanitary water) 79.01 4.47% 4.86% 19.53% 0.35% 1.05%Construction 99.90 5.66% 10.92% 17.27% 3.71% 4.22%Trade. Hotels and Restaurants (THR) 356.81 20.20% -3.89% 23.35% 1.65% 2.12%Transportation. Storage and Communications 156.76 8.88% 11.02% 29.20% 2.23% 2.11%Corporate Services 268.14 15.18% 1.59% 12.13% 0.56% 0.69%Social/Public Services 22.79 1.29% 4.58% 8.17% 2.45% 2.92%Others 15.81 0.90% 65.30% 36.80% 0.52% 2.18%

Total 1.766.19 100.00% 0.81% 21.29% 1.50% 1.87%

Share ofTotal CreditEconomic Sector



6

7

(Million of USD)

2014

Sem I Sem II Sem I1 Agriculture, Livestock, Fisheries and Forestry 4,063 4,637 4,969 5,744 6,454 7,414 7,720 5.04%

2 Mining and Quarrying 12,103 10,842 16,878 20,346 25,240 26,381 27,224 17.77%

3 Manufacturing 19,336 19,471 22,646 25,637 26,660 29,168 30,885 20.16%4 9,707 13,142 14,946 16,855 16,456 17,088 18,734 12.23%

5 291 320 755 667 661 968 1,010 0.66%6 3,744 3,157 4,919 6,565 6,787 7,632 8,185 5.34%

7 4,739 6,272 8,108 10,080 10,326 10,084 10,479 6.84%8 Financial, Leasing and Corporate Services 15,981 21,048 28,390 34,862 35,706 37,180 42,579 27.79%

9 Services 400 769 584 637 563 975 965 0.63%

10 Others 3,242 4,130 4,537 4,852 5,135 5,150 5,443 3.55%

TOTAL 73,606 83,789 106,732 126,245 133,988 142,041 153,224 100.00%

ShareSem I 2014

No Economic Sector 20122013

2009 2010 2011


(million of USD)

Sem I Sem II Sem I*

1, Parent Company 7,547 11,947 15,785 21,677 23,128 25,867 69.73%

Agriculture, Livestock, Fisheries and Forestry 703 1,044 992 1,826 2,763 2,735 7.37%Mining and Quarrying 887 1,190 1,368 2,718 2,061 2,716 7.32%Manufacturing 3,376 3,871 5,912 8,215 8,500 9,495 25.60%

409 827 899 826 1,892 1,928 5.20%155 204 332 175 391 368 0.99%588 788 1,234 1,428 1,262 1,731 4.67%486 2,496 3,046 4,293 4,072 4,320 11.64%

Financial, Leasing and Corporate Services 649 1,225 1,740 1,918 1,622 1,841 4.96%Services 133 127 43 39 37 38 0.10%Others

Agriculture, Livestock, Fisheries and ForestryMining and QuarryingManufacturing

Financial, Leasing and Corporate ServicesServicesOthers

160 174 221 239 528 694 1.87%2, 10,956 10,392 11,491 10,915 11,275 11,231 30.27%

211 163 - - 33 34 0.09%2,994 2,364 3,952 3,205 3,230 3,108 8.38%1,429 1,493 1,356 927 1,056 1,083 2.92%4,143 4,404 3,840 4,023 4,017 4,022 10.84%

- - 93 1 - - 0.00%928 157 546 740 737 745 2.01%712 1,053 1,160 1,187 1,187 1,192 3.21%433 242 188 458 823 854 2.30%

55 220 167 167 - - 0.00%52 295 189 206 193 193 0.52%

18,503 22,339 27,276 32,592 34,402 37,098 100.00%TOTAL (1+2)

Share ofSem I 2014

2009 2010No Economic Sector 20112013 2014


Box 3.1 Credit Risk Concentra on in the Corporate Sector

Share of Debtors

86


Box 3.2 Risk of increasing Nonbank Private External Debt

8

9

Creditor Status

Short

Stress Testof Bank Credit

Export

Domes c

PeriodLong

Corporate

87


Throughout2013

( USD ( USD

N t Supp y/

Short Domes c 662 102,895 7,353 (36,942) Export 177 37,278 3,593 1,397

Short-Term Total 839 140,173 10,947 (35,546

BorrowerStatus

A 19 7,319 34%Non A 94 13,940 66%Tot 113 21,259 100%

StatusTotal Total

US ) US )Share(%)

Share(%)

113 21,259 18%2,051 95,407 82%

Tot 2,164 116,666 100%

-0,2

0,3

0,8

1,3

1,8

2,3

2,8

3,3

-12,0%

-7,0%

-2,0%

3,0%

8,0%

13,0%

18,0%

23,0%

28,0%

Mar-0

8…

Des-0

8

Sep-0

9

Jun-10

Mar-1

1

Des-1

1

Sep-1

2

Jun-13

Jun-08

Mar-0

9

Des-0

9

Sep-1

0

Jun-11

Mar-1

2

Dec-1

2

Sep-1

3

Sep-0

8

Jun-09

Mar-1

0

Des-1

0

Sep-1

1

Jun-12

Mar-1

3

Mar-0

8…

Des-0

8

Sep-0

9

Jun-10

Mar-1

1

Des-1

1

Sep-1

2

Jun-13

Non A as

Non A as

Non A as

Non A as

A asA as

A as

A as

ROA DER (rhs) Current Ra o (rhs)

88


Safe

SectorGrey Safe Grey Safe Grey Safe Grey

Share (%)

89

The Banking Industry andNon-bank Financial Ins tu ons

Chapter 4

91

4.1 THE BANKING SECTOR

4.1.1 An Assessment of Liquidity and Risk

Against a backdrop of moderating economic growth, widespread uncertainty concerning the

presiden al elec on as well as ght macroeconomic policy, the banking sector, which dominates the

nancial system of Indonesia, con nued to improve with rela vely maintained levels of resilience

and risk uch condi ons were re ected by preserved liquidity and mi gated liquidity risk, improved

intermedia on performance with funding risk and credit risk maintained at safe levels despite a slight

escala on as well as mi gated market risk uring the repor ng semester, with the support of a solid

capital base, banks successfully increased pro tability Greater pro tability, coupled with liquid asset

growth and slower credit growth, evidenced greater bank prudence in an cipa on of poten al risk

The results of stress tests revealed that the Capital Adequacy a o CA of the banking industry is

su cient to an cipate shocks as well as moun ng poten al credit and market risks

Chapter4

The Banking Industry andNon-bank Financial Ins tu ons

25% 140%

120%

100%

80%

60%

40%

20%

0%

20%

15%

10%

5%

2012 2013 2014

0%

Jan

Feb

Mar

Apr

May Jun Jul

Augt

Sep

Oct

Nov Dec Jan

Feb

Mar

Apr

May Jun Jul

Augt

Sep

Oct

Nov Dec Jan

Feb

Mar

Apr

May

Jun

M2 (%yoy) M1 (%yoy) AL/NCD (%) - RHS

850

900

950

1000

1050

1100

1150

0

100

200

300

400

500

600

700

800

12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6

2011 2012 2013 2014

Rp TRp T

Primary Reserves Secondary ReservesTer ery Reserves Liquid Assets

(%)

AL/NCD

Jun’12 Dec’12 Jun’12 Dec’12 Jun’14Jan’14 Feb’14 Mar’14 Apr’14 May’14

120

Liquid assets = Cash + placements at Bank Indonesia + Excess Reserve – Statutory Reserve RequirementNCD = 30% of demand deposits + 30% of savings accounts + 10% of term deposits

110

100

90

80

70

60

50

eposit erformance and isk4.1.2 An Assessment of Intermedia on and Risk

Sem II-2012 Sem I-2013 Sem II-2013 Sem I-2014

Credit (Rp T) 145.32 160.20 178.36 193.59Deposits (RP T) 171.32 197.92 196.45 233.23LDR (%) 84.82 80.94 90.79 83.01



Credit (Rp T) 1,131.80 1,252.62 1,389.86 1,445.75Deposits (RP T) 1,490.85 1,522.31 1,676.34 1,715.10LDR (%) 75.92 82.28 82.91 84.30

Credit (Rp T) 2,707.86 2,959.12 3,292.87 3,468.16Deposits (RP T) 3,225.20 3,374.42 3,663.97 3,834.50LDR (%) 83.96 87.69 89.87 90.45

BUKU 1

BUKU 2

BUKU 3

BUKU 4

Industri

Primary (%) 62.24 62.31 62.52 63.15 62.95 55.76 56.14Secondary (%) 19.45 19.47 19.54 19.73 19.67 27.88 28.07LDR (%) 4.90 3.87 3.42 2.38 1.71 0.76 0.48Foreign Exchange (%) 13.42 14.34 14.53 14.74 15.67 15.61 15.31Total GWM (%) 100.00 100.00 100.00 100.00 100.00 100.00 100.00

Statutory ReserveRequirement Sem I - 2011 Sem II - 2011 Sem I - 2012 Sem II - 2012 Sem I - 2013 Sem II - 2013 Sem I - 2014

Region 2012 2013 2014Java 76.10 76.75 76.18Sumatra 11.87 11.45 11.82Kalimantan 4.98 4.77 4.80Sulawesi 2.99 2.93 2.99Bali and Nusa Tenggara 2.56 2.60 2.65Papua and the Maluku Islands 1.50 1.49 1.57

13.63%

10.60%

7.50%

0%

1%

2%

3%

4%

5%

6%

7%

8%

6%

8%

10%

12%

14%

16%

18%

Semester I Semester II Semester I

BI Rate (RHS)Adjusted Deposit GrowthDeposit Growth

(150)

(100)

(50)

0

50

100

150

200

250

300

Rp T

Sem II -2013 Sem I -2014

Centra

l Gov

ernm

ent

Loca

l Gov

ernm

ent

Priva

te-In

dividua

lPr

ivate

-Fina

ncial

Insti

tutio

nPr

ivate

-Com

pany

Priva

te-O

ther

s

Non-R

esiden

t

Market Share inSemester I 2014 (%)

BUKU 1 28.76 20.81 17.54 14.67 17.84 6.08BUKU 2 22.22 15.06 13.39 12.03 11.97 23.89BUKU 3 21.16 17.71 12.55 16.92 16.04 25.30BUKU 4 19.87 14.62 15.06 12.44 12.66 44.73Industry 21.24 15.81 14.16 13.60 13.63 100.00

Sem I 2014Deposits Growth (%) Sem I 2012 Sem II 2012 Sem I 2013 Sem II 2013

Industry(Rp T)

Sem I2012

Sem II2012

Sem I2013

Sem II2013

Sem I2014

Demand Deposits 718.26 767.07 827.40 846.78 911.98

Saving 939.20 1,076.83 1,066.01 1,212.71 1,167.02

Term Deposits 1,298.37 1,381.30 1,481.02 1,604.48 1,755.50

Total Deposits 2,955.83 3,225.20 3,374.42 3,663.97 3,834.50

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Smt I 2010 Smt II 2010 Smt I 2011 Smt II 2011 Smt I 2012 Smt II 2012 Smt I 2013 Smt II 2013 Smt I 2014

Demand deposits Savings Term deposits <= 2 billion Term deposits > 2 billion

Sem I 2011

Sem II 2011

Sem I 2012

Sem II 2012

Sem I 2013

Sem II 2013

Sem I 2014

<= 2MBUKU 1 23,73 23,51 21,20 14,41 9,17 9,49 18,14

BUKU 2 7,04 15,62 10,37 6,23 9,19 10,55 9,58

BUKU 3 4,11 2,32 0,40 2,42 8,32 15,11 19,23

BUKU 4 1,96 6,11 9,05 4,73 1,82 7,40 16,41 INDUSTRI 5,27 8,07 7,48 5,17 6,09 10,71 15,99

> 2MBUKU 1 49,50 36,15 33,42 29,00 33,01 27,62 19,14

BUKU 2 20,98 27,28 27,71 7,07 13,48 11,71 14,15

BUKU 3 46,39 33,08 33,79 29,97 19,34 23,53 19,93

BUKU 4 9,22 5,87 10,00 8,85 19,79 18,87 25,06 INDUSTRI 24,15 20,87 23,66 16,10 18,61 19,20 19,83

DEPOSITOPertumbuhan Deposito (yoy,%)

9.5Percent

9.0

8.5

8.0

8.30

7.5

7.0

6.5

6.0

Dec-13

BUKU 1

Jan-14 Feb-14 Mar-14 Apr-14 May-14 Jun-14

BUKU 2 BUKU 3 BUKU 4 INDUSTRY

BUKU 1 BUKU 2 BUKU 3 BUKU 4 INDUSTRY

0.30min

0.20

0.10

0.00

-0.10

-0.20

-0.30Jan 14 Feb 14 Mar 14 Apr 14 May 14 June 14

Credit erformance

14.07%

Jul-13

Aug-1

3Se

p-13

Oct-1

3No

v-13

Dec-1

3Jan

-14Fe

b-14

Mar-14

Apr-1

4May-

14

Jun-14

17.20%

7.50%

10%

15%

20%

25%

6%

7%

8%

Semester II 2013 Semester I 2014

BI Rate Credit Growth (yoy. RHS) Adjusted Credit Growth (yoy. RHS)

40%

35

30

25

20

15

10

5

0

Rupiah

I-2013

15.81

24.80

17.20

Foreign Currency Total

II-2013 I-2014

40%

35

30

25

20

15

10

5

0

Working Capital Credit Investment Credit

I-2013

17.30

22.46

12.72

II-2013 I-2014

98

Region 2011 2012 2013 2014

BUKU 1 27.68 28.01 27.65 24.2 22.74 20.84 5.58BUKU 2 27.42 30.56 25.01 21.37 24.64 19.85 26.64BUKU 3 25.46 24.26 19.12 13.56 16.62 16.70 26.09BUKU 4 21.65 23.59 24.00 24.53 22.80 15.42 41.69Industry 24.44 25.75 23.08 20.64 21.60 17.20 100.00

Sem I-2014Credit Growth (%) Sem II-2011 Sem I-2012 Sem II-2012 Sem I-2013 Sem II-2013 Market Share on Semester I-2014 (%)

18.28

13.93

24.9028.61

17.54

25.44

6.18

14.31

6.97

19.53

17.20

05

10152025303540

I-2013 II-2013 I-2014

%

Trad

e

Othe

rsM

anuf

actu

ring

Agric

ultu

reCo

rpor

ate S

ervic

esSo

cial S

ervic

es

Min

ing

Elect

ricity

Tota

l

99

icro, mall and edium Enterprise E Credit

erformanceDe

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-1

1-1

2-1

2-1

2-1

2-1

2-1

2-1

2-1

2-1

2-1

2-1

2-1

2-1

3-1

3-1

3-1

3-1

3-1

3-1

3-1

3-1

3-1

3-1

3-1

3-1

4-1

4-1

4-1

4-1

4-1

4

11.56

19.73

0.0

5.0

10.0

15.0

20.0

25.0

0

100

200

300

400

500

600

700(Percent)Triliun Rp

Medium Enterprises Small Enterprises

Micro Enterprises MSME Credit Growth (yoy) (RHS)

MSME Credit Share (RHS)

-20%

0%

20%

40%

60%

80%

100%

120%

Jan

-12

Fe

b-1

2

Ma

r-1

2

Ap

r-1

2

Ma

y-1

2

Jun

-12

Jul-

12

Au

g-1

2

Se

p-1

2

Oct-

12

No

v-1

2

De

c-1

2

Jan

-13

Fe

b-1

3

Ma

r-1

3

Ap

r-1

3

Ma

y-1

3

Jun

-13

Jul-

13

Au

g-1

3

Se

p-1

3

Oct-

13

No

v-1

3

De

c-1

3

Jan

-14

Fe

b-1

4

Ma

r-1

4

Ap

r-1

4

Ma

y-1

4

Jun

-14

100

Credit isk

2.06

1.11

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

2008

2009

2010

2011

2012

2013

2014

%

Gross NPL Net NPL

Trad

e

Othe

rsM

anuf

actu

ring

Agric

ultu

reCo

rpor

ate S

ervic

esSo

cial S

ervic

es

Min

ing

Elect

ricity

Tota

l

2.92

2.002.46

4.24

1.29

2.132.48 2.49

1.06

1.66

0.00.51.01.52.02.53.03.54.04.5

%

Sem I 2013 Sem II 2013 Sem I 2014

0.0

0.5

1.0

1.5

2.0

2.5

3.0%

Sem I 2013 Sem II 2013 Sem I 2014

Working Capital Credit Investment Credit

101

Region Sem I - 2013 Sem II - 2013 Sem I - 2014

Jawa 2.05 1.60 1.67

Sumatera 2.58 2.43 2.87

Kalimantan 2.13 2.47 3.19

Sulawesi 2.60 2.62 3.27

Bali and

and the Islands

Nusa Tenggara 0.93 0.86 1.65

Papua Maluku 2.16 2.07 2.83

Gross NPL (%) Sem II-2011 Sem I-2012 Sem II-2012 Sem I-2013 Sem II-2013 Sem I-2014BUKU 1 2,36 2,38 2,26 2,15 2,41 2,68BUKU 2 2,11 2,14 1,92 2,02 2,02 2,22BUKU 3 2,32 2,3 1,99 2,11 1,94 2,50BUKU 4 2,08 2,09 1,89 1,62 1,43 1,63INDUSTRI 2,17 2,18 1,94 1,88 1,77 2,06

E Credit isk

7.5

13.86

6.7

3.88

-

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

18.00

Jan

-11

Feb

-11

Mar

-11

Apr

-11

May

-11

Jun

-11

Jul-

11A

ug-1

1Se

p-1

1O

ct-1

1N

ov-1

1D

ec-1

1Ja

n-1

2Fe

b-1

2M

ar-1

2A

pr-1

2M

ay-1

2Ju

n-1

2Ju

l-12

Aug

-12

Sep

-12

Oct

-12

Nov

-12

Dec

-12

Jan

-13

Feb

-13

Mar

-13

Apr

-13

May

-13

Jun

-13

Jul-

13A

us-1

3Se

p-1

3O

ct-1

3N

ov-1

3D

ec-1

3Ja

n-1

4Fe

b-1

4M

ar-1

4A

pr-1

4M

ay-1

4Ju

n-1

4

BI Rate MSME NPLLending Rate of MSME Credit

9.00%

8.00%

7.00%

6.00%

5.00%

4.00%

3.00%

2.00%

1.00%

0.00%

Jun’13

Jul’1

3

Sept’1

3Oct

’13Nov’1

3Dec

’13Ja

n’14Fe

b’14M

ar’14

Apr’14

May

’14Ju

n’14

Agst’1

3

Agriculture and Forestry

Mining and Quarrying

Fisheries

Manufacturing

Wholesale and Retail

4.1.3 Market Risk Assessment

Interest ate isk in the Banking Industry

Smt I 2012 Smt II 2012 Smt I 2013 Smt II 2013 Smt I 2014

BUKU 1 6.47 6.79 6.61 9.06 9.14BUKU 2 5.49 5.65 5.69 7.99 8.02BUKU 3 5.59 5.85 5.90 8.54 8.87BUKU 4 4.92 5.05 5.08 7.02 7.76INDUSTRY 5.39 5.58 5.60 7.92 8.30





1-month Rupiah Term Deposit Rate

Term Deposit Rate

Savings Deposit Rate

E change ate isk

Smt I 2010 Smt II 2010 Smt I 2011 Smt II 2011 Smt I 2012 Smt II 2012 Smt I 2013 Smt II 2013 Smt I 2014BUKU 1 14.66 14.79 14.46 14.76 14.72 14.11 14.00 14.08 14.72BUKU 2 12.38 12.16 12.33 11.73 11.16 11.14 10.96 12.09 12.69BUKU 3 14.64 13.46 13.16 12.71 12.26 11.77 11.52 12.56 13.22BUKU 4 12.78 12.45 11.10 11.82 11.53 11.23 11.28 11.70 12.05INDUSTRY 13.18 12.75 12.24 12.16 11.79 11.49 11.41 12.13 12.63



Interest Rate of Working Capital Credit (%)

Interest Rate of Investment Credit (%)

Interest Rate of Consumption Credit (%)

(1.0)

(0.5)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

BUKU 1 BUKU 2 BUKU 3 BUKU 4

Rp T

isk of ower Tradeable Government ecuri es BN

rices

Period < 12 bulan > 12 bulanJun-12 -1.13 19.29Dec-12 -0.56 19.17Jun-13 0.97 80.09Dec-13 2.77 86.54Jun-14 4.92 83.72

(in trillions of rupiah)

0%

1%

2%

3%

4%

5%

6%

7%

Jun-10 Dec-10 Jun-11 Dec-11 Jun-12 Dec-12 Jun-13 Dec-13 Jun-14

BUKU 1 BUKU 2 BUKU 3 BUKU 4 Industry

4.1.4 Assessment of Pro tability E ciency and Capital

ro tability

BUKU 4 170.82 169.77 148.86 180.23 Trading 1.93 1.88 0.80 1.97 Trading 1.13 1.10 0.54 1.09 AFS 114.12 114.48 108.10 123.26 AFS 66.80 67.43 72.62 68.39 HTM 54.77 53.41 39.95 55.00 HTM 32.06 31.46 26.84 30.51




Industri 246.82 266.20 261.27 308.19 Trading 21.44 26.52 15.88 28.93 Trading 8.69 9.96 6.08 9.39 AFS 157.03 164.61 176.23 193.98 AFS 63.62 61.84 67.45 62.94 HTM 68.35 75.07 69.16 85.28 HTM 27.69 28.20 26.47 27.67

BUKU 1

BUKU 2

BUKU 3

BUKU 4

INDUSTRI

Share of Total (%)

Dec-12 Jun-13 Dec-13 Jun-14

Trading 1.13 1.10 0.54 1.09 AFS 66.80 67.43 72.62 68.39 HTM 32.06 31.46 26.84 30.51

Trading 12.05 15.87 9.69 22.73 AFS 71.86 67.80 76.05 60.18 HTM 16.09 16.33 14.25 17.09

Trading 37.97 32.00 16.97 21.21 AFS 44.61 43.72 50.47 53.31 HTM 17.42 24.28 32.56 25.48

Trading 13.23 7.03 4.55 4.62 AFS 51.22 54.31 43.20 35.94 HTM 35.55 38.66 52.25 59.45

Trading 8.69 9.96 6.08 9.39 AFS 63.62 61.84 67.45 62.94 HTM 27.69 28.20 26.47 27.67

Nominal (Rp T)

Dec-12 Jun-13 Dec-13 Jun-14

BUKU 4 170.82 169.77 148.86 180.23 Trading 1.93 1.88 0.80 1.97 AFS 114.12 114.48 108.10 123.26 HTM 54.77 53.41 39.95 55.00




Industri 246.82 266.20 261.27 308.19 Trading 21.44 26.52 15.88 28.93 AFS 157.03 164.61 176.23 193.98 HTM 68.35 75.07 69.16 85.28

Sem I-2013 Sem II-2013 Sem I-2014 Sem I-2013 Sem II-2013 Sem I-2014 Sem I-2013 Sem II-2013 Sem I-2014 Sem I-2013 Sem II-2013 Sem I-2014

BUKU 1 2.50 1.00 2.5 0.10 0.30 0.01 2.60 1.30 2.49 2.10 0.60 1.97

BUKU 2 13.40 15.90 18.01 1.10 0.70 1.92 14.50 16.50 16.09 11.20 12.10 12.71

BUKU 3 12.10 12.30 13.24 0.30 0.30 0.13 12.40 12.60 13.38 9.50 9.60 10.68

BUKU 4 34.10 40.20 40.46 0.80 2.00 1.06 34.90 42.20 41.52 28.30 33.30 33.07

Industry 62.00 69.50 74.21 2.30 3.30 0.74 64.40 72.70 73.47 51.10 55.60 58.43

Opera onal P/L Non-Opera onal P/L P/l before Tax P/L a er Tax

2014I II I II I II I

88.5 98.9 94.7 107.2 106.5 138.8 134.53.5 4.5 2.9 1.3 2.3 1.2 1.67.5 6.0 6.2 5.5 6.0 8.4 8.7

57.5 73.9 66.8 79.4 77.2 100.1 96.229.4 37.7 33.6 24.8 36.4 30.5 40.1

2.8 4.2 3.2 0.2 1.1 1.0 1.67.1 7.1 8.9 5.5 12.6 20.8 15.58.8 8.0 9.4 10.4 10.6 13.0 13.3

10.8 -1.7 5.3 5.9 5.5 9.4 6.4

Income Account2011 2012 2013

2014I II I II I

91.7 92.0 98.7 116.4 136.11.1 1.5 1.7 2.1 2.2

50.5 50.1 52.9 63.5 79.62.6 2.5 2.8 3.1 3.51.2 1.2 1.2 1.3 1.8

35.9 36.4 39.9 46.0 48.7109.1 109.3 124.9 126.2 138.9

4.5 1.2 2.0 1.0 1.715.2 10.8 21.7 27.0 27.2

3.6 4.0 4.3 4.5 4.824.0 20.3 27.0 14.7 27.429.6 33.4 35.0 36.8 39.616.2 20.0 17.1 20.3 19.4

4.2 13.0 4.4 16.1 6.8

Cost Account2012 2013

108

NIM Sem I-2012 Sem II-2012 Sem I-2013 Sem II-2013 Sem I-2014BUKU 1 5.91 6.15 6.11 5.85 5.09 BUKU 2 4.44 4.59 4.64 4.02 3.18 BUKU 3 5.65 5.64 5.21 4.87 3.72 BUKU 4 5.68 5.83 5.91 5.28 5.10 INDUSTRY 5.38 5.49 5.43 4.89 4.22

2.90

2.95

3.003.02

3.05

3.10

3.15

3.20

1.0

1.5

2.0

2.5

3.0

3.5

4.0

I-2011 II-2011 I-2012 II-2012 I-2013 II-2013 I-2014

BUKU 1 BUKU 2 BUKU 3 BUKU 4 INDUSTRY (RHS)

Percent Percent

I-2011 II-2011 I-2012 II-2012 I-2013 II-2013 I-2014


Percent Percent81

80

79

78

77

75.45 76

7574

73

72

71

70

90

85

80

75

70

65

60

109

Capital

I-2011 II-2011 I-2012 II-2012 I-2013 II-2013 I-2014


58.30

65

70Percent

60

55

50

45

40

35

I-2011

Percent

II-2011 I-2012 II-2012 I-2013 II-2013 I-2014

14.41

22

20

18

16

14

12

10

BUKU 1 BUKU 2 BUKU 3 BUKU 4 INDUSTRY

110

4.1.5 Stress Tes ng the Banking Industry

Capital esilience to Credit isk

19.48

15

16

17

18

19

20

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

I-2011 II -2011 I-2012 II -2012 I-2013 II -2013 I-2014

PercentRp T

Capital Risk-Weighted Assets CAR (RHS)

19.48

17.89

12

14

16

18

20

22

24

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

Percent

CAR Tier 1

Industry

Lowest CARHighest CAR Average CAR CAR

111

Capital esilience to arket isk

19.40% 19.33%

26.04%

16.54% 17.10%17.19% 14.11%

20.67%

10.63%

13.98

0%

5%

10%

15%

20%

25%

30%

Industry BUKU 1 BUKU 2 BUKU 3 BUKU 4

Initial CAR NPL of 5% (NPL at individual banks increases 2.32x)NPL of 10% (NPL at individual banks increases 4.63x)NPL of 15% (NPL at individual banks increases 6.95x)

NPL of 7.5% (NPL at individual banks increases 3.48x)NPL of 12.5% (NPL at individual banks increases 5.79x)

-40

-121

- 109

-- 122

-30

-222

-522

- 537

- 591

-312

-700 -600 -500 -400 -300 -200 -100 0

Industry

BUKU 1

BUKU 2

BUKU 3

BUKU 4

NPL of 15% (NPL at individual banks increases 6.95x) NPL of 12.5% (NPL at individual banks increases 5.79x)NPL of 10% (NPL at individual banks increases 4.63x) NPL of 7.5% (NPL at individual banks increases 3.48x)NPL of 5% (NPL at individual banks increases 2.32x)

tress Tes ng an Increase in Interest ates

tress Tes ng upiah eprecia on

19.40% 19.33%

26.04%

16.54% 17.10%18.56% 17.60%

25.22%

15.36%16.54%

0%

5%

10%

15%

20%

25%

30%

Industri BUKU 1 BUKU 2 BUKU 3 BUKU 4

Initial CAR Increase of 1% Increase of 2%Increase of 3% Increase of 4% Increase of 5%

-16

-34

-16

-23

-11

-84

-172

-82

-117

-56

-200 -180 -160 -140 -120 -100 -80 -60 -40 -20 0

Industry

BUKU 1

BUKU 2

BUKU 3

BUKU 4

Increase of 5% Increase of 4% Increase of 3%Increase of 2% Increase of 1%

19.40% 19.24%

26.03%

16.52% 17.11%

19.41% 19.31%

26.04%

16.50% 17.14%

0%

5%

10%

15%

20%

25%

30%


Initial CAR Depreciation of 10% Depreciation of 20%Depreciation of 30% Depreciation of 40% Depreciation of 50%

tress Tes ng ower BN rices

0

8

0

0

0

1

7

0

-3

3

-4 -2 0 2 4 6 8 10

Industry

BUKU 1

BUKU 2

BUKU 3

BUKU 4

Depreciation of 50% Depreciation of 40% Depreciation of 30%Depreciation of 20% Depreciation of 10%

19.40% 19.33%

26.04%

16.54% 17.10%17.93%19.00%

24.70%

15.46% 15.17%

0%

5%

10%

15%

20%

25%

30%


Initial CAR 5% decline in SBN price 10% decline in SBN price15% decline in SBN price 20% decline in SBN price 25% decline in SBN price

-29

-6

-27

-21

-39

-147

-32

-133

-107

-193

-250 -200 -150 -100 -50 0

Industry

BUKU 1

BUKU 2

BUKU 3

BUKU 4

25% decline in SBN price 20% decline in SBN price 15% decline in SBN price10% decline in SBN price 5% decline in SBN price

4.2 NON BANK FINANCIAL INSTITUTIONS NBFI

4.2.1 Finance Companies (FC)

(Rp. T)

250 28

23

18

13

8

3

(2)

200

150

10077

165

102

179

105 106

192

210

117

223

116

237

50

Dec’11

Leasing

Jun’12 Dec’12 Jun’13 Dec’13 Jun’14

-

(Rp. T)

Consumer Financing Factoring

4 45 5

8 8

(Rp. T)

450

350

400

250

300

200

150

100

245

291

50

Dec’11

Assets

Jun’12 Dec’12 Jun’13 Dec’13 Jun’14-

Financing

284

322302

342321

359348

401

361

4133,00%

2,50%

2,00%

1,50%

1,99%

2,29%

2,00%

2,16%

2,03%

2,48%

2,29%

1,85%1,62%

1,33%1,47%

1,00%

0,50%

0,00%

Des’11

Mar

’12

Jun’

12

Sep’

12

Des’12

Mar

’13

Jun’

13

Sep’

13

Des’13

Mar

’14

Jun’

14

(Rp, T)

Dec'11 Jun'12

Loans

160

140

120

100

80

60

40

20

-External

LoansEquitas

Dec'12 Jun'13 Dec'13 Jun'14

45.00%

40.00%

35.00%

30.00%

25.00%

20.00%

15.00%

10.00%

5.00%

0.00%Mar’13

37.31%

36.22%

26.47%

39.06%

37.02%

23.92%

38.10%

37.84%

24.05%

34.12%

36.36%

29.52%

32.16%

34.61%

33.23%

31.48%

32.59%

35.93%

Jun’13 Sep’13 Dec’13 Mar’14 Jun’14

0%-10%

10.01%-12%

>12.01%

4.2.2 Insurers1

Licensed

PT Asuransi Jiwa Indosurya Sukses 11 September 2013

PT Asuransi Agrapana Aksata Januari 2013

PT Central Asia Financial March 2013

Company Name

25.00% 82.00%

81.00%

80.00%

79.00%

78.00%

77.00%

76.00%

75.00%

20.00%

15.00%

10.00%

5.00%

0.00%

ROA

Mar’13

4.96%

20.00%

78.34%

Jun’13

5.08%

19.83%

77.74%

Sep’13

5.16%

19.79%

77.40%

Des’13

5.07%

19.22%

77.98%

Mar’14

4.47%

16.78%

79.56%

Jun’14

4.17%

15.66%

81.30%

ROE

BOPO

25%

16%15%

44%

Life insurance General Insurance and Reinsurance

ocial Insurance Programmesand Social Insurance forPrivate Sector Workers

Insurers of Civil Servants,Army Personnel and the Police

481.75

569.32

652.9

419.7

497.03521.97

87.12% 87.30%

79.95%

50%

55%

60%

65%

70%

75%

80%

85%

90%

0

100

200

300

400

500

600

700

2011 2012 2013

Rp Trillion

Assets Investments

87.79

109.62121.67

153.13

178.07

198.53

57.33%

61.56% 61.29%

25%

30%

35%

40%

45%

50%

55%

60%

65%

0

20

40

60

80

100

120

140

160

180

200

2011 2012 2013*

Rp Trillion

Gross Claims Gross Premiums

Life Insurance

Total

State-Owned

PrivateNa onal

JointVenture

Insurance Pro le Total

Loss Insurance

Reinsurance

11 93 37 141

Social Insurance Programmes and Social Insurance for Private Sector Workers

Insurers of Civil Servants, Army Personnel and the Police

1 29 19 493 62 18 832 2 4

2

3

2

3

Thousand Rp800

2008 2009 2010 2011 2012 2013*

%25

25

15

10

5

0

700

600

500

400

300

200

100

0

Density Growth

19.6817.51

22.37

13.74

0.27

11.41

118

Box 4.1. Impact of Economic Condi ons on MSME Credit Risk

Test Granger Causality Signi cant at Lag

GDP NMSME PL 2**,3*,4*,5*

1.60***

− 1 0.91***

− 1 -0.20**

− 2 0.24*

− 1 0.03**

0.84

2.22

Determinantsof NPL

MSME Credit Risk

119

10.0

9.0

8.0

7.0

6.0

5.0

4.0

3.0

2.0

MSME NPL (%) on-MSME NPL (%) GDP (% yoy)

1.0

Mar

-03

Sept

-03

Mar

-04

Sept

-04

Mar

-05

Sept

-05

Mar

-06

Sep-

06M

ar-0

7Se

pt-0

7

Mar

-08

Sept

-08

Mar

-09

Sept

-09

Mar

-10

Sept

-10

Mar

-11

Sept

-11

Mar

-12

Sept

-12

Mar

-13

Sept

-13

Mar

-14

Box 4.2 The Role of Educa on and Provision of Informa on to derail the Upward NPL Trend

Financial Iden ty Number

Financial Educa on

Informa on System for Farmers and Fishermen

(SIPN)

123

Chapter 5. Financial System Infrastructure

Financial System Infrastructure

Chapter 5

124


125


5.1 PAYMENT SYSTEM PERFORMANCE

5.1.1 The Payment System Operated by Bank Indonesia

Financial System InfrastructureChapter5


5.1.2 The Industry-Operated Payment System

5.2 PAYMENT SYSTEM TRANSACTION PERFORMANCE


VALUE VOLUME

S1 2013 S1 S014 (%)

S1 2013 S1 2014 (%)

BI-RTGS 40,188.74 47,968.18 19.36 8.75 8.64 -1.26

BI-SSSS 10,238.73 13,570.49 32.54 0.07 0.07 9.57

1,153.52 1,378.53 19.51 50.29 51.97 3.34

1,907.39 2,235.84 17.22 1,766.93 2,067.12 16.99

a)ATM ATM/D

1,800.72 2,115.34 17.47 1,650.71 1,943.72 17.75

106.67 120.50 12.97 116.23 123.40 6.17

1.27 1.58 24.41 64.99 82.17 26.43


(TRILLIONS OF RP) (TRILLIONS OF RP) (MILLIONS OF TRANSACTIONS)


5.3 PAYMENT SYSTEM INDICATORS

5.3.1 Account Balance

1

(Trillion of Rp)

TOR (LHS)

240270

260

250

240

230

220

210

200

190

220

200

180

160

140

120

100

80

60

02-0

1-20

1202

-02-

2012

05-0

3-20

1205

-04-

2012

08-0

5-20

1211

-06-

2012

11-0

7-20

1210

-08-

2012

17-0

9-20

1217

-10-

2012

21-1

1-20

1221

-12-

2012

29-0

1-20

1228

-02-

2012

03-0

4-20

1203

-05-

2012

05-0

6-20

1208

-07-

2012

12-0

8-20

1211

-09-

2012

11-1

0-20

1215

-11-

2012

17-1

2-20

1222

-01-

2012

24-0

2-20

1226

-03-

2012

30-0

4-20

1205

-06-

2012

TOR Trend (LHS)Opening Balance (RHS)


0,00

0,50

1,00

1,50

2,00

2,50

BUKU 1 BUKU 2 BUKU 3 BUKU 4 Industri

2012 Sem I 2012 Sem II 2013 Sem I 2013 Sem II 2014 Sem I

2 2012 Sem I 2012 Sem II 2013 Sem I 2013 Sem II 2014 Sem I

0.00

0.50

1.00

1.50

2.00

2.50


Millions of Rp

2012 Sem I 2012 Sem II 2013 Sem I 2013 Sem II 2014 Sem I

0

4000

3000

2000

1000



5 5.4 PAYMENT SYSTEM RISK AND MITIGATION EFFORTS

3

5.4.2 Liquidity Risk4

131


Box 5.1

132


133

Ar cle1. Banking Model of Bank Indonesia - BAMBI

2. LDR-linked RR Policy to Support Countercyclicality in the Op misa on of Intermedia on and Minimisa on of Liquidity Risk

135

1. INTRODUCTION

4

2. MODEL STRUCTURE AND ESTIMATION RESULTS

2.1 Model Structure

Banking Model of Bank Indonesia - BAMBI1

Ar cle 1

Ndari Sur aningsih2 dan Tevy Chawwa3

a. Interac on between the Macroeconomic and

Banking Sector

138

b. Interac on between Variables in the Banking Sector

2.2 METHODOLOGY

2.3 Es ma on Results

5 The

3. MODEL PERFORMANCE EVALUATIONS AND

SIMULATIONS ANALYSIS

4. MODEL LIMITATIONS

7

143

5. CONCLUSION REFERENCES

145

Article 2. KLDR-linked RR Policy to Support Countercyclicality in the Optimisationof Intermediation and Minimisation of Liquidity Risk

1. INTRODUCTION

In Indonesia, bank credit remains a key factor in terms

of funding corporate investment and working capital. The

banking system dominates 75-80% of assets in the financial

system, which leads authorities to ensure that bank credit

extension is constantly optimal in support of the economy.

From a macroprudential standpoint, the ratio of credit to

deposits, or the Loan-to-Deposit ratio (LDR), illustrates

liquidity conditions in the banking sector. In general, deposits

are short term and must be available for withdrawal at any

time by depositors. In contrast, credit is relatively long term,

nearly always longer term than deposits, requiring time to be

repaid. As more credit is disbursed in comparison to deposits,

liquidity risk can manifest when depositors withdraw their

funds.

2. ECONOMIC RATIONALE OF MACROPRUDENTIAL

POLICY

2.1. Economic Rationale

Bank management will always strive to maximise profit

in order to maximise shareholder value as the overarching

goal of providing value added to the shareholders and

minimisingthe possibility of losing managerial position

in the operating activity of the bank. On the other hand,

bank supervisors are in a position to assure operational

sustainability of the banks that fall under their supervisory

activities . In general, economic and financial policy

can be divided into four main areas: microprudential,

macroprudential, monetary and macroeconomic policy (refer

to Table 1).

In terms of microprudential, supervisors of financial

institutions tend to place safety factors higher in order to

ensure that a bank is adequately resilient in the face of future

financial disruption. That explains why bank management

tends to emphasise safety factors, which can be viewed as

imprudent behaviour or worse bordering on fraud. The main

aim of microprudential policy is to optimise operational

efficiency at a bank and concomitantly ensure that the bank

maintains its risk-taking capacity, supported by sound risk

management and good corporate governance. Typically, all

information concerning the operational soundness of a bank

is contained within the bank soundness rating report.

LDR-linked RR Policy to Support Countercyclicality in the Optimisation of Intermediation and

Minimisation of Liquidity Risk1

Article 2

Dadang Muljawan2, Cicilia Anggadewi Harun3, Aditya Anta Taruna4

1) The opinions expressed in this paper are those of the authors and not those of Bank Indonesia.2) Senior Economic Researcher, Macroprudential Policy Department, Bank Indonesia; Email:

[email protected]) Senior Economic Researcher, Macroprudential Policy Department, Bank Indonesia; Email:

[email protected]) Economic Researcher, Macroprudential Policy Department, Bank Indonesia; Email: aditya_at@

bi.go.id

146


Concerning macroprudential pol icy, deeper

consideration is required over the longer term.

Macroprudential policy not only deals with the operational

sustainability of a bank but also systemic stability that

correlates with other variables. Countercyclical policy at

times can be considered not to support bank management

efficiency because banks are required to maintain larger

reserves when economic conditions are actually favourable.

A similar perception is also found in terms of liquidity risk

management, where banks are encouraged to maintain a

larger buffer when profits from loans are higher.

Monetary policy aims to achieve price stability through

monetary operations and implement the function of Lender

of Last Resort (LOLR) in order to ensure an adequate

level of liquidity, thereby enabling effective monetary

operations. Macroeconomic policy, in general, is instituted

by the government to create aconduciveenvironment to the

production of goods and provision of services. Such policy

encompasses policy in the fiscal sector, minimum wages

and various other policies related to real sector activity. The

differences between macroeconomic and macroprudential

policy can be observed from two main perspectives, namely

the countercyclicality impact produced and sector-based

policy. The core of countercyclicality in financial policy is to

compile an appropriate incentive scheme for market players

in order that they might prepare themselves to confront

future uncertainty and to encourage them to contribute

to a national economic recovery. Sector-based policy is

policymaking that refers to the different dynamics in each

sector, which might require differing policy incentives, for

example variable LTV policy (loan-to-value) in each target

sector. In terms of monetary policy, sector-based policy can

be considered less effective as interest rate and exchange rate

policy is aggregate in nature and aims to impact the system

as a whole. Meanwhile, for banking supervisors, the core of

the policy taken is to ensure operational continuity at the

institutional level.

2.2. LDR-linked RR Policy

Originally, the reserve requirement (RR) was a monetary

instrument that aimed to control bank credit. The reserve

requirement functioned to provide bank liquidity in order

to reduce credit allocation. Notwithstanding, as sources of

deposits became more diverse, the reserve requirement

became less effective at reducing the banks’ ability to extend

credit. Despite losing power in terms of reducing credit

allocation, the reserve requirement remained a powerful

instrument for the authorities becauseits capability to impose

Area Target Remarks

Microprudential Risk absorption capacity and efficiency Optimise banking sector operations and risk absorption capacity, supported

by sound risk management practise and good corporate governance. Such

information is usually available from the bank soundness rating system.

Macroprudential Financial system stability Policy that encompasses microprudential and macroprudential policy.

Monetary Price Stability Optimise monetary instruments in order to achieve price stability through

interest rate and exchange rate policy..

Macroeconomic Growth and Unemployment Optimise infrastructure in order to achieve robust economic growth

through fiscal management, including tax policy, sectoral growth,

minimum wages, etc.

Article Table 2.1. Description of Regulatory Regimes

147


penalties that directly impact bank liquidity and can also

provide clear signals to the banking industry in support of

economic growth. Consequently, the RR was subsequently

supplemented with additional features aimed at controlling

bank credit growth. In this case, bank behaviour in terms

of extending credit is reflected by the loan-to-deposit ratio

(LDR). The correlation between the RR and LDR is illustrated

in Figure 1.

Lower Limit

In general, LDR is used to illustratesthe level of

efficiency at a bank in terms of the intermediation function.

In a traditional economic system, a low LDR level reflects

a low level of intermediation, implying that the economy

requires a capital injection to bolster activity and economic

growth. Hitherto, however, there is no instrument to maintain

intermediation at a level desired by the authority. During a

contractionary economic phase, the level of return of credit

might be lower than the level of return offered by financial

assets. Therefore, enforcing a high LDR is perceived as

inefficient by the banks and by the supervisory authority too

because the regulation encourages banks to extend more

credit that is, in fact, less profitable. From a macroprudential

standpoint, however, such regulations could save the

economic system from a deeper contraction, into a recession,

and provide an opportunity for economic recovery. The idea

behind applying a higher reserve requirement is to provide a

disincentive to banks with a low loan-to-deposit ratio5.

(E.1)

As shown in Equation 1, banks with a loan-to-deposit

ratio below the threshold, ( ), will be required to place

loanable funds at the central bank in the event they cannot

extend their funds to economic sectors. P0 represents primary

reserves and P1 is the increase in the reserve requirement

due to a bank’s inability to meet the minimum LDR (lower

limit). This can be considered an indirect penalty because

the bank will experience a higher cost of capital whilst their

funds remain idle at the monetary authority.

Upper limit

A high LDR (surpassing the upper limit) indicates

excessive lending, where credit disbursed exceeds the funds

accumulated from the customers. Such conditions imply

that a portion of the bank’s capital is also utilised in the

extension of credit. Excessive lending is undesirable to the

supervisory authority because it can undermine bank liquidity

conditions and bank infrastructure development. During an

5) Historically, the lowest level of LDR in Indonesia was 60% during the recovery period after the 1998 crisis. At that time, banks were unwilling to extend credit due to the perception of high credit risk.

Artikel 2. Kebijakan GWM-LDR Untuk Mendukung Countercyclicality…

𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 = 𝜌𝜌𝜌𝜌0 + 𝜌𝜌𝜌𝜌1 𝑑𝑑𝑑𝑑𝑙𝑙𝑙𝑙 , when 𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑 < 𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑 (P.1)

Sebagaimana ditunjukkan pada persamaan (P.1), bank yang memiliki LDR dibawah threshold 𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑akan

diwajibkan untuk menyimpan loanable fund yang dimiliki di otoritas moneter jika mereka tidak dapat menyalurkan dananya ke dalam sektor ekonomi. 𝜌𝜌𝜌𝜌0merepresentasikanprimary RR dan 𝜌𝜌𝜌𝜌1merepresentasikan kenaikan RR karena bank tidak dapat memenuhi minimum LDR (batas bawah). Ini dapat dianggap sebagai bentuk indirect penaltykarena bank akan mengalami tingkat biaya capital yang lebih tinggi ketika dana mereka ditahan idle di otoritas meneter. Batas atas (Upper limit) Tingginya LDR (diatasbatas atas) menggambarkan excessive lendingdimana kredit yang diberikan melampaui dana yang dikumpulkan dari nasabah. Hal ini berarti sebagian modal yang dimiliki bank juga digunakan untuk mendukung pemberian kredit. Pemberian kredit yang berlebihan juga tidak diinginkan oleh otoritas pengawasan karena hal itu dapat berakibat buruk pada kondisi likuiditas bank dan proses pembangunan infrastruktur bank. Dalam kondisi economic boom, bank mungkin saja memaksimalkan pemberian kreditnya untuk mengoptimalkan keuntungan yang ingin dicapai. Dalam kondisi demikian, bank cenderung untuk meminimalkan likuiditas (termasuk instrumen likuiditas) karena tingkat return yang didapat dari kredit lebih tinggi. Pengawas bank akan menetapkan threshold tertentu sebagai posisi likuiditas minimum untuk memastikan bahwa bank selalu berada dalam kondisi yang sehat dalam memenuhi kewajiban jangka pendeknya. Regulasi seperti ini akan dianggap tidak efisien oleh manajemen bank karena berusaha untuk menekan ekspansi kredit. Hal ini menunjukkan bahwa, pada area tertentu, otoritas pengawasan dan manajemen bank selalu berada pada natural conflict guna mengoptimalkan pencapaian tujuan masing-masing.Otoritasmakroprudensial bahkan dapat berada pada posisi yang lebih berhati-hati lagi mengingat mereka tidak hanya memperhatikan masalah kesinambungan operasi bank sebagai institusi, namun juga kestabilan sistem keuangan yang dapat dirusak oleh gagalnya satu bank. Oleh karena itu, untuk mengisi kekosongan tujuan kebijakan, instrumen kebijakan makroprudensial diterapkan.

Gambar3 a) Probability of liquidity problem6 b) Total return of the bank

6Probability of Liquidity Problem (probabilitas masalah likuiditas) diasumsikan terdistribusi secara Poisson distribusi untuk menggambarkan behavioraldi pasar keuangan dan dampak terhadap bank akibat diskon harga yang berlaku.

144







144

Gambar1

Kerangka LDR-linked Reserve Requirement

RR

LDR

Primary RR

Optimal LDR

Theoretical FrameworkRR

LDR

Primary RR

Lowerlimit

Upperlimit

Framework Design

Article Graph 2.1. LDR-linked Reserve Requirement Framework

148


economic boom, banks may maximise credit allocation in

order to optimise profit. Under such conditions, banks tend

to minimise liquidity (including liquidity instruments) because

the level of return on credit is higher. Bank supervisors will

determine a specific threshold as the minimum liquidity

position to ensure that banks remain sound in terms of

meeting their short-term liabilities. Regulations such as this

are considered inefficient by bank management because

they strive to supress credit expansion. This indicates

that, in certain areas, the supervisory authority and bank

management are in a constant state of natural conflict when

trying to achieve their respective objectives. In fact, the

macroprudential authority can adopt an even more prudential

position considering it must pay due regard not only to

problems of bank operational sustainability as an institution

but also financial system stability, which could be disrupted

by the default of one bank. Consequently, macroprudential

policy instruments are used to fill the policy gaps.

Article Graph 2.2.a shows the potential probability of

liquidity problems faced by a bank when the level of liquidity

drops. Banks, under normal conditions, will have a number

of options to meet their liquidity requirement, namely by

internally determining liquidity reserves, optimising credit

lines through the interbank money market and provisioning

secondary reserves consisting of liquid assets ready to sell

directly or through repurchase agreements (repo). Under

liquidity crisis conditions, where all of the bank’s options are

closed, the bank can utilise the lender of last resort (LOLR)

facility. However, the costs involved are higher, making LOLR

the most inefficient option. Figure 3.b illustrates how total

returns of a bank can become negative when the cost of

liquidity management (cost of liquidity) exceeds operational

revenue (I). Under extreme conditions, the cost of liquidity

can even surpass the net worth of the bank itself (I+K),

illustrating how an acute illiquid position can make a bank

solvent but illiquid and therefore insolvent. In order to

minimise that possibility, the banking authority sets a specific

threshold considered sufficient to maintain a secure liquidity

position. The following is a balance sheet equilibrium formula

to determine a capital adequacy ratio that supports a 92%

level of LDR:

l + liq + RR = d + k

Dividing both sides by d produces:

(E.2)

6) The probability of liquidity problems is assumed as a Poisson distribution to illustrate financial market behaviour in money market and the impact on a bank because of price discounts.


Gambar3.amenunjukkan potensi probability of liquidity problem(probabilitas masalah likuiditas) yang akan dihadapi bank ketika tingkat likuiditas menurun. Bank, dalam kondisi normal, akan memiliki beberapa pilihan dalam memenuhi kebutuhan likuiditasnya yaitu dengan menetapkan cadangan likuiditas secara internal, mengoptimalkan credit line melalui pasar uang antar bank, membentuk secondary reserve yang terdiri dari liquid assetsyang siap untuk dijual secara langsung maupun melalui mekanisme repo.Dalam kondisi darurat likuiditas, dimana seluruh pilihan bank telah tertutup, bank bisa memanfaatkan fasilitas LOLR.Namun demikian, biaya yang dibutuhkan akan semakin tinggi sehingga menempatkan fasilitas LOLR sebagai opsi yang paling tidak efisien untuk didapat. Gambar3.bmenunjukkan bagaimana total returnsdari dari bank menjadi negatif ketika biaya yang ditimbulkan dari manajemen likuiditas (cost of liquidity) melebihi operational revenue (I). Dalam kondisi yang ekstrim,cost of liquiditymungkin saja melebihi networth bank (I + K) yang menggambarkan bagaimana posisi illikuid yang akut dapat membuat bank yang solvent namun tidak likuid menjadi tidak solvent. Untuk meminimalkan kemungkinan tersebut, otoritas perbankan menentukan threshold tertentu yang dipercaya dapat menjaga posisi likuiditasnya secara aman. Berikut adalah formulasi kesetimbangan balance sheet untuk mendapatkan angka Capital Adequacy Ratio (CAR)yang dapat menunjang 92% LDR: 𝑙𝑙𝑙𝑙 + 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 + 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 = 𝑑𝑑𝑑𝑑 + 𝑘𝑘𝑘𝑘 Membagi kedua sisi dengan d, kita mendapatkan 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑 = 1 + 𝑘𝑘𝑘𝑘𝑑𝑑𝑑𝑑 − 𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑 − 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑑𝑑𝑑𝑑 , dimana 𝑑𝑑𝑑𝑑 = 𝐴𝐴𝐴𝐴 − 𝑘𝑘𝑘𝑘 (P.2)

Menentukan posisi likuiditas aman sebesar 8%7dengan RR sebessar 8%, didapatkan nilai berikut:

0.13 = 𝑘𝑘𝑘𝑘𝐴𝐴𝐴𝐴−𝑘𝑘𝑘𝑘 atau 𝑘𝑘𝑘𝑘𝐴𝐴𝐴𝐴 = 0.115

Dengan rasio aktiva tertimbang menurut risikosebesar 80%, nilai optimum CAR yang dapat mendukung 92% percent LDR dengan pemenuhan 8% RR and 8% likuiditas adalah 14.38%.

Gambar4 Probability of liquidity problem8

7Analisa base line menunjukkan bahwa likuiditas optimal berarti bank memiliki kemampuan menyerap shock dengan mempertahan kan efisiensi berada di angka 8% (threshold oleh rasio AL/DPK). 8Simulasi di Gambar 3 dilakukan menggunakan (P.2)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

0.00

0.10

0.20

0.30

0.40

0.14 0.19 0.23 0.27 0.31 0.34

liq/d

RR/d

k/d

l/d (RHS)

145

a) Probability of liquidity problem6 b) Total return of the bankArticle Graph 2.2.







144







144

149


Determining a safe liquidity position of 8% with a RR of 8%

produces the following value:

With a risk-weighted assets ratio of 80%, the optimal

value of CAR that can support a 92% LDR and meet an 8% RR

and an 8% liquidity ratio is 14.38%.

7) Base line analysis shows that optimal liquidity means a bank is able to absorb a shock while maintaining efficiency at 8% (threshold of LA/D).

8) The simulation in Article Graph 2.3. is conducted using (E.2).

the bank reaches a critical point. The terms for provisioning

secondary reserves are presented in Equation 3.

(E.3)

The discussion above shows that banks will operate

within a prudent corridor, which can accommodate concerns

surrounding the intermediation process and sound bank

liquidity management.

3. MODEL

This section discusses the analytical review of incentives

in the regulatory framework applied to each corridor, thereby

encouraging more prudent behaviour in the banking sector.

An appropriate incentive scheme can be interpreted as banks

incurring higher costs when their financial position moves

away from that desired by the authority. Therefore, a sound

incentive mechanism should encourage banks to always

return to the prudential corridor because that is where most

efficiency can be achieved.

Suppose a bank has a profit optimisation function, π,

as a function of loans (l), deposits (d) and liquidity (liq) as

expressed in the following equation:

(E.4)

With balance sheet constraints, where d plus equity

(k) is equal to 1. Ω represents the average gearing ratio to

substitute k with l.

Another constraint is found on the assets side, which

represents the types of assets that can be owned by a bank,

such as loans, liquid assets and the RR.


Gambar3.amenunjukkan potensi probability of liquidity problem(probabilitas masalah likuiditas) yang akan dihadapi bank ketika tingkat likuiditas menurun. Bank, dalam kondisi normal, akan memiliki beberapa pilihan dalam memenuhi kebutuhan likuiditasnya yaitu dengan menetapkan cadangan likuiditas secara internal, mengoptimalkan credit line melalui pasar uang antar bank, membentuk secondary reserve yang terdiri dari liquid assetsyang siap untuk dijual secara langsung maupun melalui mekanisme repo.Dalam kondisi darurat likuiditas, dimana seluruh pilihan bank telah tertutup, bank bisa memanfaatkan fasilitas LOLR.Namun demikian, biaya yang dibutuhkan akan semakin tinggi sehingga menempatkan fasilitas LOLR sebagai opsi yang paling tidak efisien untuk didapat. Gambar3.bmenunjukkan bagaimana total returnsdari dari bank menjadi negatif ketika biaya yang ditimbulkan dari manajemen likuiditas (cost of liquidity) melebihi operational revenue (I). Dalam kondisi yang ekstrim,cost of liquiditymungkin saja melebihi networth bank (I + K) yang menggambarkan bagaimana posisi illikuid yang akut dapat membuat bank yang solvent namun tidak likuid menjadi tidak solvent. Untuk meminimalkan kemungkinan tersebut, otoritas perbankan menentukan threshold tertentu yang dipercaya dapat menjaga posisi likuiditasnya secara aman. Berikut adalah formulasi kesetimbangan balance sheet untuk mendapatkan angka Capital Adequacy Ratio (CAR)yang dapat menunjang 92% LDR: 𝑙𝑙𝑙𝑙 + 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 + 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 = 𝑑𝑑𝑑𝑑 + 𝑘𝑘𝑘𝑘 Membagi kedua sisi dengan d, kita mendapatkan 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑 = 1 + 𝑘𝑘𝑘𝑘𝑑𝑑𝑑𝑑 − 𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑 − 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑑𝑑𝑑𝑑 , dimana 𝑑𝑑𝑑𝑑 = 𝐴𝐴𝐴𝐴 − 𝑘𝑘𝑘𝑘 (P.2)

Menentukan posisi likuiditas aman sebesar 8%7dengan RR sebessar 8%, didapatkan nilai berikut:

0.13 = 𝑘𝑘𝑘𝑘𝐴𝐴𝐴𝐴−𝑘𝑘𝑘𝑘 atau 𝑘𝑘𝑘𝑘𝐴𝐴𝐴𝐴 = 0.115

Dengan rasio aktiva tertimbang menurut risikosebesar 80%, nilai optimum CAR yang dapat mendukung 92% percent LDR dengan pemenuhan 8% RR and 8% likuiditas adalah 14.38%.

Gambar4 Probability of liquidity problem8

7Analisa base line menunjukkan bahwa likuiditas optimal berarti bank memiliki kemampuan menyerap shock dengan mempertahan kan efisiensi berada di angka 8% (threshold oleh rasio AL/DPK). 8Simulasi di Gambar 3 dilakukan menggunakan (P.2)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

0.00

0.10

0.20

0.30

0.40

0.14 0.19 0.23 0.27 0.31 0.34

liq/d

RR/d

k/d

l/d (RHS)

145


Gambar4.menggambarkan hubungan antara CAR dan maximum capabilityuntuk menyalurkan kredit dengan menjaga RR and liquidity ratiosecara konstan pada8%.Secara alami, bank dengan CAR yang lebih tinggi akan memiliki kapasitas untuk mengekspansi kredit secara lebih kuat. Namun demikian, sebagaimana telah disebutkan sebelumnya, terdapat kemungkinan bank memaksakan ekspansi kredit diatas kapasitas maksimumnya untuk mendapatkan tingkat keuntungan yang paling tinggi yaitu dengan mencapai LDR yang lebih tinggi dari yang seharusnya. Jika LDR terlampau tinggi, bank akan memiliki keterbatasan likuiditas yang lebih intensifserta membahayakan kelangsungan operasinya dalam jangka panjang. Untuk memastikan bahwa bank beroperasi dalam area risk taking capacity-nya, regulator menerapkan disinsentif dengan memaksakan pembentukan secondary reserve jauh sebelum posisi likuiditas bank sampai pada kondisi kritis.Persyaratan untuk pembentukan secondary reserve diberikan pada persamaan (P.3). 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 = 𝜌𝜌𝜌𝜌0 + 𝜌𝜌𝜌𝜌2 𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑 − 𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑 (P.3)

Pembahasan di atas menunjukkan bahwa bank akan beroperasi dalam prudential corridor yang dapat mengakomodasi concern proses intermediasi dan manajemen likuiditas perbankan yang sehat. 3. Model Bagian ini membahas tinjauan analitistentang insentif pada regulatory framework yang diterapkan untuk setiap koridor sehingga bank dapat berperilaku secara lebih berhati-hati.Skema insentif yang tepat dapat diartikan bahwa bank harus membayar biaya yang lebih tinggi ketika posisi keuangannya bergeser menjauhi area yang diinginkan oleh otoritas.Oleh karena itu, mekanisme insentif yang baik seharusnya dapat mendorong bank untuk selalu kembali ke dalam prudential corridor karena mereka merasakan tingkat efisiensi yang lebih tinggi. Misalkan sebuah bank memiliki fungsi optimisasi keuntungan sebagai fungsi dari loan (l), deposit (d)dan likuiditas(liq) seperti ditunjukkan dalam persamaan (P.4). max𝑙𝑙𝑙𝑙 ,𝑑𝑑𝑑𝑑 ,𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 𝜋𝜋𝜋𝜋 = 𝑟𝑟𝑟𝑟𝐿𝐿𝐿𝐿 𝑙𝑙𝑙𝑙 + 𝑟𝑟𝑟𝑟 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 − 𝑟𝑟𝑟𝑟𝐷𝐷𝐷𝐷𝑑𝑑𝑑𝑑 − 𝑟𝑟𝑟𝑟𝐾𝐾𝐾𝐾 𝑘𝑘𝑘𝑘 (P.4) dengan kendala neraca (balance sheet constraint)dimana d ditambah dengan equity (k) sama dengan 1. merepresentasikan rata-rata gearing ratiountuk mensubstitusi k dengan l. 𝑑𝑑𝑑𝑑 + 𝑘𝑘𝑘𝑘 = 1,dimana 𝑘𝑘𝑘𝑘𝑙𝑙𝑙𝑙 = Ω 𝑑𝑑𝑑𝑑 + 𝑙𝑙𝑙𝑙 Ω = 1 Kendala yang lain adalah pada sisi aset yang merepresentasikan jenis-jenis aset yang mungkin dimiliki oleh bank seperti loan, liquid assetsdan RR. 𝑙𝑙𝑙𝑙 + 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 + 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 = 1

146




146

Article Graph 2.3. illustrates the relationship between

CAR and banks maximum capability to extend credit whilst

constantly maintaining the RR and liquidity ratio at 8%.

Naturally, banks with a higher level of CAR will have greater

capacity to expand credit. As mentioned previously, however,

there remains the possibility that a bank will force credit

expansion beyond maximum capacity in order to maximise

profit, namely by achieving a higher LDR than it should. If LDR

is too high, the bank will face more intense liquidity limitations

as well as threaten operational continuity in the long term.

To ensure a bank operates within its risk-taking capacity,

the regulator applies disincentives through the imposition

of secondary reserves well before the liquidity position of

Article Graph 2.3. Probability of liquidity problem8

0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

0,00

0,10

0,20

0,30

0,40

0,14 0,19 0,23 0,27 0,31 0,34

liq/dRR/d

k/dl/d (skala kanan)




146




146

150


The optimisation process that provides an optimal LDR

whilst paying due regard to the market rate can be written

as follows:

(E.5)

Equation 5 shows that the value of LDR increases as

the differential between the lending rate (rL) and the yield

of liquidity instruments (r) increases.

Lower Limit

Referring to Equation 5, the intermediation process

of the banking system will be suboptimal when the level of

return from productive sectors is lower than that provided

by financial assets. As mentioned previously, a low level of

intermediation is undesirable because it reflects a low level

of capital injection to support economic activity. As part of

the efforts to overcome a decline in capital for development,

the authority will apply a disincentive that requires banks

to place funds at the central bank if the minimum level of

intermediation is not achieved. The lower limit constraint

equation is as follows:

The outcome of the profit optimisation process

implemented by the bank in the form of credit, deposit and

liquidity volume demonstrates that the optimal level chosen

by the bank is based on the securities, deposit and credit

market rates available and disincentive factors as expressed

in Equations 6, 7 and 8.

(E.6)

(E.7)

(E.8)

Article Graph 2.4.a shows the bank’s response in the

form of the LDR level based on a change in the securities rate,

ceteris paribus(rL, rK, rD, Ω, ρ0 and ρ1 unchanged)9. It can be

observed that LDR declines if the return on credit decreases.

The disincentive applied, however, can hold the rate of LDR

decline. A thicker line shows that a higher level of disincentive

can maintain intermediation at a higher level.

Article Graph 2.4.a demonstrates that a decline in the

intermediation function in line with an increase in deposits

can be suppressed. This is evidenced when the LDR decline

slopes in line with the increase in deposits accumulated

by the bank. The incentive produced will encourage


Proses optimasi yang memberikan LDR optimal dengan mempertimbangkan suku bunga pasar diberikan dalam persamaan (P.5). 𝑙𝑙𝑙𝑙∗𝑑𝑑𝑑𝑑∗ = 𝑟𝑟𝑟𝑟𝐾𝐾𝐾𝐾−𝑟𝑟𝑟𝑟𝐷𝐷𝐷𝐷−𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝐿𝐿𝐿𝐿−𝑟𝑟𝑟𝑟 (P.5)

Persamaan diatas menunjukkan bahwa nilai LDR meningkat sejalan dengan peningkatan perbedaan suku bunga kredit (rL) dengan yielddari instrumen likuiditas (r). Batas bawah (Lower limit) Mengacu pada persamaan (P.5), proses intermediasi dari sistem perbankan menjadi sub-optimal atau lebih rendah ketika tingkat return yang diberikan oleh sektor produktif lebih rendah dibandingkan dengan tingkat return yang diberikan oleh aset keuangan. Sebagaimana telah disebutkan sebelumnya, tingkat intermediasi yang rendah tidak diinginkan karena hal tersebut merefleksikan injeksi modal yang rendah dalam mendukung kegiatan ekonomi.Sebagai upaya untuk menanggulangi penurunan modal untuk pembangunan, otoritas menerapkan disinsentif yang mewajibkan bank untuk menempatkan dananya di bank sentral jika tingkat intermediasi minimum tidak tercapai. Persamaan kendala (constraint) batas bawah menjadi: 𝑙𝑙𝑙𝑙 + 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 + 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑃𝑃𝑃𝑃 = 1,dimana 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑃𝑃𝑃𝑃 = 𝜌𝜌𝜌𝜌 𝑑𝑑𝑑𝑑, dan 𝜌𝜌𝜌𝜌 = 𝜌𝜌𝜌𝜌0 + 𝜌𝜌𝜌𝜌1

𝑑𝑑𝑑𝑑𝑙𝑙𝑙𝑙

Hasil dari proses optimisasi profit yang dilakukan oleh bank dalam bentuk volume kredit, deposit dan likuiditas menunjukkan tingkat optimum yang akan dipilih oleh bank berdasarkan tingkat suku bunga pasar kredit, deposit, securities yang tersedia di pasar dan faktor disinsentif ditunjukkan pada persamaan (P.6), (P.7), dan (P.8). 𝑙𝑙𝑙𝑙∗ = 𝑟𝑟𝑟𝑟𝜌𝜌𝜌𝜌1𝑟𝑟𝑟𝑟[1+𝜌𝜌𝜌𝜌1Ω2+𝑟𝑟𝑟𝑟𝐾𝐾𝐾𝐾Ω]− [𝑟𝑟𝑟𝑟𝑙𝑙𝑙𝑙+𝑟𝑟𝑟𝑟𝐷𝐷𝐷𝐷Ω+𝑟𝑟𝑟𝑟Ω𝜌𝜌𝜌𝜌0]1

2 (P.6)

𝑑𝑑𝑑𝑑∗ = 1 − Ω𝑙𝑙𝑙𝑙∗ (P.7) 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙∗ = 1 − 𝑙𝑙𝑙𝑙∗ + 𝜌𝜌𝜌𝜌0𝑑𝑑𝑑𝑑∗ + 𝜌𝜌𝜌𝜌1

𝑑𝑑𝑑𝑑∗2𝑙𝑙𝑙𝑙∗ (P.8)

Gambar5.amenunjukkan respon bank dalam bentuk tingkat LDR berdasarkan perubahan rate dari securities dengan tingkat suku bunga atau rasio yang lain dianggap konstan (rL, rK, rD, Ω,ρ0, dan ρ1)9.Terlihat bahwa LDR menurun jika return dari kredit bergerak turun. Namun disinsentif yang diterapkan dapat menekan laju penurunan LDR.Garis yang lebih tebal menunjukkan bahwa dengan tingkat disinsentif yang lebih tinggi, intermediasi dapat dipertahankan lebih tinggi.

9Parameter menggunakan data historis pasar (r= 8 pct, rK = 9 pct, rD = 5 pct, Ω = 0.1, ρ0 = 0.05, and ρ1 = 0.01)

147






2 (P.6)





147






2 (P.6)





147






2 (P.6)





147






2 (P.6)





147

9) The parameters use historical market data (r = 8 pct, rk = 9 pct, rD = 5 pct, Ω = 0.1, ρ0 = 0.05 and ρ1 = 0.01)

Article Graph 2.4.


Gambar5 a) LDR as a function of rate differential b) LDR as a function of deposit

Gambar5.bmenunjukkan bahwa penurunan fungsi intermediasi sejalan dengan kenaikan deposit dapat di tekan. Hal ini ini ditunjukkan ketika penurunan LDR menjadi melandai seiring dengan kenaikan deposit yang dihimpun oleh bank. Insentif yang dihasilkan akan mendorong countercyclicality dari proses penyaluran kredit walaupun hal ini harus didukung oleh kualitas governance yang baik yang dapat memastikan bahwa sound credit granting process dapat dipertahankan sehingga potensi peningkatan kredit bermasalah dapat ditekan khususnya dalam kondisi makroekonomi yang kurang baik10. Batas Atas (Upper Limit) Kebalikan dari batas bawah, penentuan batas atas dilakukan ketika ekonomi memasuki periode boom dimana tingkat return yang diberikan dari kredit lebih tinggi dari return yang diberikan financial asset yang juga dapat berfungsi sebagai alat-alat likuid (secondary reserve) bagi bank dalam mengelola likuiditasnya. Hal ini berarti bank akan mendorong kredit setinggi mungkin sehingga berpotensi untuk membahayakan kesinambungan kegiatan operasional bank. Sekarang, otoritas perbankan ingin membatasi ekspansi dalam area liquidity risktaking capacity yang baik. Disinsentif yang diberikan adalah: 𝜌𝜌𝜌𝜌 = 𝜌𝜌𝜌𝜌0 + 𝜌𝜌𝜌𝜌1𝑙𝑙𝑙𝑙, sehingga 𝑙𝑙𝑙𝑙(1 + 𝜌𝜌𝜌𝜌1) + 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 + 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 = 1 Menyelesaikan fungsi optimasi Lagrange, didapatkan tingkat LDR optimum bank sebagai fungsi ρ yang ditunjukkan dalam Gambar6. 𝑑𝑑𝑑𝑑∗ =

𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 + 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙1 + 𝜌𝜌𝜌𝜌 .

𝑟𝑟𝑟𝑟𝐿𝐿𝐿𝐿 − 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝐾𝐾𝐾𝐾 − 𝑟𝑟𝑟𝑟𝐷𝐷𝐷𝐷

𝑙𝑙𝑙𝑙∗ = 1 − 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 − 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙

1 + 𝜌𝜌𝜌𝜌

Hal ini menunjukkan bahwa pada saat tingkat LDR menuju tingkatan yang dianggap membahayakan, pemberian disinsentif dalam bentuk portfolio restriction (bank dipaksa untuk membentuk secondary reserve) akan secara efektif membatasi tingkat LDR bank.

10Saat resesi, otoritas moneter cenderung untuk menahan suku bunga pada level tertinggi. Hal ini aka berdampak pada portofolio bank.

148

a) LDR as a function of rate differential a) LDR as a function of deposit

151


10) During a recession, the monetary authority tends to maintain interest rates at the highest level, which influences bank portfolio.

countercyclicality in the credit extension process, although

this must be buttressed by quality governance to ensure that

a sound credit granting process can be maintained, thereby

suppressing a potential increase in non-performing loans

(NPL) when macroeconomic conditions are unfavourable10.

Upper Limit

In contrast to the lower limit, the upper limit is

determined when the economy enters a boom period, when

the level of return provided by credit exceeds the return on

financial assets, which also function as secondary reserves

for the bank to manage liquidity. This suggests that banks will

expand credit as rapidly as possible, creating the potential to

endanger operational continuity. At this point, the banking

authority would like to limit credit expansion to the area of

sound liquidity risk-taking capacity. The disincentive imposed

will be as follows:

Resolving the Lagrange optimisation function produces

an optimal level of LDR as a function of p as shown in Article

Graph 2.5.

This shows that as LDR approaches a level deemed

unsafe, applying a disincentive in the form of portfolio

restrictions (banks are required to provision secondary

reserves) will effectively limit bank LDR.










148










148










148

4. CONCLUSION

Macroprudential policy is formulated to fill the gaps that

emerge between microprudential and macroeconomic policy.

The policy formulated must accommodate bank operational

continuity at the institutional level and also financial system

stability to bolster economic sustainability. LDR-linked RR

policy can be utilised as a macroprudential policy instrument

to bridge the micro and macro concerns. Determining the

lower limit of the LDR-linked RR must accommodate the

interests of the banking system to support the intermediation

process, thereby ensuring capital allocation for developmentis

maintained, especially during a recession. An incentive

mechanism was shown to influence bank preferences away

from investments in securities towards credit extension,

hence demonstrating the countercyclical effect of the policy.

Similarly, when determining the upper limit, incentives can

persuade a bank to reduce excessive lending and expand an

adequate liquidity buffer.

Article Graph 2.5.LDR as a function Rho


Gambar6 LDR as a function rho

4. Kesimpulan Kebijakan makroprudensialdisusun untuk mengisi gap yang muncul antara kebijakan mikroprudensial dan kebijakan macroekonomi.Kebijakan yang disusun harus dapat mengakomodasi kesinambungan operasional bank pada tingkat institusi dan juga stabilitas system keuangan untuk mendukung kesinambungan pembangunan ekonomi. Kebijakan GWM-LDR dapat digunakan sebagai salah satu instrumen kebijakan makroprudensial yang dapat menjembatani concernmikro dan makro. Penetapan batas bawah GWM-LDR mengakomodasi kepentingan system perbankan untuk mendukung proses intermediasi sehingga pengalokasian modal untuk pembangunan khususnya pada kondisi resesi ekonomi dapat selalu dipertahankan. Ditunjukkan bahwa mekanisme insentif yang terbentuk dapat menggeser preferensi bank dari investasi di surat-surat berharga ke penyaluran kredit dan hal ini menunjukkan efek countercyclicality dari kebijakan yang dibentuk. Sama halnya dengan penetapan batas atas, insentif yang terbentuk dapat menggeser preferensi bank untuk mengurangi penyaluran kredit yang berlebihan kearah pembentukan liquidity buffer yang mencukupi.

149

152


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is page is in en ona e ank

Financial Stability ReviewNo.23, September 2014

DIRECTOR

Halim Alamsyah Darsono Agusman Yati Kurniati

COORDINATOR & EDITOR

Cicilia A. Harun., Bambang Pramono, Butet Linda H.P.

ANALYSTS

Arlyana Abubakar, Ita Rulina, Ibrahim, Iman Gunadi, M. Firdaus Mutaqin, Dwityapoetra S. Besar,

Clarita Ligaya Iskandar, Koppa Kepler, Ndari Suryaningsih, Dadang Muljawan, Kurniawan Agung,

Rozidyanti, Danny Hermawan, Eka Vitaloka, Kartina Eka D., Risa Fadila, Elis Deriantino, Mestika

Widantri, Darmo Wicaksono, Bayu Adi Gunawan, Maulana Haris Muhajir, Harris Dwi Putra, Tevy

Chawwa, Justina Adamanti, Aditya Anta Taruna, Syaista Nur, Teguh Afriyanto, Yogi Ferdian Y, Hero

Wonida, Randy Cavendish, Syachman Perdymer, Veny Tamarind, Lestari Shitadewi, Dwiyanto Cahyo

Sumirat, Ratih Maharani, Inrayanto Ariandos, Fransiskus Xaverius Tyas Prasa, Santi Permatasari

OTHER DEPARTMENT CONTRIBUTION ON SELECTED ANALYSIS

Economic and Monetary Policy Department (DKEM)

Financial Access and SME Development Department (DPAU)

Financial System Surveillance Department (DSSK)

Statistics Department (DSta)

Payment System Policy and Oversight Department (DKSP)

Payment System Management Department (DPSP)

PRODUCTION AND DISSEMINATION TEAM

I Made Yogi, Saprudin, Arievtha Al K., Rio Akbar, Wandi Yanda S.

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