Financial Stability Review

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 2011 and is based on data and information available as of June 2011,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

Directorate of Banking Research and Regulation

Financial System Stability Bureau

Jl.MH Thamrin No.2, Jakarta, Indonesia

Phone : (+62-21) 381 8902, 381 8075

Fax : (+62-21) 351 8629

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. 17, September 2011)

Directorate of Banking Research and Regulation

Financial System Stability Bureau

ii

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iii

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

Foreword .............. .................................................................................................................................................. vii

Overview ......... ........................................................................................................................................................ 3

Chapter 1. External and Internal Conditions .............................................................................................................. 7

1.1. Potential External Vulnerability ................................................................................................................ 7

1.2. Potential Internal Vulnerability ................................................................................................................. 9

Box 1.1. The impact of higher interest rates on non-financial, LQ 45 listed companies .................................... 17

Box 1.2. Assessment of Corporate Resilience .................................................................................................. 19

Chapter 2. Financial System Resilience ....................................................................................................................... 25

2.1. Financial System Structure and Resilience ................................................................................................. 25

2.2. Risk in The Banking System ...................................................................................................................... 26

2.3. Potential Financial Market Risk and Financing ........................................................................................... 35

Box 2.1 Implementation of Transparent Base Lending Rates .......................................................................... 45

Box 2.2 Automotive Loans: Is Policy Harmonisation required between Bank Indonesia and the Capital Market

and Financial Institution Supervisory Board (Bapepam-LK)? ............................................................... 47

Chapter 3. Financial System Stability Prospects and Challenges .................................................................................. 51

3.1. Crisis threats from the United States and Europe to the economy of Indonesia ......................................... 51

3.2. Impact on The Indonesian Financial System .............................................................................................. 53

3.3. Impact on banks and Stress Tests ............................................................................................................. 55

3.4. Financial System Projections ..................................................................................................................... 57

Box 3.1 European Financial Stability Facility ................................................................................................... 58

Chapter 4. Special Topic ............................................................................................................................................ 63

4.1. Systemically Important Financial Institutions (SIFI) .................................................................................... 63

4.2. Refining the Crisis Management Protocol to maintain Financial System Stability ....................................... 65

4.3. BPD implementation of the regional champion program .......................................................................... 67

4.4. Compilation of a financial curriculum for schools ..................................................................................... 68

Articles................ ...................................................................................................................................................... 71

Article 1 Optimisation of Bank Portfolio Composition in Indonesia ................................................................... 73

Article 2 Procyclicality Of Banks’ Capital Buffer In Asean Countries .................................................................. 85

Attachment................ ............................................................................................................................................... 91

Summary of Bank Indonesia Regulations concerning Financial System Stability (Semester I-2011) .................... 93

Table of Contents

iv

List of Tables and Figures

Tables Figures

1.1 Global Economic Growth ............................... 81.2 State Budget Realisation in Semester I – 2010-2011 ................................. 121.3 Government Foreign Debt .............................. 131.4 Debt Service Ratio .......................................... 14

2.1 Number of Financial Institutions ..................... 252.2 Liquid Asset Growth ....................................... 272.3 Profit/Loss of the Banking Industry ................. 322.4 SUN Value at Risk (VaR) .................................. 372.5 Ownership of Tradable Government Securities (SBN) .............................................................. 372.6 Indices of several Global Stock Markets .......... 382.7 Share Price Index by Economic Sector ......... 392.8 Firms that Issued Bonds in Semester I-2011 412.9 Bonds due to Mature by Yearend 2011 ...... 422.10 Financial Ratios of Finance Companies......... 432.11 NPL of Finance Companies .......................... 44

3.1 Projected GDP and Inflation ........................ 523.2 Simulated hike in BI Rate on SUN Prices, FR Series ..................................................... 543.3 Simulated hike in BI Rate on SUN Prices, VR Series .................................................... 55

1.1 Price Indices of several Global Commodities 2000 = 100 .................................................... 81.2 Indices of Global Share Prices ......................... 81.3 CDS in several European Countries ................. 91.4 CDS in several Asian Countries ....................... 91.5 Non-Oil/Gas Imports/Exports .......................... 101.6 Total Exports and Imports ............................... 101.7 The Rupiah Exchange Rate ............................. 101.8 Rupiah Exchange Rate Volatility ...................... 101.9 Inflation in several ASEAN member countries . 111.10 Inflation in several Developed Countries ......... 111.11 Real Interest Rates .......................................... 111.12 Composition of Direct Investment and Portfolio Investment to Indonesia ................................. 111.13 ROA and ROE of Non-financial Public Listed Companies ..................................................... 141.14 DER and LL/TA of Non-financial Public Listed Companies ..................................................... 141.15 Major Corporate Financial Indicators .............. 151.16 Consumer Confidence Index (CCI) .................. 151.17 Credit and NPL to the Household Sector ........ 161.18 Household Non-performing Loans .................. 161.19 Types of Household Loans .............................. 161.20 Composition of Household Credit in June 2011 . 16

2.1 Composition of Financial Institutions’ Assets .. 252.2 Financial Stability Index 1996-2011 ................ 262.3 Shares of Bank Funding and Financing ........... 262.4 Growth in Deposits by Semester ..................... 262.5 Deposit Growth based on Ownership ............. 272.6 Composition of Bank Liquid Assets ................. 272.7 Share of Bank Placements at Bank Indonesia .. 282.8 Credit Growth by Currency ............................ 282.9 Credit Funding by Currency ............................ 292.10 Credit Growth by Type ................................... 292.11 Credit Growth by Economic Sector ................. 292.12 Growth and Share of Property Credit ............. 302.13 Non-Performing Loans (NPL) ........................... 302.14 NPL Ratio by Currency .................................... 302.15 NPL Growth by Currency ................................ 312.16 NPL Growth by Loan Type .............................. 31

v

Figures Figures

2.17 NPL Ratio by Loan Type .................................. 312.18 NPL Ratio by Economic Sector ........................ 312.19 NPL Ratio of Property Credit ........................... 322.20 Bank Profit/Loss .............................................. 332.21 Composition of Interest Income in the Banking

Industry (%) ................................................... 332.22 Interest Rate Spread in Rupiah (%) ................. 332.23 Bank ROA and Efficiency Ratio (%) ................. 332.24 Bank Capital, Risk-Weighted Assets and CAR . 342.25 CAR by Bank Group (%) ................................ 342.26 MSM Credit (yoy) ........................................... 352.27 Gross NPL Ratio of MSM Bank Loans (%) ....... 352.28 Foreign Investor Placements: SBI, SUN, Stock .. 352.29 Foreign Portfolio in Rupiah Financial Instruments (SBI, SUN, Stock) ......................... 352.30 Average Monthly SUN Price ............................ 362.31 Price of Benchmark SUN FR Series .................. 362.32 SUN Value at Risk (VaR) .................................. 372.33 SUN Maturity Profile (June 2011) .................... 372.34 Performance of JCI as well as other Global and Regional Indices (indexed as per 31st December 2005) ............ 372.35 Volatility on various Asian Bourses .................. 392.36 Bank Share Prices ............................................ 392.37 Percentage Change in Bank Share Prices ........ 402.38 Performance of Mutual Funds ........................ 402.39 Net Asset Value by type of Fund ..................... 402.40 Capitalization Value and Value of Issuances ... 402.41 Issuances and Position of Corporate Bonds ..... 412.42 Business Activity of Finance Companies .......... 422.43 Financing (billions of rupiah) ........................... 422.44 Finance Companies’ Source of Funds ............. 43

3.1 GDP Growth per Capita ................................. 523.2 Debt to GDP Ratio of several Countries .......... 533.3 Indonesia’s Debt to GDP Ratio 2006-2011 ..... 533.4 JCI versus Foreign Transactions (2008-2009) .. 533.5 JCI versus Foreign Transactions (2010-2011) .. 543.6 Maturity Profile Rupiah ................................... 553.7 Stress Tests for Higher Interest Rates .............. 553.8 Net Open Position (NOP) ................................ 563.9 Stress Tests for Rupiah Depreciation ............... 563.10 Stress Test for a decline in SUN Price .............. 563.11 Stress Test for Credit Risk ............................... 57

vi

List of Abbreviations

ADB Asian Development BankAEC Asean Economic CommunityASEAN Association of Southeast Asian NationsBapepam- LK Capital market and Financial Institution

Supervisory BoardBCBS Basel Committee on Banking SupervisoryBIS Bank for International SettlementBNM Bank Negara MalaysiaBPD Regional Banksbps basis pointsBRC BPD Regional ChampionBRIC Brazil, Rusia, India, dan ChinaCAR Capital Adequacy RatioCC Code of ConductCCP Central Counter PartiesCDS Credit Default SwapCPI Consumer Price IndexCRA Credit Rating AgencyCRBC China Banking Regulations CommissionsDER Debt to Equity RatioEFSF European Financial Stability FacilityETF Exchange-Traded FundEU European UnionFASB Financial Accounting Standard BoardFDI Foreign Direct InvestmentFSA Financial Service AuthorityFSAP Financial Sector Assessment ProgramFSB Financial Supervisory BoardFSI Financial Stability IndexG20 The Group of TwentyGDP Gross Domestic ProductGIM Indonesian Saving MovementG-SIFI Global Systemically Important Financial

InstitutionsIAIS International Association of Insurance

SupervisorIASB International Accounting Standard BoardIDMA Inter-dealer Market AssociationIMF International Monetary FundIOSCO International Organization of Securities

CommissionsJCI Jakarta Composite IndexJPSK Financial System Safety NetLBU Commercial Bank ReportLC Letter of CreditLDR Loan to Deposit RatioMSM Micro Small and Medium CreditNII Net Interest IncomeNIM Net Interest Margin

NOP Net Open PositionNPF Non Performing FinancingNPL Non Performing LoanOPEC Organization of the Petroleum Exporting

CountriesOTC Over the CounterPBI Bank Indonesia RegulationPD Probability of DefaultPIIGS Portugal, Ireland, Italy, Greece and SpainPMK BI Bank Indonesia’s Crisis Management

ProtocolROA Return on Asset ROE Return on EquitySBI Bank Indonesia CertificatesSBN Government SecuritiesSIFI Systemically Important Financial InstitutionsSUN Government BondsTL/TA Total Loss to Total Asset RatioUS United States of America UU Act

vii

As a manifestation of accountability in the implementation of its task to maintain financial system stability, Bank

Indonesia publish Financial Stability Review (FSR) No 17, September 2011. Through the publication of the Financial Stability

Review, Bank Indonesia presents the results of its risk monitoring activities in the financial system as well as macroprudential

research so that the stakeholders receive a complete picture of development conditions, the risks faced and future prospects

of the financial system. In particular, Bank Indonesia also appeals to the banking sector and the business community to

implement a number of measures to mitigate potential risk in the financial sector looking ahead. In this edition FSR is

presented more simply and directly addresses the core of the problems faced, hence, raising public understanding of the

risks encountered in the financial system as well as the vulnerabilities that could spark another crisis.

Assessments of financial system conditions indicate that financial system stability was maintained during the reporting

period amid dynamic developments in the global economy. Sound financial system conditions were bolstered by favourable

bank and financial market performance during the fist half of the year. Aspects of capital and profitability that continued

to strengthen reflected positive bank performance. In addition, the quality of bank intermediation also improved, which

was evidenced by the increase in productive credit extension in excess of that projected. Furthermore, banks continued

to manage their credit risk in the current economic climate in harmony with the decline in non-performing loans. The

performance of mutual funds and finance companies also improved. A decline in the Financial Stability Index from 1.75

(December 2010) to 1.65 (June 2011) was a good reflection of financial system resilience in the reporting period. Bank

resilience was relatively well maintained and volatility on the domestic bourse eased on the back of the solid domestic

economy and controlled inflation helped contribute to the decline in FSI.

However, vigilance and prudence are still required considering that global economic conditions looking ahead remain

marred by widespread uncertainty. Although financial system resilience is well maintained, global instability could spillover

into the domestic financial markets, thereby, intensifying asset price volatility on the markets. Global economic uncertainty

also has the potential to trigger a sudden reversal in short-term foreign capital flows. Therefore, these challenges necessitate

vigilance due to their potential for escalating pressures on financial system stability and monetary stability.

In closing, we expect this edition of the Financial Stability Review to achieve its mission as an effective communication

media to our stakeholders regarding the outcome of surveillance conducted by Bank Indonesia in the area of financial

system stability. We warmly welcome any suggestions, comments and constructive criticism from all parties with the aim

to further improve this Review in later editions.

Foreword

Jakarta, September 2011

GOvERNOR OF BANk INDONESIA

Darmin Nasution

Overview

1

Overview

2

Overview


Overview

3

POTENTIAL VULNERABILITY AND FINANCIAL

SYSTEM STABILITY

Improved resilience coupled with financial system

stability in 2010 persisted until the end of Semester

I-2011, bolstered by sound macroeconomic performance

and maintained financial stability, including effective bank

supervision, thus alleviating volatility on the stock and bond

markets as well as reducing credit risk, as reflected by a

decline in non-performing loans.

Externally, the economic recovery in developed

countries, the US and Europe remained languid.

Conversely, robust economic growth was posted in

emerging market countries. Foreign capital continued

to flow into Indonesia but at a lesser volume due to the

application of policy to extend the holding period from

one month to six months.

Potential vulnerability from the corporate and

household sectors caused little concern as a result of

improved corporate sector performance accompanied by

less risk. Corporate sector indicators were reassuring and,

hence, consumer confidence in economic performance for

the upcoming six months remained high.

Banking sector performance during the first semester

of 2011, in general, improved. Bank capital was maintained

at a sufficiently high level, whereas profitability and net

interest income increased with a lower efficiency ratio.

Credit, both in rupiah and foreign exchange, posted

buoyant growth in nearly all economic sectors. Productive

credit, which expanded more rapidly, is expected to

catalyse stronger economic growth.

Financing sourced from securities helped shore

up credit growth. Nevertheless, deposit growthwas

inadequate to cover the requirement for credit, which was

a result of the banks’ strategy response to Bank Indonesia

policy taken to manage bank liquidity. Banks met their

requirement for funds to extend credit by reducing their

ownership of tradable government securities (SBN) and

monetary operations.

Mutual funds and finance companies continued

to perform better. The increase in the net asset value of

mutual funds primarily stemmed from equity funds and

protected funds.

FINANCIAL SYSTEM STABILITY PROSPECTS AND

CHALLENGES

Looking ahead, sound financial system conditions

in Semester I-2011 will be strained by greater global

economic instability as well as a slowdown in economic

growth. As a consequence of such inauspicious global

economic dynamics, the banks and market participants

are expected to:

• Remain vigilant of a possible increase in risk due

to uncertainty regarding crisis resolution and fiscal

deficits in the US and Europe; and

• Remainwatchfulofadeclineingloballiquidityand

an escalation in volatility on the stock and bond

markets as well as enhance their risk management.

Meanwhile, macroeconomic conditions during

the second semester of 2011 are expected to remain

conducive. Slower economic growth in developed

Bab 1 Overview


4

Overview

countries, which will undermine exports to these countries,

will have to be offset by diversifying the destinations of

Indonesian exports. Furthermore, the role of domestic

consumption and investment will remain the engine of

domestic economic expansion.

In broad terms, credit risk in the corporate and

household sectors is still low. However, a potential decline

in exports due to the global crisis will require vigilance,

which could affect the level of non-performing loans and

probability of default (PD) in the corporate sector. In this

context, business players and the banks are expected to:

• Prepare anticipatorymeasures to overcome the

impact of the global economy, particularly in terms

of corporate performance in order to avoid disrupting

the performance of the banking sector.

The bank intermediation function is predicted to

continue. Credit extended by banks to the real sector,

especially to productive sectors, has already expanded

substantially on the back of increased investment credit and

working capital credit. However, it is important to remain

vigilant of this increase so as to avoid a corresponding

increase in credit risk.Accordingly, the banks and business

players are reminded to:

• Enhancetheintermediationfunction,particularlyin

the agricultural, manufacturing and infrastructure

sectors, which are labour intensive and affect the

development of supporting subsectors; and

• Maintain a low level of non-performing loans for

investment credit and working capital credit.

In terms of liquidity, slow deposit growth and strong

credit growth are expected to affect the level of liquidity

on the money market. Therefore, the banks and business

players are urged to:

• Maintainadequateliquidity;and

• Remainvigilantofmoneymarketsegmentation.

In general, financial system resilience is projected

to remain during the second semester of 2011

despitewidespread uncertainty in the global economy.

Nonetheless, there remains the potential for a sudden

capital reversal, which would undermine financial sector

performance and financial system stability.

The results of stress tests indicate that the corporate

sector is able to service its domestic and foreign loans even

under a worst-case scenario, while the household sector

will not experience any serious problems. On the financial

markets, price volatility of shares and bonds will increase

in line with global economic uncertainty.

Referringtothebankingsector,industry-widestress

tests demonstrate adequate bank capital in the face of

possible defaults in the US and Europe. Furthermore, if the

stress tests take into account the impact of rising NPL on

export credit and assume exposure to default in the US and

Europe,bankCARstillremainssafeinexcessof15%.

5

Chapter 1. External and Internal Conditions

Chapter 1External and Internal Conditions

6



7


Chapter 1 External and Internal Conditions

Financial system stability was supported in Semester I-2011 by improved

macroeconomic performance in Indonesia despite intense inflationary

pressures at the beginning of the year. The improvement in macroeconomic

performance was in line with the continuing global economic recovery

process and further bolstered by successes in terms of fiscal, monetary and

banking policy. As a result of the increasingly conducive business climate,

the corporate and household sectors helped create financial system stability.

Corporate indicators improved, which are used as a barometer of performance,

accompanied by declining risk. Meanwhile, the ratio of household debt to

total assets (gearing ratio) remained very low, which reflects the households’

ability to repay their debts.

1.1. POTENTIAL EXTERNAL VULNERABILITY

1.1.1. Global Economy and Financial Markets

The global economy continued to expand during the

first semester of 2011, which confirmed the continuation

of the post-crisis economic recovery. Global economic

growth was primarily driven by growth in emerging

market countries, which offset the economic slowdown

in a number of established countries in Europe as well as

the United States.

The problems facing several European nations, which

have remained for a number of years and resulted in the

downgrading of sovereign debt ratings for PIIGS countries

(Portugal, Ireland, Italy, Greece and Spain), continued to

develop and led to the resignation of the prime minister

of Portugal in March 2011. Overall economic growth,

however, for member states of the Euro zone remained

positive thanks to the solid economic performance

of France and Germany. The United States and Japan

continued to face internal problems and, hence, are

not projected to post growth which exceeds that of the

previous year. With the developments that took place

during the second half of Semester I-2011, in its July 2011

publication the IMF lowered its global economic growth

projection from 4.4% to 4.3% (Table 1.1).


8


The level of inflation continued to rise, principally

triggered by high commodity prices despite the prices of

several commodities like oil actually declining slightly. The

slight drop in the oil price in the middle of Semester I-2011

was primarily attributable to expectations of a slowdown

in the global economy as well as market intervention by

the International Energy Agency to release oil reserves

following the failure of OPEC to meet the agreed upon

increase in production quota. Food prices also tended to

decline despite the slight increase in the price of wheat

stemming from concerns over drought in several areas of

Europe. The price of gold trended upwards in line with

uncertainty regarding the global economic recovery, which

caused investors to invest their funds in gold.

*) projectedSource: World Economic Outlook Update, June 2011. Data for Indonesia is from BPS-

Statistics Indonesia and the projections for Quarter II-2011 are calculated by Bank Indonesia.

2009(%)

2010(%)

2011*(%)

Table 1.1Global Economic Growth

World Output -0.5 5.1 4.3

Advanced Economies -3.4 3.0 2.2

United States of America -2.6 2.9 2.5

Euro Area -4.1 1.8 2.0

Germany -4.7 3.5 3.2

France -2.6 1.4 2.1

Portugal -2.0 2.3 -1.1

Italy -5.2 1.3 1.0

Ireland -11.3 -3.6 -1.3

Greece -0.8 -2.1 -2.6

Spain -3.7 -0.1 0.8

United Kingdom -4.9 1.3 1.5

Japan -6.3 4.0 -0.7

Emerging & Developing

Economies 2.8 7.4 6.6

ASEAN-5 1.7 6.9 5.4

Indonesia 4.6 6.1 6.3-6.8%

BRIC

Brazil -0.6 7.5 4.1

Rusia -7.8 4.0 4.8

India 6.8 10.4 8.2

China 9.2 10.3 9.6

Middle East and North

Africa 2.5 4.4 4.2

Source: Directorate of Economic and Monetary Statistics, Bank Indonesia

Source: Bloomberg

Figure 1.1Price Indices of several Global Commodities

2000 = 100

Figure 1.2Indices of Global Share Prices

Against this backdrop, global financial markets

remained stable during the first half of Semester

I-2011. However, as a result of the fiscal problems in

several European countries, market conditions began to

deteriorate in the second quarter of 2011. Banking shares

took the biggest hit as a result of the banks’ proclivity

to hold junk bonds from several European governments

(Figure 1.1).

0

100

200

300

400

500

600

Jan

- 07

May

- 07

Sep-

07

Jan

- 08

May

- 08

Sep

- 08

Jan

- 09

May

- 09

Sep

- 09

Jan

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May

- 10

Sep-

10

Jan

- 11

May

- 11

Oil Copper Gold Rice

0

5.000

10.000

15.000

20.000

25.000

30.000

35.000

Jan

- 07

May

- 07

Sep-

07

Jan

- 08

May

- 08

Sep

- 08

Jan

- 09

May

- 09

Sep

- 09

Jan

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May

- 10

Sep-

10

Jan

- 11

May

- 11

Hongkong (left scale) Dow Jones (left scaleSingapore (right scale) FTSE (right scale)

1.000

2.000

3.000

4.000

5.000

6.000

7.000

8.000

9


Uncertainty regarding a recovery from the crises in

Europe encouraged global investors to continue directing

their funds into emerging market countries, which posted

solid economic growth. Consequently, net private capital

flows to emerging markets are expected to surpass $1

trillion in 2011. Despite reflecting widespread investor

confidence in the economic fundamentals of emerging

market countries, there is no doubt that the deluge of

capital inflows will also lead to concerns over bubbles and

the possibility of a sudden capital reversal if something

unexpected transpires. Such conditions suggest that some

emerging market countries will apply more stringent

foreign exchange controls in response to the influx of

foreign capital flows.

1.2. POTENTIAL INTERNAL VULNERABILITY

1.2.1. Macroeconomic Conditions and the Real

Sector

Persistently high economic growth, particularly in

emerging market countries, drove strong demand for

Indonesian exports, primarily non-oil/gas exports of natural

resources. At the end of Semester I-2011 the value of

Indonesian non-oil/gas exports reached $14.8 billion,

which represents 10.1% growth compared to the end

of Semester II-2010. Meanwhile, the value of imports to

Indonesia at the end of Semester I-2011 was $11.6 billion,

which accounts for just 6.9% growth over the previous

semester. Notwithstanding, growth in imports outpaced

that of total exports, which led to a slight decline in the

current account surplus (Figure 1.5).

During Semester I-2011, credit default swaps

(CDS) in the majority of the monitored world remained

stable despite a recent upward trend triggered by the end

of the Quantitative Easing III program by the Fed on 30th

June, the downgraded US credit rating by S&P on 5th

August and the deterioration in the European crisis due

to the failure of Greece to meet its budget deficit target

(Figure 1.3). In stark contrast to the conditions found in

Europe, CDS in the majority of Asian countries declined.

Economic growth in Asia, which far exceeded that posted

in developed countries, led to a torrent of foreign capital

flows into the region (Figure 1.4).

Source: Bloomberg

Source: Bloomberg

Figure 1.4CDS in several Asian Countries

Figure 1.3CDS in several European Countries

500

450

400

350

300

250

200

150

100

50

0

Germany

Mar

- 09

May

- 09

Jul-

09

Sep

- 09

Nov -

09

Jan

- 10

Mar

- 10

May

- 10

Jul -

10

Sep

- 10

Nov -

10

Jan

- 11

Mar

- 11

May

- 11

Jul -

11

The NetherlandsFranceBelgium

ItalyAustria

Spain

800

700

600

500

400

300

200

100

0

Indonesia

Mar

- 09

May

- 09

Jul-

09

Sep

- 09

Nov -

09

Jan

- 10

Mar

- 10

May

- 10

Jul -

10

Sep

- 10

Nov -

10

Jan

- 11

Mar

- 11

May

- 11

Jul -

11

VietnamPhilippinesKorea

ThailandChina

Malaysia

10


In terms of prices, CPI inflationary pressure at the

beginning of Semester I-2011 was high at 7.02% in

January as a result of non-fundamental factors, principally

from commodities like chillies and kerosene. The high

rate of inflation was responded to by raising the BI rate

to 6.75% in February 2011. The level of inflation began

to decline in the following month up until the end of the

semester and in June was recorded at 5.54% (yoy) (Figure

1.7 and 1.8).

Source: Bloomberg Source: Bloomberg

Source: Bloomberg Source: Bloomberg

Figure 1.5Non-Oil/Gas Imports/Exports

Figure 1.7The Rupiah Exchange Rate

Figure 1.6Total Exports and Imports

Figure 1.8Rupiah Exchange Rate Volatility

Domestic consumption also remained strong on

the back of increased public income from other domestic

sources like an increase in the provincial minimum wage,

greater state income, higher salaries, as well as the wealth

effect of rising share prices, and supported by bank

financing. This was the main factor underpinning domestic

economic growth, which in Quarter II-2011 was predicted

to achieve 6.5% (yoy) compared to 6.1% in the second

quarter of 2010 (Figure 1.6).

0

12.000

14.000

16.000

18.000

4.000

2.000

6.000

8.000

10.000

Million USD

Jan

- 07

May

- 07

Sep-

07

Jan

- 08

May

- 08

Sep

- 08

Jan

- 09

May

- 09

Sep

- 09

Jan

- 10

May

- 10

Sep-

10

Jan

- 11

May

- 11

Non Oil/Gas Imports Non Oil/Gas Exports

0

12.000

14.000

16.000

18.000

4.000

2.000

6.000

8.000

10.000

Million USD

Jan

- 07

May

- 07

Sep-

07

Jan

- 08

May

- 08

Sep

- 08

Jan

- 09

May

- 09

Sep

- 09

Jan

- 10

May

- 10

Sep-

10

Jan

- 11

May

- 11

Total Exports Total Imports

0

2.000

4.000

6.000

8.000

10.000

12.000

14.000

0

2.000

4.000

6.000

8.000

10.000

12.000

14.000

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 8 9 10 11 12 1 2 3 4 5 6 1 2 3 4 5 67 8 9 10 11 12

2007 2008 2009 2010 2011

Monthly average Quarterly Average Semesterly Average

- 1,5

- 1

- 0,5

0

0.5

1

1.5

1 10 19 26 37 46 55 64 73 82 91 100

109

118

127

136

145

154

163

172

181

190

199

208

217

226

235

244

253

262

Lower limit Upper Limit Actual

262 days Period

11


Inflation in Indonesia was among the highest in the

region (ASEAN+5) (Figure 1.9 and 1.10). However, this

was offset by a higher interest rate, thus the real interest

rate in Indonesia was more attractive than that offered in

other ASEAN+5 member countries as well as the United

States and European Union. Consequently, Indonesia

remained an attractive investment destination for excess

liquid funds.

1.2.2. Investment and the Balance of Payments

With macroeconomic conditions that supported a

shift in investor attention to emerging market countries,

domestic investment and foreign direct investment

increased during the first semester of 2011 to reach

Rp115.6 trillion. This increase mainly stemmed from

domestic investment amounting to Rp33 trillion and

foreign direct investment totalling Rp82.6 trillion, which

is an increase of 24.4% over the same period in the

previous year. In total, investment in Indonesia reached

$20.4 million with the majority in the form of portfolio

investment (51%), while the portion of direct investment

(FDI) expanded compared to 2010 when just 46% was

recorded (Figure 1.12).

Sectors that secured additional investment include

the food industry (Rp4.6 trillion), food crops and

plantations (Rp4.5 trillion), transportation, storage and

telecommunications (Rp4.3 trillion), the non-metallic

minerals industry (Rp3.5 trillion) as well as basic metal

Source: Directorate of Economic and Monetary Statistics, Bank Indonesia Source: Bloomberg and the Directorate of Economic and Monetary Statistics, Bank Indonesia.

Source: CEIC and theDirectorate of Economic and Monetary Statistics, Bank Indonesia. Source: Bloomberg and the Directorate of Economic and Monetary Statistics,

Bank Indonesia.

Figure 1.9Inflation in several ASEAN member countries

Figure 1.11Real Interest Rates

Figure 1.10Inflation in several Developed Countries

Figure 1.12Composition of Direct Investment and Portfolio

Investment to Indonesia

(6)

(2)

2

6

10

y.o.y %Ja

n - 0

7

May

- 07

Sep-

07

Jan

- 08

May

- 08

Sep

- 08

Jan

- 09

May

- 09

Sep

- 09

Jan

- 10

May

- 10

Sep-

10

Jan

- 11

May

- 11

The PhilippinesMalaysia

ThailandIndonesia

(5)

(2)

1

4

7

y.o.y %

Jan

- 07

May

- 07

Sep-

07

Jan

- 08

May

- 08

Sep

- 08

Jan

- 09

May

- 09

Sep

- 09

Jan

- 10

May

- 10

Sep-

10

Jan

- 11

May

- 11

US Japan European Union Singapore

-6,0

6,0

8,0

2,0

4,0

-2,0

0,0

-4,0

Jan

- 07

May

- 07

Sep-

07

Jan

- 08

May

- 08

Sep

- 08

Jan

- 09

May

- 09

Sep

- 09

Jan

- 10

May

- 10

Sep-

10

Jan

- 11

May

- 11

US Singapore European Union Indonesia

0

20

10

30

50

40

60

%

70

2005

61

3945

55

41

59

75

25

32

68

46

5449 51

2006 2007 2008 2009 2010 2011{smt.1}

Direct Investment Portfolio Investment

12


industries, metal goods, machinery and electronics (Rp3.2

trillion). In terms of FDI, investment realization totaled $1.5

billion for mining, basic chemicals and pharmaceuticals,

$0.6 billion for basic metal industries, metal goods,

machinery and electronics, $0.5 billion for transportation,

storage and telecommunications as well as $0.4 billion for

trade and reparations.

With the inundation of capital flows as well as

the current account surplus, the Indonesian balance of

payments remained solid. Foreign exchange reserves at the

end of Semester I-2011 (June 2011) totaled $119.7 billion

(up from $96.2 billion), which is equivalent to 6.8 months

of imports and government foreign debt repayments.

The rupiah exchange rate continued to strengthen

accompanied by relatively low volatility, increasing by

417 points or 4.64% to a level of Rp8,579 per US$ with

average volatility of 0.15%.

Capital flows into the country, despite reflecting

increased investor confidence in domestic economic

fundamentals, also required vigilance due to the possibility

of a sudden reversal resulting from a change in internal

or external conditions. Vulnerabilities stemming from the

external sector are one element of the government’s and

Bank Indonesia’s focus in 2011.

1.2.3. Government Sector Conditions

The government continued to record a financial

surplus of Rp36.8 trillion, which is slightly down compared

to the same semester of the previous year at Rp47.9

trillion. As a percentage, the highest increase in budget

realisation affected capital expenditure amounting to 25%

(Table 1.2).

StateBudget

Change in State Budget

Realizationup toMay

Realizationup toMay

RealizationSemester I

RealizationSemester I

Details

2010 2011

A. Current Revenues and Grants 992.398,8 355.944,0 443.682,4 1.104902,0 421.084,9 498.268,1

I. Domestic Revenues 990.502,3 355.818,6 443.469,4 1.101.162,5 421.014,0 497.884.8

1. Tax revenues 743.325,9 275.462,2 337.576,2 850.255,5 326.573,3 386.691,7

Tax Ratio – CPI (% to GDP) 11.9 - - 12.1 - -

2. Non-tax Revenue 247.176,4 80.356,4 105.893,2 250.907,0 94.440,7 111.193,1

II. Grants 1.896,5 125,4 213,0 3.739,5 70,9 383,3

B. State Expenditures 1.126.146,5 294.823,0 395.777,5 1.229.558,5 364.208,8 461.487,5

I. Central Government Spending 781.533,5 175.334,9 234.187,9 836.578,2 212.731,7 263.333,4

1. Personnel Expenditure 162.659,0 56.171,9 73.458,6 180.824,9 67.684,3 85.937.1

2. Purchases of Goods 112.594,1 20.719,9 29.306,9 137.849,7 24.221,7 34.196,9

3. Capital Expenditure 95.024,6 12.332,9 16.391,8 135.854,2 13.630,5 20.534,6

4. Interest payments 105.650,2 34.014,2 43.363,8 115.209,2 37.460,8 48.713,1

5. Subsidy 201.263,0 36.867,6 51.733,7 187.624,3 61.891,8 61.965,7

6. Grant Expenditure 243,2 0,0 0,0 771,3 18,7 36,0

7. Social Support 71.172,8 14.638,3 19.059,5 63.183,5 7.246,2 11.053,1

8. Others 32.926,7 590,2 873,7 15.261,0 577,9 896,8

Table 1.2State Budget Realisation in Semester I – 2010-2011

(in billions of rupiah)

13


The realisation of current receipts and grants was

projected to reach Rp498,268.1 billion in Semester I-2011.

Despite an increase of 12.3% on the same period of the

previous year, realisation is only 45.1% of the target set in

the 2011 budget. Likewise, budget realisation in Semester

I-2011 was expected to reach Rp461,487 trillion, which

is 16.6% higher than the same period of the previous

year, however, realisation only reached 37.5% of the

target set.

Despite the small expected impact, if lacklustre

budget realisation is not immediately addressed it could

undermine efforts to stimulate the domestic economy.

Economic stimuli are considered necessary because

domestic consumption is one driver of the Indonesian

economy amid the ongoing threats emanating from the

global crisis.

Government foreign debt and the ability to service

that debt remained favourable, thereby further reducing

potential financial system instability stemming from

external debt. Government foreign debt continued to

increase but at a slower rate than the previous semester.

Currently (the position in June 2011), external debt stands

at $91.3 million, which is equal to Rp776 trillion at a rate

of Rp8,500 per US$, dominated by loans from the non-

IGGI/CGI scheme (Table 1.3).

II. Transfer to Region 344.612,9 119.488,1 161.589,5 392.980,3 151.477,1 198.154,1

1. Fund Balance 314.636,3 116.623,1 153.794,8 334.324,0 134.120,6 173.533,3

2. Fund for Special Autonomy and

Adjustment 30.249,6 2.864,9 7.794,7 58.656,3 17.356,5 24.620,8

C. Primary Balance (28.097,4) 95.135,2 91.268,8 (9.447,3) 94.336,9 85.493,6

D. Budget Surplus/(Deficit) (A-B) (133.747,7) 61.121,0 47.905,0 (124.656,5) 56.876,1 36.780,8

% Deficit to GDP (2,1) - - (1,8) - -

E. Financing (I+II) 133.747,7 44.457,1 54.668,2 124.656,2 63.470,5 67.301,5

I. Domestic Financing 133.903,2 51.300,0 65.131,1 125.266,0 75.369,9 85.945,8

II. Foreign Financing (155,5) (6.842,8) (10.462,9) (609,5) (11.899,4) (18.644,3)

Excess/(Deficiencies) of Financing (0,0) 105.578,1 102.573,2 0,0 120.346,7 104.082,0

Source: Ministry of Finance

The government’s ability to manage its debt is

evidenced by a stable debt service ratio despite a slight

decline compared to yearend 2010 from 24% to 22% in

June 2011. In this context, Indonesia’s foreign exchange

reserves continued to increase, however, the reserves’

ability to cover imports and debt servicing declined slightly

from 7 months to 6.8 months (Table 1.4).

Table 1.3Government Foreign Debt

Jun-09 Dec-09 Jun-10 Dec-10 Jun-11

Total 77.595 83.067 83.246 88.718 91.259

IGGI/CGI 45.898 45.358 44.263 45.922 45.452

Non IGGI/CGI 31.697 37.709 38.983 42.796 45.806

(millions of US$)

14


Source: Bloomberg

Source: Bloomberg

Figure 1.13ROA and ROE of Non-financial Public Listed

Companies

Figure 1.14DER and LL/TA of Non-financial Public Listed

Companies

Table 1.4Debt Service Ratio

Q-I Q-I Q-I

2009 2010 2011

Q-II Q-II Q-IIQ-III Q-IIIQ-IV Q-IV

Foreign exchange reserves 54.840 57.576 62.287 66.105 71.823 76.321 86.551 96.207 105.709 119.655

In months of imports and debt

repayments 5,4 5,7 6,1 6,5 5,2 5,6 6,3 7,0 6,0 6,8

Debt Service Ratio (%) 23% 25% 20% 25% 21% 23% 20% 24% 18% 22%

1.2.4. Corporate Sector Conditions

Stimuli from government consumption continued

to face constraints, however, lower inflation and

exchange rate stability provided optimism for the business

community, as reflected by the financial conditions of non-

financial public listed companies. When compared to the

first quarter of 2010, ROA increased from 2.03% to 2.45%

in Quarter I-2011, which is an increase of 20.34 (yoy).

Meanwhile, ROE improved moderately from 4.26% in

Quarter I-2010 to 4.71% in Quarter II-2011, representing

an increase of 10.65% (Figure 1.13). Optimism was also

reflected by the Business Activity Survey (Quarter I-2011),

which revealed that business players are optimistic of their

business situation for the upcoming six months.

In addition, solid corporate performance was not

undermined by high interest rates in the first quarter of

2011, as demonstrated by corporate resilience to interest

rate hikes (refer to Box 1.1).

The increase in revenues encouraged the corporate

sector to rely more on sources of internal funds to improve

their businesses and rely less on borrowed funds from

banks or the issuance of securities. This is observable from

the downward trend in the debt to equity ratio (DER) from

1.09 (Quarter I-2010) to 0.93 (Quarter I-2011) and the

decline in total liabilities to total assets (TL/TA) in Quarter

I-2011 compared to Quarter I-2010 (Figure 1.14).

0.00

0.20 DER

0.40

0.60

1.00

0.80

1.20

1.40

Q- I

Q- I

IQ

- III

Q- I

VQ

- IQ

- II

Q- I

IIQ

- IV

Q- I

Q- I

IQ

- III

Q- I

VQ

- IQ

- II

Q- I

IIQ

- IV

Q- I

Q- I

IQ

- III

Q- I

VQ

- IQ

- II

Q- I

IIQ

- IV

Q- I

2005 2006 2007 2008 2009 2010

2011

TL/TA

-200

-100

0

100

200

300

400

-200

-100

0

100

200

300

400

Q -

IQ

- II

Q -

IIIQ

- IV

Q -

IQ

- II

Q -

IIIQ

- IV

Q -

IQ

- II

Q -

IIIQ

- IV

Q -

IQ

- II

Q -

IIIQ

- IV

Q -

IQ

- II

Q -

IIIQ

- IV

Q -

IQ

- II

Q -

IIIQ

- IV

Q -

I

2005 2006 2007 2008 2009 2010

2011

% y.o.y% y.o.y

ROA (right scale)ROE (left scale)

15


Against this propitious financial backdrop,

assessments of corporate conditions based on credit

risk and market risk continued to provide assurance. The

expected probability of default in one year for 342 non-

financial public listed firms improved from 2.48% in the

same period of the previous year to 1.93% in the second

quarter of 2011. Furthermore, corporate capital resilience

against the possibility of a sudden reversal and rupiah

appreciation remained strong with a relatively small impact

on non-performing bank loans (refer to Box 1.2).

Rigorous and comprehensive monitoring of the

corporate sector must remain an ongoing concern

considering the transmission and impact of capital outflows

are difficult to predict.

1.2.5. Household Sector Conditions

Risk in the household sector during the first semester

of 2011 was relatively low in harmony with maintained

macroeconomic stability and the continuing global

economic recovery. Household consumption was robust,

driven by strong consumer confidence. Consumer surveys

indicated that the consumer confidence index followed an

upward trend in Semester I-2011, reaching a level of 109

in June 2011 compared to just 103 in December 2010

(Figure 1.16).

Financially the household sector remained solid.

Based on the results of surveys the household gearing ratio

was sufficiently low at 3.61%. Rising food prices at the

beginning of Semester I-2011 did not seem to have any

significant adverse affect on total debt. Based on research,

households in Indonesia tend to overcome food price hikes

by adjusting their consumption behaviour instead of taking

on the burden of more debt. Households tend to focus

on meeting their daily necessities (including food) and

reducing consumption of non-essential items.

A number of other financial indicators like the

current ratio, inventory turnover ratio and collection

period further confirmed such positive performance. The

current ratio increased from 145% (Quarter I-2010) to

163% (Quarter I-2011), while the inventory turnover ratio

declined marginally to a level of 1.86 (Quarter I-2011). The

collection period also experienced a slight decline from

0.40 (Quarter I-2010) to 0.39 (Quarter I-2011), which

indicates that firms were able to accelerate cash receipts

from their operational activities compared to the same

period of the previous year (Figure 1.15).

Source: Bloomberg, processed


Figure 1.15Major Corporate Financial Indicators

Figure 1.16Consumer Confidence Index (CCI)

0123456

ROA

ROE

Inventory Turn Over

DER

2010:Q1

2011:Q1

(Index)140

130

120

110

100

90

80

70

60

16


Accordingly, the household gearing ratio remained

at the low level of below 5% during the first semester

of 2011, which indicated that the level of household

debt is very low compared to total assets. Additionally,

such conditions also demonstrate that the household

sector contributes very little risk to the financial sector

as households have access to sufficient assets in order to

cover their liabilities in the event that household income

falls short.

Credit to the household sector followed an upward

trend in Semester I-2011 coupled by a relatively low level of

risk. The position of credit in June 2011 to the household

sector was Rp362.3 trillion, representing growth of

27.02% (yoy), while the ratio of non-performing loans

remained stable at 2.00% (Figure 1.17).

Source: LBU

Figure 1.19Types of Household Loans

Source: LBU

Figure 1.20Composition of Household Credit in June 2011


Figure 1.17Credit and NPL to the Household Sector

Source: LBU

Figure 1.18Household Non-performing Loans

The majority of loans extended to the household

sector were mortgages followed by motor vehicle loans,

multipurpose loans, loans for housewares and others

(Figure 1.18).

Compared to other types of household loans,

mortgages, multipurpose and motor vehicle loans tended

to increase, while loans for durable housewares and others

remained stable at a low level. Despite strong growth, the

NPL ratio for households was low at less than 5%.

0

Mortgages

3.0%

2.5%

2.0%

1.5%

1.0%

0.5%

Jun

- 10

Jul -

10

Aug

- 10

Sep

- 10

Oct

- 10

Nov

- 10

Dec

- 10

Jan

- 11

Feb

- 11

Mar

- 11

Apr

- 11

May

- 11

Jun-

11

HousewaresMotor vehicle Multipurpose

0

20

40

60

80

100

120

140

160

Rp T

Jun

- 10

Jul -

10

Aug

- 10

Sep

- 10

Oct

- 10

Nov

- 10

Dec

- 10

Jan

- 11

Feb

- 11

Mar

- 11

Apr -

11

May

- 11

Jun-

11

Mortgages HousewaresMotor vehicle Multipurpose

0.00

0.50NPL (left scale)

1.00

1.50

2.00

2.50

3.00

3.50

%

0

50

100

150

200

250

300

350

Rp T

Jun

- 10

Jul -

10

Aug

- 10

Sep

- 10

Oct

- 10

Nov

- 10

Dec

- 10

Jan

- 11

Feb

- 11

Mar

- 11

Apr

- 11

May

- 11

Jun-

11

Credit (right scale)

and others3%

Multipurpose25%

Householdhousewares

1%

Motor vehicle26%

Mortgages45%

17


Box 1.1 The impact of higher interest rates on non-financial,LQ 45 listed companies

Background

Raising the BI rate is expected to elevate lending

rates in general, thereby burdening the corporate sector

with higher interest costs. Stress tests were conducted

on the impact of the interest rate on corporate profit/

loss in order to observe this phenomenon.

Overview of Corporate Sector Financial

Conditions in Indonesia

In general, up to yearend 2010 non-financial

public listed (LQ45) companies posted average profits

of around Rp2.6 trillion, with the exception of one firm

that posted losses of Rp167.2 billion. The composition

of corporate debt was dominated by bank loans

and bonds with respective shares of 55% and 24%;

followed by trade payables at 15%, lease payables

at 3% and other debts totalling 3%. Bank loans and

bonds were dominated by foreign debt (56.92%).

Fixed rate Fixed rateFload rate

*)

Fload rate

Analysis Framework for the impact of higher Interest Rates

Assumed to be fixed.

Bank Loans

Foreign

Interest Costs

LendingRates

BI Rate

Cost before tax

Other Costs *)

Revenue *)

Profit / Loss

ForeignDomestic Domestic

Bonds

18


On average, the total interest cost of LQ45 listed

non-financial companies was low, more specifically

just 3.92% of total costs, despite 10 companies with

interest costs in excess of 10%.

Results of Stress Tests

Stress tests revealed the following:

• A 75-bps increase in lending rates has no

significant impact of corporate profits. On

average, corporate profits declined by just

0.9%.Two firms were sensitive to changes in

the interest rate, which in spite of still posting

a profit, it would be relatively low compared to

the other companies tested at less than Rp300

billion.

• Corporateinterestcostsriseasaresultofhigher

lending rates (assumed to rise by 25bps, 50bps

and 75bps). However, the increase in interest

costs is actually lower than the rise in the interest

rate, namely just 7bps, 13bps and 20bps or less

than 50% of the corresponding rise in the interest

rate.

• Threecompanieswerefoundtobeoutlierswhere

the respective firms experienced an increase in

interest costs that exceeded the rise in the interest

rate. This was because the three companies were

burdened by large domestic debts with high

lending rates.

Total LQ-45

Composition of Foreign and Domestic Debt for LQ45 Companies

Bank loansBonds

Leasing payablesTrade payables

Others

55%24%

3%

15%

3%

TotalAB

TRHGAQUFVNOS

WXJCDY

AHE

MAFZL

AGAEADACAA

KBPI

0% 25% 50% 75% 100%

Domestic Loans Foreign Loans

19


Box 1.2 Assessment of Corporate Resilience

1. Credit Risk: Calculating the Expected

Probability of Default

The expected probability of default (in one

year) for 342 non-financial public listed companies in

Indonesia was calculated in order to assess corporate

resilience to default credit risk. Using this method

revealed that as of Quarter II-2010 the expected

probability of default in one year was 1.93%, which is

an improvement over the previous semester at 2.48%

(refer to the Table below). This is congruous with the

improvement in corporate financial ratios during the

reporting semester.

Nevertheless, although conditions as an aggregate

were relatively sound, several firms displayed marginal

financial conditions for which the potential risk was

larger than the other sample companies. Ten such

companies had a probability of default in excess of

10%, with three even surpassing 20%. In general,

this was due to volatility in the value of equity at the

affected firms.

2. Market Risk: Stress Testing the impact of a

Sudden Reversal on Foreign Loans

A wealth of experience from dealing with

crises, particularly from the crisis in 1997/97 has taught

us that capital outflow, which can occur rapidly and

significantly, has a serious impact on the corporate

sector and the economy of Indonesia. In terms of

capital, exchange rate appreciation and the evaporation

of liquidity leads to firms failing to meet their foreign

debt repayments. A concomitant downgrade in ratings

as well as widespread risk-averse behaviour leads to

domestic banks holding liquidity (a credit crunch).

Regarding trade, rupiah appreciation raises the

prices of imported raw materials and reduces sales

value due to weak domestic and global demand,

which undermines corporate profits and the ability to

service debt.

A number of indicators provide evidence that

corporate conditions as well as foreign exchange

management are currently much better than before

the crisis. Through the monitoring of foreign exchange

flows, Bank Indonesia can more accurately measure

potential risk and, more importantly, internal corporate

conditions are relatively more solid. This is demonstrated

by the declining leverage ratio, greater domestic

corporate funding sources (credit and securities),

increased debt repayment capacity as reflected by the

interest coverage ratio, better liquidity (a current ratio

of 1.4 to 1.6) and the fact that corporate exposure

to externalities is relatively low compared to other

emerging market countries.

The stress tests were designed to measure the

impact of exchange rate appreciation and lower

consumption on corporate capital. Simultaneously,

as an impact of rupiah appreciation, the ability of a

Average Probability of Default for Non-financial Public Listed Companies

SectorQ-I Q-I Q-IQ-III Q-IIIQ-II Q-II Q-IIQ-IV Q-IV

2009 2010 2011

PD 5,28% 5,87% 5,25% 3,70% 2,52% 2,48% 2,31% 2,24% 2,38% 1,93%

20


firm to service its foreign and domestic debts is also

measured.

Data

Stress tests were conducted on 338 non-financial

public listed companies, of which 16 suffered from

negative equity and just 64 had outstanding foreign

loans. Total foreign loans of these 64 firms amounted

to Rp70 trillion (plus interest assumed at 5.5% and an

exchange rate of Rp8,563 per US$), while the capital

totalled Rp211 trillion. Of these 64 companies, 57 also

had outstanding domestic loans totalling Rp37 trillion

(plus interest assumed at a rate of 13%). A total of

185 firms had only domestic loans, totalling Rp86.5

trillion (plus interest assumed at 13%) with capital

amounting to Rp477 trillion.

Results of the Stress Tests

1. The impact of lower sales on profit/loss:

Taken as a whole, the impact of exchange rate

appreciation and lower sales was relatively

negligible at just a 1% decline in corporate

capital. Domestic trade-oriented businesses that

imported raw materials experienced the greatest

decline in capital of -3%. Export-oriented firms,

which imported raw materials, experienced a -2%

decline in capital. Meanwhile, export-oriented

firms that utilised locally sourced raw materials

experienced the smallest decline in capital of just

-1%.

2. Impact on debt repayment capacity:

• Results of the stress tests on firmswith

foreign and domestic loans.

Prior to the stress tests of 57 firms with

outstanding foreign and domestic loans,

The Scheme of the Stress Tests

Impact on Sales• Pricesofimportedrawmaterialsrise• Exportcompetitivenessincreases

Impact on Capital• Totalforeignliabilitiesincrease• Corporateratingsdowngradedandcreditcrunch

occurs

THE CORPORATE SECTOR

Corporate Capital

Impact of Profit/Loss

Non-performing

bank loans

Impact on foreign and domestic loans

As many as 25%, 50% and 100% of domestic loans mature

of the total outstanding.

Scenario1. Domestic market oriented firms that import

raw materials experience a 50% decline in profits.

2. Export-oriented firms that import raw materials experience a 25% decline in profits.

3. Export-oriented firms that source local raw materials experience a 10% decline in profits.

Scenario1. The US dollar exchange rate increases to

Rp10k, 12k and 16k.2. Risk premium increases by 866bps.3. As many as 25%, 50% and 100% of

foreign loans mature.

21


Firms with Outstanding Foreign and Domestic Loansassuming 100% Repayment

Normal Condition

0% 100%

ExchangeRate

Rp10.000

ExchangeRate

Rp12.000

ExchangeRate

Rp16.000

Number of firms with negative equity 3 19 2 2 1

Outstanding domestic loans (billions of rupiah) 2.142 13.364 467 109 825

Cumulative

Number of firms with negative equity 3 22 24 26 27

Outstanding domestic loans (billions of rupiah) 2.142 15.506 15.973 16.082 16.907

Firms with Outstanding Domestic Loans

0% 25% 50% 100%

Number of firms with negative equity 7 2 8 20

Outstanding domestic loans (billions of rupiah) 165 529 12.088 20.662

Cumulative

Number of firms with negative equity 7 9 17 37

Outstanding domestic loans (billions of rupiah) 165 694 12.782 33.444

three suffered from negative equity. A

scenario of forcing these firms to repay

100% of their outstanding foreign loans

and then 100% of their domestic loans

was used in the stress phase. Under

normal conditions (an exchange rate of

Rp8,563 per US$, interest at 3.5% and a

2% risk premium), a total of 22 firms had

insufficient capital to service their domestic

loans with potential non-performing loans

reaching Rp15.5 trillion. Under the worst-

case scenario (an exchange rate of Rp16k),

the number of firms unable to service their

domestic loans jumped to 27 with potential

NPL amounting to Rp16.9 trillion.

• Results of stress tests on firmswith only

domestic loans.

For companies with only outstanding

domestic loans a scenario of repayments

of 25%, 50% and 100% was used with

the assumption of 15% interest.

Prior to the stress tests of 185 firms with

domestic loans, seven had negative equity

with outstanding debts plus interest

totalling Rp165 billion. Under the worst-

case scenario of repaying 100% of the

domestic loans, the number of companies

that did not have sufficient capital to service

their domestic debt was 37 with potential

NPL of Rp33.4 trillion.

23

Chapter 2. Financial System Resilience

Chapter 2Financial System Resilience

24



25


Chapter 2 Financial System Resilience

2.1. FINANCIAL SYSTEM STRUCTURE AND

RESILIENCE

The banking industry continued to dominate the

financial system in Indonesia, which can be demonstrated

by the total assets that have been accrued. With a share of

78.2% of financial institutions’ total assets, the banking sector,

consisting of commercial banks and rural banks, dominates

the financial system in Indonesia. Other financial institutions

that play a salient role include insurance companies, finance

companies and pension funds (Figure 2.1).

Source: Bank Indonesia, Ministry of Finance

Figure 2.1Composition of Financial Institutions’ Assets

Institutions Numbers

Table 2.1Number of Financial Institutions

Commercial Bank 121

Rural Bank 1,682

Insurance 142

Pension Funds 282

Finance Company 192

Venture Capital 71

Securities 113

Mutual Funds** 642

Credit Guarantee Company 4

Pawn Broker 1

*) Data for commercial banks and rural banks as per June 2011, data for other institutions as per December 2010.

**) Investment Collectives, not institutions

The dominance of the banking industry is also

manifest in the number of institutions, particularly rural

banks. Meanwhile, the number of commercial banks is

relatively small compared to other institutions like pension

funds, finance companies and insurance companies. With

77.0%

1.2%9.8%

2.5%5.5%

0.1%0.7% 2.8% 0.1% 0.4%

Commercial BanksRural BanksInsurancePension FundsFinanceCompaniesVenture Capital

SecuritiesMutual Funds**Credit GuaranteeCompanies

*) Data for commercial banks and rural banks as per June 2011, data for other institutions as per December 2010.

**) Investment Collectives, not institutions

Pawn Brokers

The improved performance of financial institutions and markets during Semester

I-2011 helped create financial system stability. A decline in the Financial Stability

Index, which is evidence of greater financial system stability during the reporting

semester, was attributable to relatively well maintained bank resilience as well as

controlled volatility on the domestic stock and bond markets. Financial system

stability was also accompanied by improvements in the intermediation function,

an easing of credit risk and greater bank profitability. Such positive achievements

were inseparable from the array of micro and macroprudential policies instituted

by Bank Indonesia. However, vigilance was also required in terms of liquidity risk

and market risk, which intensified slightly at the end of Semester I-2011 due to

widespread uncertainty surrounding the crisis recovery and budget deficits in the

US and Europe.

26


a relatively small number but large assets to manage,

commercial bank management requires upmost prudence.

The total assets of commercial banks grew by 6.2% in

Semester I-2011, which exceeds that posted in the same

period of the previous year at 5.7% (Table 2.1).

Financial sector resilience was well maintained during

the reporting semester, which was evidenced by a drop in

the financial stability index (FSI) from 1.75 (December 2010)

to 1.65 (June 2011). Notwithstanding, the FSI in June 2011

was in excess of the 1.60 projected.The dip in the financial

stability index was due to relatively well maintained bank

resilience as well as less volatility on the domestic bourse,

which was bolstered by solid domestic fundamentals

and controlled inflation. Potential indirect threats from

the economic crises in Europe and the US led to the FSI

exceeding projections in June 2011 (Figure 2.2).

5.84% (a slight decline on the previous semester at

6.00%). Loans and SSB contributed the smallest shares

with just 1.17% and 0.91% respectively (Figure 2.3).

2.2. RISK IN THE BANKING SYSTEM

2.2.1. Funding and Liquidity Risk

Deposits

Bank funding remained heavily dependent upon

deposits during the first semester of 2011. The share of

deposits as a source of bank funding declined moderately

from 91.93% in the previous semester to 87.99%, while

other sources like interbank funding only contributed

Bank deposits increased by Rp99.19 trillion or 4.24%

in the first semester of 2011, which is less than half of the

increase reported in Semester II-2010 totalling Rp242.79

trillion or 11.58% (Figure 2.4).

Based on ownership, personal accounts experienced

a slight decline of 0.63% in the reporting semester.

Conversely, such accounts actually grew in the previous

semester by 15.59%. The growth in deposits was primarily

due to increases in local government accounts and private

business accounts amounting to 120.67% and 3.76%

respectively (Figure 2.5).

Figure 2.2Financial Stability Index 1996-2011

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

19

96

M0

1

19

96

M0

7

19

97

M0

1

19

97

M0

7

19

98

M0

1

19

98

M0

7

19

99

M0

1

19

99

M0

7

20

00

M0

1

20

00

M0

7

20

01

M0

1

20

01

M0

7

20

02

M0

1

20

02

M0

7

20

03

M0

1

20

03

M0

7

20

04

M0

1

20

04

M0

7

20

05

M0

1

20

05

M0

7

20

06

M0

1

20

06

M0

7

20

07

M0

1

20

07

M0

7

20

08

M0

1

20

08

M0

7

20

09

M0

1

20

09

M0

7

20

10

M0

1

20

10

M0

7

20

11

M0

12

01

1M

07

Global Crisis (Nov 2008): 2,43

1,91

1,45

Asia Financial Crisis1997/1998: 3,23

Mini Crisis 2005: 2,33

FSI 1996 - 2011

Dec 2011: 1,68June 2011 : 1,65

Source: LBU report, Bank Indonesia

Figure 2.3Shares of Bank Funding and Financing

87.99%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Funding Placement

Credits58.57%

SSB 8,40%

BI18,52%

Inter Bank 5.65%

Deposits

Inter Bank 6.00%


Figure 2.4Growth in Deposits by Semester

0

100

50

250

200

150

300

0

6%

4%

2%

12%

10%

8%

14%

Sem II - 08 sem I - 09 Sem II - 09 Sem I - 10 Sem II - 10 Sem I - 11

T Rp

Nominal growth on the left scale Percentage growth on the right scale

27


exceeded growth in liquid assets (Figure 2.6). As of June

2011, total liquid assets increased by just 3.49% (ytd)

to Rp897.42 trillion. The increase came mainly from a

21.97% surge in primary reserves consisting of cash and

checking accounts held at Bank Indonesia in order to meet

the new LDR statutory reserve requirement (March 2011)

and reserve requirement for foreign exchange (5% in

March 2011 and 8% in June 2011). Meanwhile, secondary

and tertiary reserves decreased by 3.15% and 2.21%

respectively in Semester I-2011 (Table 2.2).

By component, the largest increase in deposits

was in the form of checking accounts and term deposits

with growth totalling 5.99% and 4.70% respectively. In

comparison, the strongest growth recorded in the previous

semester was 20.03% and 11.08% for savings accounts

and term deposits respectively. The increase in term

deposits indicates that the general public are confident

in the domestic economic outlook despite volatility in the

global economy.

Based on currency, growth in deposits was contributed

almost entirely by rupiah denominated deposits with foreign

currency denominated deposits actually experiencing a

decline. During the reporting period rupiah deposits grew

by Rp102.45 trillion and foreign currency denominated

deposits declined by Rp3.26 trillion.

Liquidity Risk

Bank liquidity continued to increase during the first

semester of 2011 amid lingering pressures on the global

financial markets. However, the adequacy of liquid assets

in view of deposit withdrawals actually declined marginally

in line with the growth in deposits (4.24% ytd), which

ytd Growth

Nominal(Rp T)

Nominal(Rp T)

% %

yoy Growth

Table 2.2Liquid Asset Growth

Primary Reserves 49.77 21.97 124.16 81.60

Secondary Reserves (17.86) (3.15) 71.86 15.07

Tertiary Reserves (1.64) (2.21) (7.88) (9.82)

Total 30.27 3.49 188.14 26.53

The decline in secondary reserves was principally

due to the maturity of Bank Indonesia certificates (SBI),

meanwhile the tenor of SBI was extended (to nine months),

which led to a shift in bank liquidity from SBI to other

instruments like term deposits and FASBI. Term deposits

were also relatively long term (average tenor of more


Figure 2.5Deposit Growth based on Ownership

0

250

200

150

100

50

-50

-100Central

GovernmentLocal

GovernmentPersonal Private

FinancialInstitution

PrivateBusiness

PrivateOther

Non-Resident

T Rp

semester I-2011 semester II-2010

Figure 2.6Composition of Bank Liquid Assets

0

600 1000

900

800

700

600

500

400

300

200

100

0

Rp T Rp T

500

400

300

200

100

Jun

- 10

Jul -

10

Aug

- 10

Sep

- 10

Oct

- 10

Nov

- 10

Dec

- 10

Jan

- 11

Feb

- 11

Mar

- 11

Apr -

11

May

- 11

Jun-

11

Primary ReservesTertiary Reserve

Secondary ReserveLiquid Assets (right)

Congruent with the trend over preceding years,

growth in deposits during the first half of the year was

surpassed by that in the second.

28


than six months), which limited growth in other Bank

Indonesia instruments to just 1.75% in Semester I-2011

(Figure 2.7).

performed impressively during the first half of 2011. Credit

grew by 10.5% (ytd) in Semester I-2011 or by 23.0% year

on year, which is higher than that posted in Semester

I-2010 at 10.3% but lower than in Semester II-2010. The

acceleration in credit growth was linked to increasingly

conducive economic conditions that permitted the banks to

extend credit primarily to productive sectors (Figure 2.8).

In harmony with the conditions mentioned above,

liquid asset adequacy to anticipate deposit withdrawals

diminished slightly compared to the preceding semester

but remained at a sufficient level (ratio of liquid assets to

deposits > 100%). The ratio of liquid assets to deposits

declined in Semester I-2011 from 37.08% (December

2010) to 36.8% (June 2011). When compared to

conditions at the end of 2008, the liquidity adequacy of

individual banks to cover non-core deposits1 is currently

much improved. In this context, more banks maintained

a ratio of liquid assets to non-core deposits in excess

of 100% in Semester I-2011 and no banks fell below

50%.

2.2.1 Credit Risk and Performance

Credit Performance

As a result of several policies introduced by Bank

Indonesia, for instance the application of an LDR-based

reserve requirement as well as mediation efforts among

those parties involved in the credit process, bank credit

1 Non-core deposits consist of 30% checking accounts, 30% savings accounts and 10% term deposits of less than 3 months.

Figure 2.7Share of Bank Placements at Bank Indonesia

0

100%

T Rp

90%

80%

70%

60%

50%

40%

30%

20%

10%

Jun

- 10

Jul -

10

Aug

- 10

Sep

- 10

Oct -

10

Nov -

10

Dec -

10

Jan

- 11

Feb

- 11

Mar

- 11

Apr -

11

May

- 11

Jun

- 11

BI Checking AccountPlacements in other BI instruments

Bank Indonesia Certificates (SBI)

Figure 2.8Credit Growth by Currency

0%

5%

10%

15%

20%

25%

Rupiah Foreign Currency Total

Sem I-10 Sem II-10 Sem I-11

10.7%9.7% 9.9%

8.0%

21.0%

13.6%

11.3%10.3% 10.5%

Solid credit growth during the first semester of

2011 was driven by foreign currency denominated credit,

expanding by 13.6%, which is far in excess of that recorded

in the same period of the previous year at 8%. Rapid

growth in foreign currency denominated credit began in

Semester II-2010, which was linked to rupiah appreciation.

Therefore, banks must remain cautious of potential rupiah

depreciation, which could undermine debtor repayment

capacity and lead to non-performing loans. Sources of

financing for foreign currency denominated credit in

Semester I-2011 seemed to originate from liquidating

short-term interbank placements in foreign currency, while

foreign currency deposits actually experienced negative

growth. Ongoing global economic instability coupled with

relatively high domestic interest rates compared to other

countries encouraged banks to favour foreign currency

funds for domestic credit. Consequently, banks must

29


reported stronger growth compared to the same period

in the previous year, with the exception of mining (Figure

2.11).

Sumber:

Figure 2.9Credit Funding by Currency

remain cautious because additional losses will be incurred

from the exchange rate in the event of a mismatch (Figure

2.9).

10 30 50 Rp T(70) (50) (30) (10)

(3,3)

0,9

(50,7)

Aset

Liabilities

Loans

Interbank(Net)

Placement at BI

Other Liabilities

Borrowing

Total Deposits

7,7

29,0

37,3

75%

12%

1 month

4%

3%

6%

1 - 3 months3 - 6 months6 - 12 monthsover 12 months Sumber:

Figure 2.10Credit Growth by Type

0%

4%

8%

6%

2%

12%

10%

18%

20%

14%

16%

Working Capital Credit Investment Credit Consumption Credit


8.1%

15.8%

6.8%

13.1%

16.8%

3.5%

9.7%

12.1% 12.3%

Similar to the previous semester, the ascendancy

of credit extended to productive sectors remained in the

first semester of 2011. Working capital credit tended

to dominate in Semester II-2010 with investment credit

playing a more significant role in Semester I-2011, posting

growth of 16.8% ytd and 20.8% yoy. The expansion of

investment credit is hoped to provide more benefits to the

real sector and ultimately contribute more substantially to

the national economy (Figure 2.10). Nevertheless, banks

must remain vigilant of investment credit risk due to its

longer-term nature, especially when considering that the

majority of banks’ funding sources are still short term.

Such conditions have the potential to exacerbate the risk

of a mismatch. By sector, nearly all productive sectors

Figure 2.11Credit Growth by Economic Sector

80%

70%

60%

50%

40%

30%

20%

10%

0%

-10%

-20%

Agric

ultur

e

Mini

ng

Sem I-10Sem II-10Sem I-11

Indus

trial

Electr

icity

Cons

tructi

on

Trad

e

Lives

tock

Busin

ess

Servi

ces

Socia

lSe

rvice

s

Othe

rsGrowth in property credit, which slumped in 2009,

began to rebound in the middle of 2010 and posted

10.1% (ytd) growth in Semester I-2011 or 17.8%

yoy. Growth in the reporting semester surpassed that

in the previous two semesters primarily due to stable

macroeconomic conditions. With the housing requirement

of the population still largely unfulfilled, property credit

and, in particularly, mortgages will continue to grow. The

current share of property credit in total bank credit remains

relatively insubstantial at around 13.2% (Figure 2.12).

30


Credit Risk2

Bank credit risk during the reporting semester

increased marginally when compared to Semester II-2010

but remained under control. The gross NPL ratio reached

2.7% at the end of Semester I-2011, which is up slightly

when contrasted against the position in December 2010

at 2.6%. An Rp8.2 trillion increase in total NPL occurred in

Semester I-2011, which is about 4.4% of the total increase

in bank credit during the period. Despite robust bank credit

growth the gross NPL ratio only increased slightly. Banks

bolstered their loan loss provisioning by Rp4.2 trillion (up

6.8% of yearend 2010) in order to anticipate a potential

escalation in credit risk (Figure 2.13).

Banks faced a potential increase in foreign currency

credit risk in Semester I-2011 as a consequence of solid

foreign currency credit growth. Historically, the NPL ratio

of foreign currency credit has exceeded 30% (in the year

2000) as a result of fallout from the 1997/98 crisis and is

far in excess of the NPL ratio of rupiah denominated credit.

However, the recent performance of foreign currency

credit has demonstrated marked improvements. The NPL

ratio of foreign currency loans has remained below that

of rupiah based credit and in June 2011 was at a level of

2.2%, while the NPL ratio of rupiah credit was 2.8% (Figure

2.14). This is the result of a decline in total non-performing

loans over the past three reporting semesters. In Semester

I-2011, total NPL of foreign currency loans dropped by

10%, therefore, banks could control the potential for an

escalation in credit risk stemming from greater allocation

of such loans. Currently, credit risk pressures appear more

prevalent for rupiah based loans, which experienced a

whopping 23.8% increase in NPL during the reporting

semester (Figure 2.15).

Figure 2.12Growth and Share of Property Credit

Figure 2.13Non-Performing Loans (NPL)

2 Excluding channeling unless otherwise stated.

80%

70%

60%

50%

40%

30%

20%

10%

0%

16%

14%

12%

10%

8%

6%

4%

2%

0%

Growth of Property Loans y.o.y(left scale)

2004 2005 2006 2007 2008 2009 2010 2011

Share of Property Loansto total loans(right scale)

2007 2008 2009 2010 2011

6

%

5

4

3

2

1

0

60

Rp T

50

40

30

20

10

0

Loan loss provisions(right scale)

NPL Nominal(right scale)

Gross NPL(left scale)Net NPL

(left scale)Sumber: Bloomberg

Figure 2.14NPL Ratio by Currency

2007 2008

Ratio NPL Rp Total NPLRatio NPL Va

2009 2010 2011

9

%

8

7

6

5

3

4

2

1

0

31


Based on the type of credit, total non-performing loans

increased for all types of credit during the first semester

of 2011, with the most significant growth affecting

consumption credit. The growth in non-performing

loans for consumption credit stemmed primarily from

consumption credit for households, multipurpose loans

and other consumption loans (Figure 2.16). However, the

gross NPL ratio of consumption credit was the lowest for

all other types of loan at just 1.9% (Figure 2.17).

With the increase in investment credit, banks

must maintain prudential guidelines when extending

this particular type of loan. With a longer-term period

compared to other forms of credit, investment credit is

inherently more prone to credit risk. Historical data shows

that investment credit has had a higher gross NPL ratio

than other forms of credit since the year 2000. Only

after entering 2009 has the NPL ratio of investment credit

slipped below that of working capital credit. Total nominal

non-performing loans for investment credit in Semester

I-2011 grew by 19.1%, thus leading to a gross NPL ratio

of 2.5%, which is up slightly compared to the position at

yearend of 2.4%. Credit risk associated with investment

loans is expected to remain under control if its allocation

continues to adhere to prudential principles.

Figure 2.16NPL Growth by Loan Type

Sumber:

Figure 2.15NPL Growth by Currency

30%

25%

20%

15%

10%

5%

0%

-5%

-10%

-15%

-20%


Rupiah Foreign Currency Total

3.0%

-4.8%

23.8%

-15.2%

-2.3%

-10.0%

-0.5%-4.4%

18.2%

-20%

-10%

0%

-5%

-15%

10%

5%

25%

30%

15%

20%

Working Capital Credit Investment Credit Consumption Credit


-3.1%

6.4%

15.4%

5.0%

19.1%

-17.3% -17.4%

1.0%

25.5%

Figure 2.17NPL Ratio by Loan Type

2007 2008 2009 2010 2011

%

12

9

6

3

0

InvestmentCredit

WorkingCapital Credit

ConsumptionCredit

Figure 2.18aNPL Ratio by Economic Sector

2007 2008 2009 2010 2011

%

10

8

6

4

2

0

AgricultureIndustri Pengolahan

ConstructionMining

Electricity

32


Figure 2.19NPL Ratio of Property Credit

2.3.3 Profitability and Capital

Profitability

In harmony with improved domestic economic

conditions, the profitability of the banking industry

increased during the reporting semester. The banking

sector posted net profits of Rp37.10 trillion in Semester

I-2010, which is higher than that posted in the previous

sector and represents 64.74% of net profits for 2010 as

a whole. The rise in profits was driven by strong credit

growth (10.47% ytd) and is reflected by a high ROA of

around 3.07% in June 2011 (Table 2.3).

Tabel 2.3Profit/Loss of the Banking Industry

Jun-10 Jun-11Dec-10

Operational profit/loss 23.19 48.33 26.08

Non-operational profit/loss 16.12 427.73 20.49

Before taxes profit/loss 39.31 76.06 46.57

After taxes profit/loss 29.33 57.31 37.10

T Rp


2007 2008 2009 2010 2011

%

10

8

6

4

2

0

Business ServicesTransportation

TradeOthers

Social Services

2003 2004 2005 2007 2008 20102006 2009 2011

16%

14%

12%

10%

8%

6%

4%

2%

0%

MortgagesConstruction

Real EstateProperty Total

The agricultural, mining, manufacturing, processing,

construction as well as transportation and communications

sectors all experienced an increase in non-performing

loans during the reporting semester. Of these sectors, the

transportation and communications sector has experienced

an increase in non-performing loans for the past three

semesters (Figure 2.18).

Figure 2.18bNPL Ratio by Economic Sector

The risks inherent with property credit have

remained under control, although the ratio was slightly

above that for total credit as a whole (3.0% as of June

2011) but following a downward trend. The increase in

non-performing property loans during Semester I-2011

primarily stemmed from mortgages, however, the NPL ratio

or mortgages has remained relatively low at just 2.5% as of

June 2011. Consequently, the rise in total non-performing

loans is still manageable by the banks (Figure 2.19).

Up until the end of Semester I-2010, the composition

of bank profit was dominated by operational profit, for

which the total was Rp26.08 trillion or 56% of total

profit. Notwithstanding, the share of operational profit

to total profit actually followed a downward trend (Figure

2.20).

The prominence of operational profit was due to an

increase in net interest income (NII). The average monthly

net interest income for banks during the first semester of

2011 was Rp13.93 trillion, which surpassed that recorded

in Semester I-2010 (Rp12.18 trillion) and Semester II-2010

(Rp12.79 trillion). This indicates the banks’ efficiency in

supressing interest expenses, while raising their interest

income.

33


The share of interest income from credit remained

dominant at 80.95% (June 2011) of total interest income,

however, the share has tended to decline when compared

to June 2010 (81.06%) and December 2010 (81.03%)

(Figure 2.21).

In order to improve transparency and good

governance in the setting of bank lending rates, Bank

Indonesia issued SE No. 13/5/DPNP dated 8th February

2011 regarding transparent base lending rates, which

became effective on 31st March 2011. One aim of this

policy was to enhance market discipline and make pricing

loan products more efficient. The performance of this

policy is elaborated upon in Box 2.1.

Improved bank efficiency has raised bank

productivity and profit. ROA increased from 3.0%

(Semester I-2010) and 2.86% (yearend 2010) to 3.07%

at the end of the reporting semester. This increase in ROA

was driven by greater bank efficiency as reflected by the

efficiency ratio, which achieved 85.92% in Semester I-2011

compared to 90.47% in Semester I-2010 and 86.14% at

yearend 2010 (Figure 2.23).

Figure 2.20Bank Profit/Loss

0

10

20

30

40

50

50

70

60

50

40

30

20

10

0

60

T Rp %

2007

Operational Profit/Loss (left scale)

2008 2009 Jun’10 Dec’10 Jun’11

Non-operational Profit/Loss (left scale)

Share of Operational Profit/Loss (right scale)

Figure 2.21Composition of Interest Income in

the Banking Industry (%)

BI SSB OthersCredits

3,19

81,06

9,35

120

100

80

60

40

20

Jun’10 Dec’10 Jun’11

06,40

8,796,75

3,43 3,81

80,95

7,098,15

81,03

A narrower interest rate spread led to a smaller

share of interest income from credit against total interest

income. This is a positive indication that banks prioritised

credit volume over widening interest rate spread in their

pursuit of higher income. Narrower spread also led to a 1

bps decline in Net Interest Margin (NIM), more specifically

from 5.80% in June 2010 to 5.79% in June 2011 (Figure

2.22).

Figure 2.22Interest Rate Spread in Rupiah (%)

Figure 2.23Bank ROA and Efficiency Ratio (%)

2007 2008 20102009 2011

8.0

7.0

7.5

6.5

6.0

5.5

5.0

4.5

4.0

3.5

2007 2008 Jun-10 Dec-102009 Jun-11

3.5

3.0

91.0

90.0

89.0

88.0

87.0

86.0

85.0

84.0

83.0

82.0

2.5

2.0

1.5

1.0

ROA Efficiency Ratio

34


Capital

The banking industry maintained sound resilience

during Semester I-2011. The average capital adequacy ratio

(CAR) during the reporting semester was 17.53%, which

exceeded that in Semester II-2010 but was below the level

in Semester I-2010 (18.31%). The rise in average CAR

over the preceding semester was due to capital growth

outpacing the increase in risk-weighted assets. Average

capital in Semester II-2010 increased by Rp68.44 trillion or

22.38% compared to the previous semester. Meanwhile,

average risk-weighted assets expanded by just Rp314.24

trillion or 17.26% during the same period (Figure 2.24).

Figure 2.24Bank Capital, Risk-Weighted Assets and CAR

Figure 2.25CAR by Bank Group (%)

2007 2008 Jun-10 Dec-102009 Jun-11

3,000T Rp

2,500

19.50

Percent

19.00

18.50

18.00

17.50

17.00

16.50

16.00

15.50

15.00

2,000

1,500

1,000

500

-

Risk-weighted assets (left scale) Capital (left scale)

CAR (right scale)

State ownedbanks

2008

Private banks Joint Venturebanks

Foreign BanksRegional banks(BPD)

35

30

25

20

15

10

5

0

2009 Jun’10 Dec’10 Jun’11

Micro, Small and Medium (MSM) Credit

MSM credit continued to contribute the largest

share to total bank credit in the reporting semester. In

June 2011 the share of MSM credit to total credit reached

53.06% compared to 52.68% in June 2010 and 52.48%

in December 2010. At the end of the first semester

2011 MSM credit grew by 11.69% ytd and 23.85% yoy,

while non-MSM credit grew more slowly at 9.12% ytd.

Nevertheless, MSM credit growth experienced a moderate

slowdown in June 2011 when compared to June 2010

both in terms of year-to-date and year-on-year (Figure

2.26).

The gross NPL ratio remained under control at just

2.87% as of June 2011 in spite of solid MSM credit growth,

which is actually higher than that posted in June 2010

(2.82%) and December 2010 (2.60%). Such circumstances

were one of the reasons behind the banks’ decision to

allocate more MSM credit and encourage more banks to

enter the MSM3 sector (Figure 2.27).

3 MSM credit data does not incorporate credit cards or rural banks/sharia rural banks, including sharia commercial banks/sharia business units.

Based on bank groups, in June 2011 foreign banks

maintained the highest level of CAR (25.29%), followed

by joint-venture banks (22.0%), while regional banks

(14.24%) and private banks (15.66%) had the lowest

level. The capital adequacy ratio of state-owned banks

was 16.43%. Such conditions were due to strong credit

growth at private banks, regional banks and state-owned

banks, while credit growth at joint-venture and foreign

banks was relatively low. Only the capital adequacy ratio

for state-owned banks followed an upward trend while

the other four types of bank followed a downward CAR

trend, with the downtrend for foreign banks the most

pronounced (Figure 2.25).

35


Figure 2.26MSM Credit (yoy)

2007 2008 2010 20112009

MSM

50

%

40

30

20

10

-

(10)

Non MSM Credits

In Semester I-2011, widespread investor optimism

followed the relatively stable global economic recovery,

which led to a deluge of foreign capital inflows to rupiah-

based financial instruments (Bank Indonesia certificates

(SBI), Government Bonds (SUN) and Stock) totalling

Rp64 trillion (compared to Rp56.31 trillion in Semester II-

2010). The majority of the capital flowed to government

bonds (SUN) as well as net share purchases amounting to

Rp39.32 trillion and Rp18.03 trillion respectively. In the

second quarter of 2011 investor interest in Bank Indonesia

certificates (SBI) waned subsequent to new regulations

stipulating a minimum six-month holding period, which

gave trading investors less room to manoeuvre and

triggered a switch in portfolio from SBI to SUN and shares

(Figure 2.28). The share of foreign ownership in SBI swelled

from 27.45% in December 2010 to 33.12% in June 2011,

while foreign ownership in tradable government securities

(SBN) also expanded from 29.93% (December 2010) to

33.01% (June 2011). In addition, the position of foreign

shares also increased from 32.29% in December 2010 to

35.88% in June 2011. Inflows persisted at the beginning

of Semester II-2011, up to August. The upsurge in short-

term foreign investment led to rupiah appreciation, which

could potentially spark a correction in the event of a capital

reversal (Figure 2.29).

2.3. POTENTIAL FINANCIAL MARKET RISK AND

FINANCING

2.3.1. Potential Financial Market Risk

Foreign Portfolio: SBI, SUN and Stock

Figure 2.27Gross NPL Ratio of MSM Bank Loans (%)

2007 2008 2010 20112009

MSM

8

9

7

6

5

4

3

2

Non MSM

Figure 2.28Foreign Investor Placements: SBI, SUN, Stock

Q - I Q - II Q - IV Q - I Q - II Jul-Aug 11

2010 2011

Q - III

SBI

22.00

T Rp

18.00

14.00

10.00

2.00

6.00

-2.00

-6.00

-10.00

-14.00

-18.00

SUN Stock

Sumber: Bloomberg

Figure 2.29Foreign Portfolio in Rupiah Financial Instruments

(SBI, SUN, Stock)

Q - III Q - IV Q - II Q - III Q - IV Q - I Q - II Jul-Aug11

20102009 2011

Q - I

T Rp

-10.00

55.0050.00

45.0040.0035.0030.0025.00

20.0015.0010.005.000.00

-5.00

28.6323.74

44.77

17.11

53.23

3.08

35.07

28.94

2.26

36


Figure 2.30Average Monthly SUN Price

Figure 2.31Price of Benchmark SUN FR Series

90

95

100

105

110

115

120

125

Short-term < 5 years

Long-term > 7 years

Medium-term 5 to 7 years

Average of two monthly

Aug’

10

Sep’

10

Oct’1

0

Nov’1

0

Dec’1

0

Jan’

11

Feb’

11

Mar

’11

Apr’1

1

May

’11

Jun’

11

Jul’1

1

Aug’

11

105

110

115

120

85

90

95

100

70

75

80

FROO55FROO53

FROO56FROO54

IDMA

11/29/2010

8/22/2011

8/8/2011

7/25/2011

7/11/2011

6/27/2011

6/13/2011

5/30/2011

5/16/2011

5/2/2011

4/18/2011

4/4/2011

3/21/2011

3/7/2011

2/21/2011

2/7/2011

1/24/2011

1/10/2011

12/27/2010

12/13/2010

Government Bond Market

Table 2.4SUN Value at Risk (VaR)

PeriodsShortterm

Mediumterm

Longterm

June 10 0.361 0.808 0.930

July 10 0.354 0.792 0.913

Aug 10 0.304 0.724 0.883

Sept 10 0.315 0.704 0.882

Oct 10 0.309 0.685 0.962

Nov 10 0.323 0.702 1.137

Dec 10 0.338 0.720 1.191

Jan 11 0.366 0.906 1.462

Feb 11 0.370 0.920 1.477

Mar 11 0.371 0.928 1.476

Apr 11 0.380 0.983 1.477

May 11 0.357 0.874 1.376

June 11 0.332 0.843 1.345

0.42%) respectively. In contrast, long-tenor SUN (>7 years)

rallied 245 bps (up 2.12%). High inflation expectations at

the outset of the current year amplified potential SUN risk,

which gradually stabilised after Bank Indonesia raised its

policy rate in order to dampen expectations. Based on VaR,

most potential risk emanated from long-tenor SUN, which

spiked in Semester I-2011 (Figure 2.30 and 2.31).

The average SUN price climbed 1.14% to 108.01

during the second semester of 2011, particularly in August.

Based on tenor, however, higher prices mainly affected

medium-tenor (5-7 years) and long-tenor (>7 years)

SUN with hikes of 177 bps (up 1.56%) and 913 bps (up

7.8%) correspondingly. Conversely, the average price of

short-tenor (<5 years) SUN declined by 238.62 bps (down

2.18%) (Table 2.4 and Figure 2.32).

Based on the Inter Dealer Market Association

(IDMA) index, the price of government bonds (SUN)

dropped by around 4.11% to 101.69 in Semester I-2011

due to widespread high inflation among emerging

market countries at the beginning of the semester as a

consequence of economic overheating and the soaring

oil price. Investors exploited this issue for profit taking

activities. In 2010, the IDMA index rallied 12.38% (yoy).

In the reporting semester, the average price of SUN fell

in the range of 102.26 (21/1) and 115.90 (4/1). Based

on tenor, the average price of short-tenor (<5 years) and

medium-tenor (5-7 years) monthly SUN slumped the most

significantly by 228 bps (down 2.8%) and 48 bps (down

37


From the beginning of Semester II-2011 until August

of the same year, government bonds increased by 9.79%

to Rp703.98 trillion, with foreign investors accounting for

Rp52.08 trillion (foreign SBN portfolio achieved 35% of

total outstanding SBN) (Table 2.5). Foreigners continued to

dominate SUN ownership in Semester II-2011. The increase

that occurred in August is an indication of further foreign

ownership of government bonds in upcoming quarters

(Figure 2.33).

Stock Market

Sumber:

Figure 2.32SUN Value at Risk (VaR)

0.000

1.600

1.400

1.200

1.000

0.800

0.600

0.400

0.200

Aug 10 Sep 10 Oct 10 Nov 10 Dec 10 Jan 11 Feb 11 Mar 11 Apr 11 May 11 Jun 11 Jul 11 Aug 11

Short-tenor Medium-tenor Long-tenor

Tabel 2.5Ownership of Tradable Government Securities (SBN)

T Rp

Jun’10 Dec’10 Differences

SBN Ownership (Nominal)

Banks 219.52 226.54 7.02

Bank Indonesia 15.62 3.12 -12.5

Mutual Funds 51.16 48.76 -2.4

Insurance 79.3 93.42 14.12

Foreign 195.3 234.99 39.69

Pension Funds 36.75 36.69 -0.06

Securities 0.13 0.07 -0.06

Others 43.43 47.44 4.01

Total 641.21 691.03 49.82

Figure 2.33SUN Maturity Profile (June 2011)

60

T Rp

50

40

30

20

10

0

Fixed Rate Variable Rate

2041

2038

2037

2031

203020282027

20262025

2024

2023

20222021

2020

2019

2018

201720162015

20142013

2012

2011

Figure 2.34Performance of JCI as well as other Global and

Regional Indices(indexed as per 31st December 2005)

0.20

0.70

1.20

1.70

2.20

2.70

3.20Ju

n 10

Jul 1

0

Aug

10

Sep

10

Oct

10

Nov

10

Ded

10

Jan

11

Feb

11

Mar

11

Apr 1

1

May

11

Jun

11

JCIPOOMP

FTSE

FSSTINKY

DJIANYAKLCIKOSPISET

Hang Seng

The Jakarta Composite Index (JCI) was bullish during

the first semester of 2011 on the strength of stable global

and domestic economic growth as well as the competent

performance of issuers on the bourse. Positive sentiment

was primarily driven in Semester I-2011 by the Fed’s

decision to introduce Quantitative Easing II valued at $600

billion as well as commitment from other central banks to

maintain low policy rates, for instance in the US, Europe,

UK and Japan. Consequently, sentiment successfully

created liquidity on the markets, which continued to

bolster demand for goods and services required to maintain

post-crisis global economic momentum (Figure 2.34).

38


The index grew by 5% to a level of 3,888.57 in

Semester I-2011, which was actually slower than that

posted in Semester II-2010 at 27.11% (Table 2.6).

Improvements in the global and domestic economies

precipitated a decline in risk perception and, hence,

propagated the inundation of foreign capital flows.

Indonesia’s credit rating, which was one notch below

investment grade, further encouraged a torrent of foreign

capital flows into the domestic market. The rate at which

the index rallied was curtailed by a near-10% correction

in January due to high inflation expectations stemming

from the spiralling oil price, which exceeded $110 per

barrel at the time.

The rate at which global stock markets rallied was

restricted at the end of Semester I-2011 after a number of

central banks raised their benchmark rate in order to avoid

economic overheating. In addition, negative sentiment

stemming from the high price of oil, which itself was

the result of political upheaval in Egypt and Libya as well

as the earthquakes and tsunami that devastated Japan,

led to market concerns over default in Greece, which

could spread to other countries, as did the termination of

quantitative easing II on 30th June. Accordingly, bearish

Table 2.6Indices of several Global Stock Markets

Jun 10 Jun 11Des 10 Aug 11 Jun 10 - Jun 11Sem’ I 2011 Jun 11 - Aug 11

JCI 2,913.68 3,703.51 3,888.57 3,841.73 5.00% 33.46% -1.20%

FSSTI 2,835.51 3,190.04 3,120.44 2,885.26 -2.18% 10.05% -7.54%

SET 797.31 1,032.76 1,041.48 1,070.05 0.84% 30.62% 2.74%

KLCI 1,314.02 1,518.91 1,579.07 1,447.27 3.96% 20.17% -8.35%

PCOMP 3,372.71 4,201.14 4,291.21 4,348.50 2.14% 27.23% 1.34%

NKY 9,382.64 10,228.92 9,816.09 8,955.20 -4.04% 4.62% -8.77%

Hang Seng 20,128.99 23,035.45 22,938.10 20,534.85 -2.77% 11.27% -8.32%

KO SPI 1,698.29 2,051.00 2,100.69 1,880.11 2.42% 23.69% -10.50%

UKX 4,916.87 5,899.94 5,945.71 5,394.53 0.78% 20.92% -9.27%

NYA 6,469.65 7,964.02 8,319.10 7,528.39 4.46% 28.59% -9.50%

DJIA 9,774.02 11,577.51 12,414.34 11,613.53 7.23% 27.01% -6.45%

Growth

Source: Bloomberg

sentiment triggered expectations of a global economic

downturn due to the drying up of liquidity, which would

undermine demand.

Solid domestic economic growth coupled with the

favourable performance of issuers on the stock market

spurred expectations of greater demand, which led to a

rally on shares in the miscellaneous industries sector (up

18.11%), the trade sector (up 11.77%) and financial sector

(up 37.57%) during Semester I-2011.

The Indonesia Consumer Confidence Index rallied

from 103 in December 2010 to 109 in June 2011, annual

GDP (yoy) achieved 6.50%, automobile and motorcycle

sales continued to surge, sales of cement grew by 15% in

Semester I, commodity prices increased and export/import

activities grew respectively (yoy) by 45.3% and 48.5%;

all of which demonstrated economic development in

Indonesia that underpinned the Jakarta Composite Index.

Controlled inflation and a stable BI Rate led to bullish

sentiment concerning the banking sector, miscellaneous

industries and trade, the goods and services offered by

which are sensitive to the interest rate (Table 2.7).

Volatility on the domestic bourse eased from 23.83

(December 2010) to 13.59 (June 2011) as a consequence

39


of improved JCI performance supported by solid economic

fundamentals and sound issuers on the Indonesia Stock

Exchange. The ongoing fiscal stimulus packages introduced

by a number of central banks in various countries coupled

with global economic growth was sufficient to reign

in volatility on the global stock markets. Volatility on

the Tokyo Stock Exchange intensified as a result of the

earthquakes and tsunami in March 2011 (Figure 2.35).

A stable BI Rate, controlled inflation, 23.4% bank

credit growth and NPL of below 5% in 2011 helped

underpin favourable bank performance. During this past

year of 2011, domestic bank share prices closed mixed

after widespread profit taking following strong gains

on the financial sector index in 2010 (55% yoy) (Figure

2.36). The following banks’ shares posted gains during

Semester I-2010: BCA 28.57%, Mega 33.02%, Niaga

60.75%, Permata 36.13%, BII 92.98%, Mandiri 20.00%,

Bukopin 2.99%, Danamon 11.11%, BNI 64.89% and NISP

1.30%. Conversely, shares of Panin and BRI posted losses

of 10.78% and 30.11% respectively. The losses by BRI

were due to a stock split (Figure 2.37).

Table 2.7Share Price Index by Economic Sector

Jun 10 Jun 11Dec 10 Aug 11Jun 10 - Jun 11Sem’ I-2011 Jun 11 - Aug 11

JCI 2,913.68 3,703.51 3,888.57 3,841.73 5.00% 33.46% -1.20%

Financial Sector Index 377.18 466.67 506.87 507.12 8.61% 34.38% 0.05%

Agriculture Sector Index 1,660.50 2,284.32 2,318.69 2,247.99 1.50% 39.64% -3.05%

Basic Industries Sector Index 312.02 387.25 403.01 400.76 4.07% 29.16% -0.56%

Consumption Sector Index 959.04 1,094.65 1,180.26 1,285.18 7.82% 23.07% 8.89%

Property Sector Index 163.38 203.10 207.44 229.23 2.14% 26.96% 10.51%

Mining Sector Index 2,238.86 3,274.16 3,254.45 2,883.57 -0.60% 45.36% -11.40%

Infrastructure Sector Index 678.12 819.21 776.26 711.34 -5.24% 14.47% -8.36%

Trading Sector Index 317.02 474.08 529.86 524.67 11.77% 67.14% -0.98%

Others Industry Sector Index 809.20 967.02 1,142.15 1,203.92 18.11% 41.15% 5.41%

Growth

Source: Bloomberg

Sumber:

Figure 2.35Volatility on various Asian Bourses

0

10

20

30

40

50

60

%

Jun

10

Jul 1

0

Aug

10

Sep

10

Oct

10

Nov

10

Dec

10

Jan

11

Feb

11

Mar

11

Apr 1

1

May

11

Jun

11

IndonesiaJapan

ThailandHongkong

SingaporeMalaysia

Sumber:

Figure 2.36Bank Share Prices

2000

2500

1000

1500

0

500

10000

12000

6000

8000

0

4000

2000

04/0

1/20

11

14/0

1/20

11

24/0

1/20

11

03/0

2/20

11

13/0

2/20

11

23/0

2/20

11

05/0

3/20

11

15/0

3/20

11

25/0

3/20

11

04/0

4/20

11

14/0

4/20

11

24/0

4/20

11

04/0

5/20

11

14/0

5/20

11

2405

/201

1

03/0

6/20

11

13/0

6/20

11

23/0

6/20

11

NiagaLeft scale Right scale

BukopinPermata

BNIBRIBCADanamon

MandiriNISP

BII

PaninMega

40


The number of mutual funds increased in Semester

I-2011 from 558 in December 2010 to 632 in June 2011.

In addition, the performance of mutual funds rebounded,

as evidenced by the 5.34% increase in net asset value

(NAV) during the reporting semester (compared to 21.61%

in Semester II-2010) (Figure 2.38). Based on the type of

fund, the most impressive growth in NAV was for equity

funds and protected funds, which increased respectively

by 22.59% (position in August was 22.66%) and 1.87%

(position in August was 1.60%) to Rp55.98 trillion (position

in August was Rp56.02 trillion) and Rp290 billion (position

in August was Rp42.68 trillion) triggered by the upward

JCI trend. ETF equity funds and ETF fixed-income funds,

which are relatively new, posted gains of 4.79% (position

in August was 11.02%) and 5.39% (position in August

was 9.74%), while indexed funds increased significantly

by 12.23% (position in August was 17.93%) although

NAV remained relatively low at Rp290 billion (position in

August was Rp210 billion) (Figure 2.39).

2.3.2. Financing through the Capital Market and

Finance Companies

Issuances of Shares and Corporate Bonds

Sumber:

Sumber:

Figure 2.37Percentage Change in Bank Share Prices

Figure 2.38Performance of Mutual Funds

80.00%

60.00%

40.00%

20.00%

-0.00%

-20.00%

-40.00%

-60.00%

BCAMega

Sem I-11

Niaga

Permata Pan

in BII

Mandiri

Bukopin BRI

Danamon BNI

NISP

Sem II-10

180.00 640

620

600

580

560

540

520

160.00

140.00

120.00

100.00

80.00

60.00

40.00

20.00

NAV, T Rp

Dec 10 Jan 11 Feb 11 Mar 11 Apr 11 May 11 Jun 11

0.00

Number of shares/unit (billions) number of mutual funds

Sumber:

Figure 2.39Net Asset Value by type of Fund

60.00

50.00

40.00

30.00

20.00

10.00

Equity

Dec 10 Jan 11 Feb 11 Mar 11 Apr 11 May 11 Jun 11

0.00

Money marketDiscretionary

Fixed incomeProtectedIndexed

ETP- fixed incomeETP-equity

Islamic

Figure 2.40Capitalization Value and Value of Issuances

4,000

T Rp

3,500

4,500

4,000

3,500

3,000

2,500

2,000

1,500

1,000

500

0

3,000

2,500

2,000

1,500

1,000

500

Capitalization value

Jun Jul Aug Sep

2010 2011

Oct Nov Dec Jan Feb Mar Apr May Jun

0

value of issuance JCI (right scale)

Mutual Funds

41


Financing through the capital market became more

popular during the first semester of 2011 as reflected

by the 7.21% increase in the value of shares issued

to Rp531.1 trillion (compared to a 13.12% increase

in Semester II-2010). Year on year, the value of share

issuances increased by 21.37% compared to 18% in the

previous year. Meanwhile, a slower increase in the share

index during 2011 led to a more moderate increase in

market capitalization at 45.69% yoy (position in August

was 44.37%) compared to 60.8% in the preceding year

(Figure 2.40). Slower market capitalization primarily

occurred in the first semester of 2011 at just 7.73%

(position in August was 6.75%) compared to 35.24% in

Semester II-2010. Meanwhile, a further 14 firms issued

shares in Semester I-2011 bringing the total to 535.

Corporate financing through the issuance of

corporate bonds increased in the reporting semester on

the back of stable interest and inflation rates. The value

of bonds issued on the capital market in Semester I-2011

increased by 12.56% to Rp242.14 billion compared to

14.81% in the second semester of 2010. An additional

five companies issued bonds bringing the total to 194.

The low domestic interest rate and favourable economic

outlook helped maintain liquidity on the corporate bond

market (Figure 2.41).

Twenty-four corporate issuers issued corporate

bonds in Semester I-2011 totalling Rp27.01 trillion as

a whole compared to Rp36.60 trillion and 26 issuers in

2010. Under a framework of refinancing, of the 24 issuers

in 2011, 8 also issued in the previous year (Table 2.8). In

2011, 15 finance companies issued bonds compared to

7 in 2010. Meanwhile, in Semester II-2011 as many as

15 bonds will reach maturity with a total value of Rp6.34

trillion (Table 2.9).

Sumber:

Figure 2.41Issuances and Position of Corporate Bonds

300

250

200

150

100

( Val

ue in

Billi

ons R

p )

196

194

192

190

188

186

184

182

180

50

Value (left scale) Issuing Company (right scale)

0

Jun Jul Aug Sep

2010 2011

Oct Nov Dec Jan Feb Mar Apr May Jun

Tabel 2.8Firms that Issued Bonds in Semester I-2011

Bond’s IssuanceValue

Company

1 Surya Artha Nusantara Finance 600

2 BPD Jawa Barat dan Banten 2.000

3 Astra Sedaya Finance 2.150

4 Wahana Ottomitra Multiartha 1.400

5 Venera Multi Finance 500

6 Sarana Multigriya Finansial 463

7 Federal International Finance 3.000

8 BPD Sulawesi Selatan 500

9 Mandiri Tunas Finance 600

10 Bank International Indonesia 1.500

11 Adira Dinamika Multi Finance 2.500

12 Indomobil Finance Indonesia 1.000

13 Bank DKI 750

14 BCA Finance 1.100

15 Bank Permata 1.750

16 Bank Tabungan Pensiunan Nasional 500

17 Bank Tabungan Negara 2.000

18 MNC Securities 150

19 Bank Sumut 1.000

20 Toyota Astra Financial Services 1.200

21 Serasi Autoraya 900

22 BPD Nusa Tenggara Timur 500

23 BFI Finance Indonesia 450

24 BPD Riau Kepri 500

Total 27.013

Billions Rp

42


December 2010. In terms of efficiency, finance companies

were able to maintain their business efficiency as

demonstrated by the stable efficiency ratio at 0.79% in

line with the reduction in funding from bank loans.

Banks continued to dominate the source of funds

for finance companies but growth slowed in line with

the increase in bond issuances. The relatively stable

domestic interest rate in Semester I-2011, supported by

the favourable economic outlook, encouraged finance

companies to issue bonds resulting in an increase of

52.38% to Rp28.02 trillion. Funding sourced from

domestic bank loans increased by just 13.94% to Rp96.94

trillion, while that from foreign bank loans increased

by 11.61% to Rp67.22 trillion. Less reliance by finance

companies on bank loans also reduced the risk exposure

to banks (Figure 2.44).

Tabel 2.9Bonds due to Mature by Yearend 2011

Bond’s IssuanceValue

Company

1 Bakrieland 60

2 BNI 1.000

3 Perum Pegadaian 336,5

4 Radiant Utama Interinsco 100

5 PTPN 35

6 Selamat Sempurna 80

7 Indonesia Eximbank 1.250

8 BFI Finance 30

9 Astra Sedaya Finance 305

10 Bank Ekspor Indonesia 150

11 Bumi Serpong Damai 600

12 Summit Oto Finance 300

13 WOM Finance 590

14 Bank Jabar 1.000

15 Oto Multiartha 500

Total 6.337

Billions Rp

Figure 2.42Business Activity of Finance Companies

Figure 2.43Financing (billions of rupiah)

300,000

250,000

200,000

150,000

100,000

Billions Rp

50,000

June 2009

Assets Financing Funding Capital0

December 2009

June 2010

December 2010

June 2011

240,000

200,000

160,000

120,000

40,000

40,000

0Leasing Factoring

10.15%

Financing (billions Rp)

2.57%

16.87%

Credit Card ConsumerFinancing

TotalFinancing

46,528Dec’09Jun’10Dec’10Jun’11

2,027 930 93,054 142,53948,985 2,084 854 111,279 163,20153,167 2,295 876 130,016 186,35457,494 3,027 856 151,038 212,445

Financial Institutions – Finance Companies

Solid domestic economic growth throughout 2010

and 2011, supported by stable interest and inflation

rates, helped expand the market for finance companies

in Semester I-2011. The total assets of finance companies

grew by 12.67% or 28.76% yoy to Rp259.55 trillion.

The sources of funding activity for finance companies

increased by 14.00% or 30.17% yoy to Rp212.44 trillion,

principally bolstered by a 2.63% rise in capital or 9.83%

yoy. Meanwhile, finance company funding from loans and

bonds increased by just 17.40% or 44.44% yoy (Figure

2.42). The increase in financing from finance companies

mainly came from consumer financing with a share of

71.10% (up from 69.77% in December 2010) or Rp151.04

trillion (June 2011). Such conditions increased the risk of

finance company concentration (Figure 2.43).

The performance of finance companies slowed

marginally in Semester I-2011 as indicated by the decline

in pre-tax profits, which contributed to a lower return on

assets and return on equity compared to the position in

43


Sumber: Bloomberg

Figure 2.44Finance Companies’ Source of Funds

200,000

in billions Rp

180,000

160,000

140,000

120,000

100,000

80,000

60,000

40,000

20,000

Domestic bankloans

foreign bankloans

Securitiesissued

Total source offunds

0

Dec’09 Jun’10 Dec’10 Jun’11

In Semester I-2011, amid rapid growth in finance

company financing, nominal NPL also increased by 7.10%

to Rp2.85 trillion in contrast to the 8.41% decline in

Semester II-2010. At the end of Semester I-2011, the

percentage of non-performing loans declined from 1.37%

(December 2010) to 1.29% (June 2011). This decline was

primarily attributable to the nominal decline in NPL for

leasing and credit cards. Furthermore, a decline in NPL

was reported for all types of activity conducted by finance

companies, namely leasing, factoring, credit cards and

consumer financing (Table 2.11).

Despite the low level of non-performing loans,

potential vulnerabilities remain from the activities of

finance companies that require vigilance, particularly

motor vehicle loans. Consequently, policy harmonisation

between Bank Indonesia and the Capital Market and

Financial Institution Supervisory Board is critical in light of

the close interconnectedness among banks and finance

companies (Box 2.2).

Dalam Rp Miliar December

2009

June

2010

June

2011

December

2010

Assets (Billions Rp) 174,442 201,570 230,301 259,548

Debt (Billions Rp) 115,555 133,057 163,701 192,183

Obligations (Billions Rp) 134,354 158,180 182,470 211,019

Capital (Billions Rp) 40,088 43,390 47,831 48,529

Profit Before Tax (Billions Rp) 10,421 5,869 11,563 5,932

Profit After Tax (Billions Rp) 7,827 4,637 8,929 4,727

ROA (%) 5.97 2.91 5.02 2.29

ROE (%) 25.99 13.53 24.17 12.22

BOPO (%) 73.81 71.44 73.94 79.48

Debt/Equity 2.88 3.07 3.42 3.96

Obligations/Equity 3.35 3.65 3.81 4.35

Table 2.10Financial Ratios of Finance Companies

44


Nominal NPL

Billions Rp

December

2009

June

2010

June

2011

December

2010

Table 2.11NPL of Finance Companies

Leasing 730 714 351 261

Factoring 126 123 73 78

Credit Cards 41 47 44 38

Consumer Financing 1,932 2,017 2,189 2,469

Total Financing 2,829 2,901 2,658 2,846

%NPL December 2009 June 2010 December 2010 June 2011

Leasing 1.50% 1.39% 0.63% 0.43%

Factoring 5.93% 5.60% 3.07% 2.51%

Credit Cards 3.93% 5.00% 4.62% 4.06%

Consumer Financing 2.01% 1.76% 1.63% 1.59%

Total Financing 1.91% 1.72% 1.37% 1.29%

45


As part of the efforts to boost transparency

and good governance in the setting of bank lending

rates, Bank Indonesia promulgated SE No 13/5/DPNP

dated 8th February 2011 regarding the transparent

publication of prime lending rates. The aim of this policy

is, among others, to reduce asymmetric information

while simultaneously bolstering market discipline.

Furthermore, in order to reinforce the application

of this regulation, a number of socialisation measures

have been taken towards the general public as well

as various approaches to enhance bank supervision.

In terms of socialisation, the measures taken by

Bank Indonesia aim to raise public awareness of the

regulation and prime lending rates in general, therefore

empowering the public to compare lending rates

between banks as a source of information in their

decision-making process. Hitherto, Bank Indonesia has

taken the flowing steps:

• Publishedabookletandaddedaquestion/answer

section to the official Bank Indonesia website.

• Socialised the new regulation to the banking

community, lecturers, academics, business

associations and other elements of society

in Jakarta as well as a number of other cities

(Surabaya, Makassar, Medan, Solo, Yogyakarta

and Aceh).

• Implementedsocializationactivitiesthroughprint

media (newspapers and magazines) as well as

electronic media (television and radio).

Meanwhile, in terms of supervision, Bank

Indonesia has and will continue to: i) meet with

individual banks and banking associations to teach and

broaden their knowledge regarding the structure and

calculation of the prime lending rate at each specific

bank; ii) compile a benchmark/summary of base

lending rates for the industry and peer groups; and iii)

compile bank ratings. All of this data and information

is particularly beneficial for Bank Indonesia when

conducting bank supervision and inspections.

Impact of the Regulation on Lending Rates

Based on bank reports from March – July 2011 it

was revealed that in the final month (June compared

to July) the base lending rates of corporate loans and

mortgages had actually declined. However, the prime

lending rate of retail credit increased slightly and no

changes were reported for the non-mortgage segment.

The main component affecting the prime lending rate

is the cost of funds for credit, followed by overhead

costs and profit margin.

Based on available reports (LBU),an indirect

impact of issuing the base lending rate regulation has

been greater bank discipline in terms of setting their

lending rates. This is reflected, among others, by the

following developments:

• Theprimelendingrateinthelastmonthdeclined

by 18 bps for the corporate segment and 35 bps

for mortgages, while no change was reported

for retail credit and the non-mortgage segment

increased moderately by 9 bps.

• Yearonyear,effectiveinterestratesforworking

capital credit and investment credit have declined

Box 2.1 Implementation of Transparent Base Lending Rates

46


respectively by 86 bps and 44 bps, while rates

for consumption credit have increased by 66 bps.

Similarly, in terms of year to date, the rates for

working capital credit and investment credit have

decline respectively by 62 bps and 11 bps, while

consumption credit has increased by 84 bps.

Although it is still too early to decisively conclude

that the developments mentioned were the result of

the prime lending rate regulation, Bank Indonesia

welcomes the current positive trends and hopes that

they will continue, accompanied by a decline in the

rates for consumption credit.

Looking ahead, the challenges faced in the

implementation of transparent lending rate policy

include:

• Raisingpublicawareness.

• Follow-up studies regarding the structure of

setting bank lending rates, which are highly

variable, including reviewing the calculation and

determination of the risk premium at banks.

Average Rupiah Lending Rates (%)

18

16

14

12

10

8

6

Working Capital Credit

2007 2008 2009 2010 20114

Investment Credit

Consumption Credit

1 month deposits

47


The income and consumption level of the public

has increased in line with the general improvement

in macroeconomic conditions, including the ever-

growingdesire for motor vehicles. Consequently, banks

and finance companies alike have reported expansive

growth in automotive loans. The value of consumer

financing (including for motor vehicles from finance

companies) was Rp130 trillion in 2010, compared to just

Rp33 trillion estimated. Regarding the source of funds,

as much as Rp79.35 trillion of finance companies’ funds

were estimated to originate from banks. Meanwhile,

the value of outstanding automotive financing from

banks in 2010 was Rp80 trillion, against an estimated

Rp28.4 trillion or 53.9% yoy.

Despite rapid growth in automotive loans the

level of non-performing loans has remained low. Non-

performing automotive bank loans were just 1.2% in

July 2011 (the highest of which was for motorcycle

loans at 2.1% NPL). In comparison, non-performing

financing from finance companies for automotive credit

was in the range of 2.8%.

Sixty-one percent of automotive loans are car

loans followed by 38% for motorcycle loans and 1%

for commercial vehicles and trucks. In terms of growth,

car loans are experiencing the strongest growth at

37.1% (ytd) or 64.5% (yoy). Growth in motorcycle

loans is much lower at around 0.9% (ytd) or 7.5%

(yoy) and for commercial vehicles growth is negative

in terms of year to date and year on year.

Box 2.2Automotive Loans: Is Policy Harmonisation required between Bank Indonesia and the Capital Market and Financial Institution Supervisory Board (Bapepam-LK)?

Car LoansMotorcycle loans

TrucksOthers

57.561%

35.238%

0.20%

1.21%

Breakdown of Automotive Loans(T Rp /%)

-10 0 10 20 30 -100% -50% 0% 50% 100%

(1.6)

(3.3)

(0.1)

(0.3)

0.3

-56.8%Growthnominal

GrowthProsentase

-72.6%

-23.4%

-55.5%

ytd

0.9%

7.5%

37.1%

64.5%

2.5

15.6

22.6 Rp T

yoy

Growth (yoy) in Automotive Loans

With such rapid growth in auto loans coupled

with the reliance of finance companies on banks for

funds, financial system instability could potentially

escalate. Potential instability emerges due to: i)

low deposits that encourage potential consumers

with insufficient income to obtain credit, which is

48


subsequently vulnerable to future default; and ii) credit

terms of 4 years for second-hand motorcycles and 5

years for used automobiles increases the potential for

default because the age of the used vehicle can be in

excess of 10 years, while the economic age of motor

vehicles, therefore, is insufficient.

However, regulations legislating automotive

loans by banks would be less effective against motor

vehicle sales if not conducted in unison with finance

companies. This is due to a disparity between the rules

governing finance companies that do utilise funds from

banks and those that do not, which leads to a business

imbalance. Consequently, regulatory harmonisation

is required between Bank Indonesia and the Capital

Market and Financial Institution Supervisory Board

(Bapepam-LK) in order to ensure that the polices set

can apply across the industry as a whole.

49

Chapter 3. Financial System Stability Prospects and Challenges

Chapter 3Financial System StabilityProspects and Challenges

50



51


Chapter 3 Financial System Stability Prospects and Challenges

3.1. CRISIS THREATS FROM THE UNITED STATES

AND EUROPE TO THE ECONOMY OF INDONESIA

Hitherto maintained financial system stability will face

a number of arduous challenges during Semester II-2011.

The ongoing crisis in the US and Europe is the main threat

to financial system stability in Indonesia. Crisis resolution

in these countries is still failing to show many encouraging

results. Furthermore, the languid crisis recovery process

has undermined international confidence. Large fiscal

deficits in these countries have spurred deep concerns.

Assistance from donor countries like France and Germany,

which was initially believed would restore conditions, is

currently in doubt because it would exacerbate the fiscal

deficits in the two countries. The European Financial

Stability Facility, which is the centrepiece of crisis resolution

in Europe, is now in doubt and has become a topic for

public debate (Box 3.1).

Meanwhile, the overriding problems of the large

budget deficit and Quantitative Easing III in the United

States, which have persisted since last year, are expected

to encourage excess liquidity on US financial markets that

will propagate the inundation of foreign capital flows to

emerging market countries, including Indonesia. Such

circumstances are expected to remain a major concern in

Semester II-2011.

Deteriorating problems affecting the financial sectors

of advanced countries like the US and in Europe have the

potential to jeopardise global economic performance and

world trade volume. Global economic growth is expected

to slow. The IMF through its World Economic Outlook,

June 2011, projected global GDP in 2011 at 4.3%, which is

lower than that posted in 2010 at 5.1%. This value is lower

than the IMF’s previous projection of 4.4% and, at the time

of writing, the IMF was actually revising its projection for

Financial system stability is expected to persist through to yearend 2011

despite a moderate increase in the financial stability index (FSI), attributable to

escalating volatility on the domestic bond and stock markets as well as greater

credit risk in the banking sector, stemming from widespread uncertainty

regarding the global economic recovery and the large fiscal deficits in the

US and Europe. Notwithstanding, the results of stress testing banks against

various micro and macro scenarios demonstrated that banks could survive

crisis conditions. In this context, stress tests on the business community also

confirmed adequate resilience in the face of a sudden capital reversal. In

addition, solid domestic economic growth in 2011 further supports financial

system stability.This page intentionally blank

52


global economic growth to just 4%. Meanwhile, Morgan

Stanley also lowered its own projection for global economic

growth from 4.2% to 3.9% and trimmed its estimation

of stock market growth in emerging market countries,

including Indonesia. Revisions were made as a result of

the US and Europe approaching back into a recession

zone. Meanwhile, in its report the Asian Development

Bank (ADB) downgraded its own projections for economic

growth in Asia from 7.8% to 7.5% in 2011.

Meanwhile, inflationary pressures, which increased in

Semester I-2011 due to volatile foods as a result of limited

domestic food supply, weather anomalies, global food

and commodity price hikes, as well as limited food exports

from specific countries, are expected to ease in the second

semester of 2011. The panoply of policies instituted by

Bank Indonesia to dampen prices, like raising the policy rate

and enhancing the performance of the Inflation Control

Team, has yielded positive results.

Robust domestic economic growth coupled with

controlled inflation continues to ensure Indonesia’s

fundamental attractiveness to investors. Economic growth

in excess of 6% has helped the economy of Indonesia

move away from dependence on the global economy

(Figure 3.1). Additionally, strong consumption supported

by rising per capita income (exceeding that in other ASEAN

countries) further boosts Indonesia’s appeal to investors.

Moreover, Indonesia’s debt to GDP ratio is following a

downward trend while that of other countries is trending

upwards, which demonstrates the robustness of the

domestic economy and that additional loans can be used

effectively to further boost GDP, thereby reducing the debt

ratio (Figure 3.2 and 3.3).

2011*2010

GDP (% yoy) 6,1 6,3 - 6,8

Inflation (%, end of period) 6,96 5 ± 1

Table 3.1Projected GDP and Inflation

*) Bank Indonesia projections

Despite the economic slowdown in advanced

countries, the economy of Indonesia is predicted to

continue growing solidly in the range of 6.3-6.8%.

Meanwhile, inflation at yearend is projected to remain

within the target corridor of 5%±1%. Robust economic

growth in Indonesia is projected on the back of strong

domestic consumption and investment as well as greater

government budget realisation in Semester II-2011. The

direct impact of the economic slowdown in the US and

Europe is expected to only slightly disrupt Indonesian

exports to European countries, which account for 15% of

total Indonesian exports, while the United States contributes

10% to total exports. The relatively small disruption is due

to ongoing efforts to diversify export destination countries.

Accordingly, overall export performance is expected to

remain solid. Nonetheless, the indirect impacts that could

undermine exports require vigilance, namely Indonesian

exports to the US and Europe through a third party (for

instance Singapore), for which the total is relatively large

compared to other ASEAN countries (Table 3.1).

Figure 3.1GDP Growth per Capita

40%

30%

20%

10%

0%

-10%

Indonesia Malaysia

2002 2003 2004 2005 2006 2007 2008 2009 2010

-20%

Thailand Singapore

53


3.2. IMPACT ON THE INDONESIAN FINANCIAL

SYSTEM

In general, the persistent crisis in the US and Europe,

the lacklustre recovery in certain countries as well as

uncertainty surrounding future global economic conditions

will continue to tarnish the financial system of Indonesia

in Semester II-20011. Despite well-maintained financial

system stability, such conditions will precipitate uncertainty

on domestic markets, in particular on the capital market

and bond market, which will aggravate price volatility on

these markets and potentially intensify the risk of financial

system instability.

The potential of a sudden capital reversal requires

vigilance considering the experience gleaned in 2008

when a capital reversal struck in October and led to rapid

rupiah depreciation to over Rp13,000 per US dollar, a 50%

correction on the stock market and a 30% correction to

SUN prices. Based on a static correlation between JCI and

foreign transactions, the correlation during the crisis in

2008-09 was 55.8%, which then increased to 85.5% in

2010-11.Such a tight correlation will lead to additional JCI

volatility following global market developments, thereby

leaving the index vulnerable to profit taking (Figure 3.4

and 3.5).

Source: Ministry of Finance and BPS-Statistics Indonesia, processed

*) projections

Figure 3.2Debt to GDP Ratio of several Countries

Figure 3.3Indonesia’s Debt to GDP Ratio

2006-2011

In the real sector, corporate indicators are expected

to remain favourable up to yearend 2011 despite the global

economic slowdown, which is predicted to undermine

corporate performance slightly. Looking ahead, corporate

risk will escalate in line with the rise in NPL and probability

of default. However, in general, the corporate sector will

remain resilient to global economic dynamics. Meanwhile,

conditions in the household sector are expected to remain

conducive combined with low risk, which is further

corroborated by the insignificant household debt to asset

ratio.

Figure 3.4JCI versus Foreign Transactions (2008-2009)

250

%

200

150

100

50

Indonesia US

2006 2007 2008 2009 2010

0

Japan EURO

Brazil

India

8.000

(trillion rupiah)

7.000

6.000

5.000

4.000

3.000

2.000

1.000

Outstanding Debt

2006 2007 2008 2009 2010 2011**

0

120%%

100%

80%

60%

40%

20%

0%

39.0% 35.1% 33.0%28.3% 26.0% 25.7%

GDP Debt to GDP Ratio

40.000

35.000

30.000

25.000

20.000

15.000

10.000

5.000

0

2.500

3.000

1.500

2.000

0

1.000

500

1/01

/200

82/

01/2

008

3/01

/200

84/

01/2

008

5/01

/200

86/

01/2

008

7/01

/200

88/

01/2

008

9/01

/200

810

/01/

2008

11/0

1/20

0812

/01/

2008

1/01

/200

92/

01/2

009

3/01

/200

94/

01/2

009

5/01

/200

96/

01/2

009

7/01

/200

98/

01/2

009

9/01

/200

910

/01/

2009

11/0

1/20

0912

/01/

2009

Net Foreign Transactions (annual) JCI

54


On the bond market, increased risk of default

on Greek bonds is expected to encourage investors to

sell bonds from Spain, Ireland, Italy and Portugal, all of

which are also encumbered by large debts. From the

results of analyses using dynamic coefficient correlation,

it was revealed that the relationship between markets

in the countries mentioned and Indonesia is very small.

Nevertheless, such conditions require careful observation

considering that inter-market linkages are susceptible to

contagion from the crisis in Europe, which would spread

and become a global crisis because the risk perception of

Asia would also increase and trigger a hike in bond yields

from developing countries. Ultimately, this would add to

the interest burden of countries in the Asian region.

The Taylor Expansion method, which can simulate

the impact of a 25 bps increase in yield for all tenors of

SUN, indicated that the average decline in SUN prices

for FR series and VR series would be 3.07% and 3.25%

respectively (Table 3.2 and 3.3).

Figure 3.5JCI versus Foreign Transactions (2010-2011)

Table 3.2Simulated hike in BI Rate on SUN Prices, FR Series

SerialNumber

Periods SUN PriceBI Rate:6,75%

New PriceBI Rate:6,75%

Differences(%)

0,25 bps

1 FR0016 9 101.14 99.21 -1.91%

2 FR0017 9 104.16 102.08 -2.00%

3 FR0018 10 107.80 105.33 -2.11%

4 FR0019 11 115.02 112.39 -2.28%

5 FR0020 11 118.35 115.52 -2.39%

6 FR0022 8 101.41 99.52 -1.86%

7 FR0023 9 107.35 105.14 -2.06%

8 FR0025 7 101.39 99.69 -1.68%

9 FR0026 10 113.50 110.94 -2.26%

10 FR0027 10 109.87 107.30 -2.34%

11 FR0028 12 114.25 111.08 -2.77%

12 FR0030 11 116.01 113.17 -2.45%

13 FR0031 15 123.18 118.97 -3.41%

14 FR0032 13 142.05 138.13 --2.76%

15 FR0033 7 110.93 109.18 -1.57%

16 FR0034 15 135.66 131.12 -3.35%

17 FR0035 16 136.05 131.22 -3.55%

18 FR0036 13 124.45 120.77 -2.96%

19 FR0037 20 131.46 125.63 -4.43%

20 FR0038 12 123.65 120.38 -2.65%

21 FR0039 17 127.82 123.06 -3.72%

22 FR0040 19 122.53 117.41 -4.18%

23 FR0042 20 115.49 110.26 -4.53%

24 FR0043 15 116.80 112.80 -3.43%

25 FR0044 17 114.27 109.84 -3.88%

26 FR0045 30 105.98 99.00 -6.59%

27 FR0046 16 111.20 107.22 -3.58%

28 FR0047 20 112.60 107.49 -4.54%

29 FR0048 11 109.39 106.67 -2.48%

30 FR0049 6 105.94 104.59 -1.27%

31 FR0050 30 113.45 105.91 -6.65%

32 FR0051 5 113.01 111.66 -1.19%

33 FR0052 21 116.49 111.09 -4.63%

34 FR0053 11 105.10 102.46 -2.51%

35 FR0054 21 108.00 102.95 -4.67%

36 FR0055 6 102.34 100.93 -1.38%

37 FR0056 16 101.72 98.04 -3.62%

*) Calculated using the Taylor Expansion Method**) Assuming a 25 bps increase on all tenors of SUN

45.000

40.000

35.000

30.000

25.000

20.000

15.000

10.000

5.000

0

4.000

4.500

3.000

3.500

1.500

2.500

2.000

1/01

/201

0

2/01

/201

0

3/01

/201

0

4/01

/201

0

5/01

/201

0

6/01

/201

0

7/01

/201

0

8/01

/201

0

9/01

/201

0

10/0

1/20

10

11/0

1/20

10

12/0

1/20

10

1/01

/201

1

2/01

/201

1

3/01

/201

1

4/01

/201

1

5/01

/201

1

6/01

/201

1

7/01

/201

1

8/01

/201

1

9/01

/201

1

net foreign transactions (annual) JCI

55


Well-managed market risk during Semester I-2011

is expected to continue in Semester II-2011. Stress tests

conducted to measure the resilience of bank capital against

market risk, which constitutes a decline in government

securities, rupiah depreciation and rising interest rates,

in general provided evidence of sufficiently resilient bank

capital.

3.3. IMPACT ON BANKS AND STRESS TESTS

Looking ahead, banks will continue to dominate

the financial system in Indonesia based on total assets

of financial institutions. In terms of bank capital, up to

yearend 2011 banks are expected to continue absorbing

risk stemming from the failing economies of the United

States and Europe. This is principally based upon the fact

that total exposure of bank assets originating from abroad

is insignificant compared to total domestic assets. Direct

foreign exposure, which consists of on and off balance

sheet portfolio, includes securities, placements at other

banks, acceptances, bank guarantees and irrevocable

letters of credit totalling Rp110 trillion (that sourced

domestically totals Rp638.30 trillion). This foreign portfolio

accounted for a mere 3.13% of total bank assets in June

2011, namely Rp3,195 trillion.

Sumber:

Sumber:

Figure 3.6Rupiah Maturity Profile

Figure 3.7Stress Tests for Higher Interest Rates

Tabel 3.3Simulated hike in BI Rate on SUN Prices, VR Series

Periods SUN PriceBI Rate:6,75%

New PriceBI Rate:6,75%

Differences(%)

0,25 bps

1 VR0017 9 99,25 97,17 -2,09%

2 VR0018 10 99,25 96,95 -2,32%

3 VR0019 12 99,71 96,92 -2,80%

4 VR0020 12 99,93 97,05 -2,88%

5 VR0021 13 99,00 96,02 -3,01%

6 VR0022 13 99,00 95,95 -3,09%

7 VR0023 14 99,00 95,81 -3,22%

8 VR0024 14 99,00 95,74 -3,30%

9 VR0025 15 99,00 95,81 -3,43%

10 VR0026 15 99,00 95,53 -3,50%

11 VR0027 16 99,00 95,42 -3,61%

12 VR0028 16 99,00 95,40 -3,63%

13 VR0029 17 99,00 95,18 -3,88%

14 VR0030 17 99,00 95,10 -3,94%

15 VR0031 18 99,00 94,97 -4,07%

*) Calculated using the Taylor Expansion Method**) Assuming a 25 bps increase on all tenors of SUN

Potential bank losses stemming from a future hike

in interest rates will tend to decline due to the banks

ongoing reduction in their short position on the rupiah

maturity profile <12 months, namely a decline from

600

Trillion Rp

400

200

0

-200

-400

-600

-800

up to 1 month 1-3 months

Dec - 09

3-6 months 6-12 months >12 months

Jun - 10 Dec - 10 Jun - 11

17.20%CAR

17.00%

16.80%

16.60%

16.40%

16.20%

16.00%

0

Initial CAR InterestRates

Rise 1%

InterestRates

Rise 2%

InterestRates

Rise 3%

InterestRates

Rise 4%

InterestRates

Rise 5%

-70 bps

56


Rp347.31 trillion (December 2010) to Rp337.81 trillion

(June 2011). Based on the results of stress tests, bank

capital is relatively resilient to the risk of higher interest

rates. More specifically, under a scenario of a 5% increase

in the interest rate, CAR would only decline by 70 bps.

However, greater sensitivity to the interest rate in line with

an increased short position on the rupiah maturity profile

<1 month must be monitored (Figure 3.6 and 3.7).

Increased volatility on the global market encouraged

banks to reduce their exposure to foreign currency in the

first semester of 2011. This is reflected by the decline in

the net open position from 3.7% in December 2010 to

3.43% in June 2011, hence, the resilience of bank capital

in anticipation of rupiah depreciation is adequate (Figure

3.8). With this kind of limited exposure to foreign currency,

the results of stress tests simulating rupiah depreciation by

50% demonstrate that the CAR of no banks would drop

below the 8% threshold (Figure 3.9).

The SUN portfolio of banks shrank moderately

by 0.2% to Rp223.19 trillion (June 2011), with banks

tending to prefer trading and available-for-sale (AFS)

SUN as opposed to held to maturity (HTM). Accordingly,

the majority of SUN held by banks was available-for-sale

(60.33%), with trading and HTM accounting for 7.25%

and 32.42% respectively. Total bank exposure to the risk

of a decline in SUN price, consisting of trading and AFS

SUN, increased from Rp149.54 trillion (December 2010) to

Rp150.82 trillion (June 2011). Under a scenario of a 25%

drop in the AFS and trading SUN price, banking industry

CAR would potentially decline by 110 bps (Figure 3.10).

Sumber:

Figure 3.8Net Open Position (NOP)

Figure 3.10Stress Test for a decline in SUN Price

Figure 3.9Stress Tests for Rupiah Depreciation

12%

8%

4%

NOP

0%Privatebanks

Jointventure

Regionalbanks (BPD)

StateOwnedbanks

Foreignbanks

Aggregate

December 2009

June 2010

December 2010

June 2011

4.5%

2.8%

2.8%

2.91

%

3.7%

3.9%

2.5%

2.99

%

2.4%

3.0%

3.8%

3.09

%

4.1%

4.5%

3.8%

6.35

%

4.8%

2.8%

8.6%

5.07

%

4.1%

3.1%

3.7%

3.43

%

17.01%

17.00%

17.00%

16.99%

16.99%

16.98%

16.98%

16.97%

16.97%

16.96%

16.96%

CAR

Initial CAR DepreciationRp 10%

DepreciationRp 20%

DepreciationRp 30%

DepreciationRp 40%

DepreciationRp 50%

-3 bps

17.20%

17.00%

16.80%

16.60%

16.40%

16.20%

16.00%

15.80%

15.60%

15.40%

15.20%

CAR

Initial CAR SUN Price5%

SUN Price10%

SUN Price15%

SUN Price20%

SUN Price25%

-110 bps

57


Sumber:

Figure 3.11Stress Test for Credit Risk

Bank CAR is forecast to remain adequately resilient in

anticipation of mounting credit risk despite a slight increase

in the level of NPL compared to the end of 2010. Using

a scenario of a 15% increase in NPL, bank CAR would

potentially decline by 401 bps. Meanwhile, using macro-

credit risk stress testing based on FSAP 2009, assuming

0% GDP growth, then the position of NPL in June 2011

would rise a further 3.6-fold with the potential to reduce

CAR by 199 bps (Figure 3.11).

of a 5% decline in deposits (average deposit withdrawals

were around 5% during the 2008 crisis). Meanwhile,

when compared to conditions at yearend 2008, sufficient

liquidity of individual banks to cover the withdrawal of

non-core deposits4 is currently much improved. In this

context, more banks currently enjoy a ratio of liquid assets

to non-core deposits in excess of 100% and no banks have

a ratio of below 50%.

3.4. FINANCIAL SYSTEM PROJECTIONS

Taking into consideration all the factors detailed

above, the prospects of financial system stability in

Indonesia up to yearend 2011 will be maintained. The

financial stability index is projected in the range of

1.45 - 1.91, with a baseline of 1.68. This projection is

slightly higher than that for the end of Semester I-2011

considering that, looking ahead, uncertainty in the global

economy will continue to compound volatility on the stock

and bond markets coupled with a moderate escalation in

bank credit risk. However, maintained macroeconomic

conditions in Indonesia up to the end of 2011 accompanied

by favourable bank performance in general will have a

positive effect on the resilience of financial system stability.

In addition, a sudden capital reversal in the deluge of

capital flowing into domestic financial markets requires

constant vigilance by the Government and Bank Indonesia,

and measures are required to be put in place in order to

minimise potential instability risk. To this end, the existence

of a financial sector safety net is imperative.

Stress tests on the foreign exposure, from the US and

Europe, of domestic banks indicated sufficient resilience to

the possibility of default due to total exposure from the US

and Europe, where CAR would decline respectively by 47

bps and 63 bps from 17% to 16.53% and 16.37%. If the

stress tests were adjusted to include the 3.6-fold increase

in NPL (based on the results of macro-credit risk stress

tests assuming 0% GDP growth), then bank CAR has the

potential to decline by 127 bps to 15.73%.

In terms of liquidity risk, the performance of liquid

assets in Semester I-2011 was adequate to anticipate

future deposit withdrawals, namely more than 100% of

the requirement despite a slight decrease compared to the

position at the end of Semester II-2010. Based on stress

tests, no banks ran into liquidity difficulties in the event 4 Non-core deposits consist of 30% checking accounts, 30% savings accounts and 10%

term deposits of <3 months

18.00%

16.00%

14.00%

12.00%

10.00%

8.00%

6.00%

4.00%

2.00%

0.00%

CAR

Initial CAR NPL 5% NPL 7.5% NPL 10% NPL 12.5% NPL 15%

-401 bps

58


Box 3.1 European Financial Stability Facility

The economies of member states in the Eurozone

have already experienced numerous downturns.

During the period of 1992-93 economies in the euro

area experienced a contraction and then in 2002-03

suffered from stagnation. In addition, resolution of the

ongoing sovereign debt crises in a number of European

countries remains unclear and has potential contagion

risks. Such inauspicious circumstances have encouraged

the establishment of a special purpose vehicle known as

the European Financial Stability Facility (EFSF) in order

to maintain financial stability in the euro area through

the availability of bailout funds in the event of a crisis.

The European Financial Stability Facility will operate

through to 2013, when it will become the European

Stability Mechanism (ESM).

The European Financial Stability Facility can issue

bonds or other debt instruments with the support of

the German Debt Management Office. The objective is

to raise funds for Eurozone member states in financial

troubles, recapitalise banks or buy sovereign debt.

Moody’s and S&P rate bonds issued by the European

Financial Stability FacilityAAA, the highest rating

possible5.

Guarantee Commitments

The following table shows the current contribution

of each member state of the euro area in the bailout

fund system of EFSF. As part of the rescue package

totalling €750 billion, EFSF can issue bonds that are

guaranteed to a maximum of €440 billion6. Under the

financing architecture of EFSF, the country with the

healthiest economy guarantees the second soundest

economy, which in turn guarantees the third, etc.

This guarantee mechanism ensures that all

member states are covered. A domino effect would

occur in the event that instability befalls the weakest

economy, which affects the next weakest economy all

the way up to the healthiest, thus causing a double

negative effect. If this scenario happens then the

presence of the European Financial Stability Facility will

only deepen the impact of the European crisis.

5 http://euobserver.com/19/308446 http://www.efsf.europa.eu/about/index.htm

59


Country Guarantee

Commitments (EUR)

Millions

Guarantee

Commitments (EUR)

Millions

(%) (%)

Initial contributions Initial contributions

Austria 12,241 2.78 21,639 2.78

Belgium 15,292 3.48 27,032 3.47

Cyprus 863 0.20 1,526 0.20

Estonia 1,995 0.26

Finland 7,905 1.80 13,974 1.79

France 89,657 20.38 158,488 20.32

Germany 119,390 23.13 211,046 27.06

Greece 12,388 2.82 21,898 2.81

Ireland 7,002 1.59 12,378 1.59

Italy 78,785 17.91 139,268 17.86

Luxembourg 1,101 0.25 1,947 0.25

Malta 398 0.09 704 0.09

Netherlands 25,144 5.71 44,446 5.70

Portugal 11,035 2.51 19,507 2.50

Slovakia 4,372 0.99 7,728 0.99

Slovenia 2,073 0.47 3,664 0.47

Spain 52,353 11.90 92,544 11.87

Source: EFSF

61

Chapter 4. Special Topics

Chapter 4Special Topics

62



63


Chapter 4 Special Topics

4.1. SYSTEMICALLY IMPORTANT FINANCIAL

INSTITUTIONS (SIFI)

The recent crisis in 2008 triggered defaults at a large

number of global financial institutions, which disrupted the

global financial system and had an adverse impact on the

real economy. On one hand, the ability of the supervisory

authority and other authorities was limited in terms of

preventing the impact of the financial crisis on the business

community and financial system. Consequently, public

sector intervention in the form of financial and economic

costs to repair the financial system was required during

the crisis on a large scale.

The financial service board recommended several

resolutions, primarily in the form of a change in regime

and tools at the national level as well as an adjustment

to the legal framework so that the relevant authorities

had jurisdiction to coordinate in terms of cross-border

resolution. Systemically important financial institutions

should have the capability to absorb risk (as a minimum

pursuant to Basel III). Such institutions should also be

coordinated and subject to more intensive supervision as

well as planned resolutions to reduce the impact of their

failure.

In its response to the crisis, the Basel Committee

on Banking Supervision adopted a series of reforms to

ameliorate the resilience of the banks and banking system.

The reforms include improving the quality and quantity of

capital, risk coverage, introducing a leverage ratio, capital

conservation, countercyclical buffer and liquidity risk. This

series of policies is expected to have a significant impact

on global systemically important financial institutions

(G-SIFI).

What is meant by systemically important financial

institutions? Hitherto, there is no universally accepted

standard definition. In general, policymakers define

systemically important financial institutions as a financial

Bank Indonesia remained continuously active in maintaining financial system

stability during the first semester of 2011. An array of measures was introduced

to prevent excessive risk on the financial market in synergy with global financial

reforms. Reinforcing the structure of the banking sector became a priority

agenda item in reaching the wider community. Furthermore, Bank Indonesia

also began refining its crisis management protocol as part of the efforts to

nurture financial system stability. In addition, Bank Indonesia also actively

disseminated information regarding the banking sector and financial system

to the general public.


64


institution with systemic impact that cannot exit the

financial system without brining it to its knees. Meanwhile,

Thomson (2009)7 stated that a financial institution could

be categorised as systemically important if its default

would involve a significant contagion effect economically,

and, if ignored, would disrupt financial system stability

and subsequently have an inauspicious impact on the

real sector.

Which kinds of institution can be categorised as

asystemically important financial institution? A survey

conducted jointly by the International Monetary Fund

(IMF), Bank for International Settlements (BIS) and the

Financial Stability Board (FSB) in 30 countries, including

Indonesia, concerning regulations associated with the

supervision of systemically important financial institutions

revealed that financial institutions in the form of banks,

insurance companies and pension funds have the largest

potential systemic impact. The survey also found that

banks are the most important institutions and have the

potential to trigger systemic risk prior to a crisis. After a

crisis has struck,however, not only banks but also insurance

companies and pension funds are considered to have a

potential systemic impact.

How to determine which financial institutions to

categorise as systemically important financial institutions?

The financial service board categorises G-SIFI based upon five

indicators, namely size, interconnectedness, substitutability,

cross-jurisdictional activity and complexity.

How are these five indicators measured? FSB

recommended that the Basel Committee compile a

methodology to assess G-SIFI (G-SIB) using quantitative

and qualitative indicators. To this end, the Basel Committee

developed a methodology, known as the indicator based

approach. The selected indicators reflect every aspect of

the impact of externalities, which can push a bank towards

instability.

The advantages of this approach include the multi-

dimensional scope of systemic importance, the ease of use

and that it is more robust than the current model-based

measurement that uses fewer data sets. Each respective

category is given the same weighting of 20%. The impact

of regulations on G-SIB is significant because banks in

this category must have sufficient capital for higher loss

absorbency compared to other banks.

In addition to the identification of SIFI, comprehensive

measures are required to curb their degree systemic impact.

The collapse of Lehman Brothers demonstrated that the

failure of a SIFIcan have a significant impact on financial

stability. On the other hand, the idea of too-big-to-fail is

an incentive for SIFI to take excessive risk. The measures

that can be taken in order to reduce the degree of systemic

impact as well a moral hazard, which emerges from the

idea of too-big-to-fail are as follows:

1. Impose a higher capital charge on SIFI.

A higher capital charge would function as a

disincentive for financial institutions to become

systemically important.

2. Impose more intensive supervision of SIFI.

More intensive supervision would reduce the incentive

for financial institutions to become systematically

important. This measure must be supported by a

greater number of supervisors. On the other hand,

SIFI supervisors must be given a broader mandate

to supervise the soundness of SIFI and implement a

measured resolution considering that the impact of

a failed SIFI or a SIFI in trouble on financial stability

is significant

3. Subject SIFI to cross-border supervision through

a supervisory college.

The failure of a systemically important financial

institution, particularly a global SIFI, has a significant

7 James B. Thomson On Systemically Important Financial Institutions and Progressive Systemic Mitigation, Policy Discussion Paper, Federal Reserve Bank of Cleveland, August 2009.

65


impact on global financial stability. In order to limit

the contagion effect and harmonise the handling of

a SIFI that operates across borders, the cross-border

exchange of information and supervisor cooperation

is vital. The mechanism to facilitate an exchange of

ideas as well as improve coordination can be achieved

through supervisory colleges.

Supervisory colleges are working groups of supervisors

who supervise an international banking group. The

goal of supervisory colleges is to assist supervisors

broaden their knowledge and understanding of the

risk profile of a banking group or individual financial

institution that is part of the banking group. In

their development, supervisory colleges play an

important role in a crisis as a means to exchange

information relevant to the contingency plan and

crisis management.

4. Bail-in Mechanism.

Bail-in represents an effort to ameliorate the market

discipline of creditors and wholesale depositors.

Through the bail-in mechanism the deposits of

wholesale depositors and the debt of creditors

will be converted into capital in the event that the

respective SIFI runs into difficulties or experiences

default. As a consequence of bail-in implementation,

creditors will face costs that reflect more closely the

level of risk associated with the corresponding SIFI.

Therefore, bail-in is expected to reduce moral hazard

stemming from the belief of too-big-to-fail as well as

guarantee more balanced competition betweenSIFI

and non-SIFI.

Bank Indonesia, as the banking authority, is currently

familiarising itself with the criteria to determine systemically

important banks. Assessments of size, interconnectedness,

substitutability and complexity are currently in the process

of being refined.

Regardless of the SIFI framework, it is critical that

the supervision of such financial institutions continues

effectively. In particular for banks that are categorised as

systemic, the supervisory procedure must be conducted

more intensively. Likewise, the resources associated with

oversight require greater capacity and must be available in

sufficient quantity. The technology and approaches used

must enable the supervisors to effectively supervise earlier

in order to avoid bank failure later on.

4.2. REFINING THE CRISIS MANAGEMENT PROTOCOL

TO MAINTAIN FINANCIAL SYSTEM STABILITY

Recent crisis experience reminded the financial

authorities in a number of countries of the need to develop

a crisis management protocol in order to provide the

relevant authorities with guidelines for crisis prevention and

resolution.In fact, mounting risk in the financial system as

a result of financial sector development and the 2007/08

global crisishas forced a number of countries to re-evaluate

and revise their existing crisis management protocol. An

intelligible protocol is required that empowers the relevant

authorities to make quick and effective decisions, but that

still adheres to good governance and does not conflict with

existing laws. In addition, crisis management is required

considering that a crisis can entail colossal costs, financially

and socially, and the recovery process is protracted at best.

Experience from the East Asian banking crisis in 1997/98,

which affected Indonesia severely, is testament to this.

Similar to the measures taken by financial authorities

in several countries, this year Bank Indonesia also refined its

crisis management protocol, hereafter known as PMK BI.

PMK BI represents guidelines that are used as a reference

for Bank Indonesia in its crisis prevention and resolution

efforts. PMK BI was compiled based on a number of key

principles, namely good governance, prioritising crisis

prevention and rapid crisis resolution, as well as effective

66


coordination and communication. The principles of good

governance cover two main aspects, namely that policy

relating to crisis prevention and resolution must be in

harmony with the task and authority of Bank Indonesia

(aspects of responsibility) and that any policy action

or response is accountable (aspects of accountability).

Meanwhile, prioritising crisis prevention and rapid

crisis resolution implies that policy instituted under a

framework of crisis prevention and resolution may differ

from conventional policy taken under normal conditions,

but still adheres to established guidelinesand that the

decision-making process can be expedited under crisis

conditions. Other principles, like effective coordination,

aim to facilitate the formulation of a policy response and

implementation internally at Bank Indonesia as well as

between Bank Indonesia and the Government and/or other

relevant institutions involved with crisis prevention and/

or resolution. Ultimately, the policy response taken must

be communicated to all stakeholders in order to restore

public confidence under a framework of supporting the

subsequent economic recovery. Therefore, the principles

of effective communication are inextricably linked to the

crisis prevention and resolution policy response.

PMK BI is made up of two sub-protocols, namely

the exchange rate and the banking sector considering

that the task and authority of Bank Indonesia covers these

two areas. In general, the scope of PMK BI consists of

surveillance, crisis prevention and resolution, coordination

with the government and/or relevant institutions, as well

as communicating the policy response to stakeholders.

Surveillance, conducted by a relevant work unit at Bank

Indonesia, represents the first line of defence because

this activity identifies the amount of pressure faced by

the economic system and banking system. In this context,

Bank Indonesia divides the pressure into two: namely that

under normal conditions and that under crisis conditions.

Everything related to crisis conditions is subsequently

controlled through PMK BI. In addition,PMK also controls

the decision-making mechanism as well as coordination

under a framework of crisis prevention and resolution.

At all levels of crisis conditions, effective coordination is

critical in order to prevent the crisis or resolve it quickly.

Furthermore, effective and proactive communication of

the policy response taken is important in order to restore

and maintain public confidence.

In the implementation of crisis management

protocol, particularly under crisis conditions, a number

of issues require understanding by all parties, namely the

elements of policy choice in the decision-making process

by the relevant authority. Therefore, the authorities need

to evaluate the policies taken during crisis conditions

and then normalise them again after conditions stabilise.

In addition, existing economic and financial indicators

should not be regarded as rigid and be used as the main

reference point indicating the level of pressure. The level of

pressure determined through surveillance activity involves

a comprehensive analysis of the indicators, triggers and

vulnerabilities, as well as the impact on the banking and

financial system. The dominance of psychological market

factors, particularly during crisis conditions, also requires

deeper understanding, which is a consideration of the

relevant authority when issuing a policy response in order

to avoid exacerbating contagion in the financial system.

Ultimately, the PMK developed by Bank Indonesia

must be synchronised with the PMK of other financial

authorities and institutions because PMK BI is inseparable

from the National PMK. Furthermore, both PMK BI and

the National PMK must be socialised to stakeholders under

a framework of providing greater comprehension to the

public regarding the efforts taken by financial authorities

in terms of crisis prevention and resolution. This will

prevent the reoccurrence of the Bank Century polemic in

2008. Additionally, promulgation of the Financial System

Safety Net Act (UU JPSK) is absolutely required as a legal

67


foundation for the authorities when engaged in efforts to

prevent and resolve a crisis.

4.3. BPD IMPLEMENTATION OF THE REGIONAL

CHAMPION PROGRAM

The challenges faced by the banking community

will become increasingly complex, thereby requiring the

banks to prepare a suitable response. The challenges will

not only be internal but also external. Internal challenges,

among others, include the breadth of the domestic

market, particularly the micro, small and medium sector

as well as equitable regional development, domestic

interest rates that are considered too high, as well as the

competitiveness of some banks that needs to be improved.

Externally, challenges will emerge in line with post-crisis

global developments as well as the planned establishment

of the ASEAN Economic Community (AEC). Anticipatory

measures are required considering that Indonesia is the

largest target market in ASEAN, hence the ratification of

AEC represents a number of opportunities and threats that

must be acknowledged and monitored.

Under Pillar 1 of the Indonesian Banking Architecture,

Bank Indonesia in conjunction with ASBANDA and regional

banks (BPD) across Indonesia completed the BPD Regional

Champion Blueprint, which departs from the internal

and external challenges faced and considers the specific

conditions of regional banks, including:

• The capital of regional banks is relatively low

compared to the average for the national banking

industry, which has the potential to undermine the

resilience of regional banks in the face of competition

from other bank groups in local regions;

• The service provided by regional banks does not

meet public expectations and poor brand awareness

compromises the desirability of the products and

services offered by regional banks, which further

weakens customer confidence;

• Thequalityandcompetenceofhumanresourcesis

below par and the proclivity of BPD to extend credit

to civil servants undermines the role of regional banks

in terms of financing the real sector in local regions.

Consequently, other banks have the opportunity to

step in and provide financing to the real sector, thus

threatening the dominance of regional banks in local

regions;

BPD Regional Champion (BRC) Blueprint

The BPD Regional Champion Blueprint is a BPD

transformation program through the institutional

strengthening of regional banks. Acknowledging the

expanding role and function of regional banks, BPD

are expected to transform themselves and achieve the

vision “to become a leading bank in local areas through

competitive products and services with a broad network

that is managed professionally under a framework of

promoting regional economic growth.” This vision will be

achieved through a series of programs grouped into pillars

as follows: i) institutional resilience, which can operate

efficiently; ii) BPD as an agent of regional development to

support regional economic development; and iii) serving

the needs of the community.

The three pillars of BRC are specified further in

a number of indicators that function as a benchmark

to measure the extent to which a regional bank can

be declared regional champion. The pillar of strong

institutional resilience is expected to mould regional banks

to operate efficiently according to a number of indicators

like core capital (tier 1), ratio of return on assets (ROA), the

efficiency ratio (BOPO) as well as net interest margin (NIM).

Meanwhile, the second pillar, dealing with the regional

bank as an agent of regional development, is expected

to encourage regional banks to contribute to local

economies. Regional banks are not required to disregard

their main purpose of helping stimulate local economic

68


development. The indicators used as a reference include

credit growth, portfolio composition of productive credit,

the loan to deposit ratio (LDR), the composition of public

funds excluding local government funds, increased credit

extension to rural banks and micro finance institutions, the

role as an APEX bank, etc. Meanwhile, the indicators used

to gauge the success of the third pillar, serving the needs of

the community, include increased customer placements in

financial products, access to financial services, the quality

of HRD, scope of office network coverage, etc. Through

the implementation of this initiative it is expected that a

number of regional banks will become regional champions

in their respective locales by 2014.

BRC Implementation

As a form of commitment to implement the BRC

program, on 21st December 2010 a joint agreement was

signed by all directors of BPD and supported by all governors

and commissioners of BPD throughout Indonesia. The vice

president of Indonesia and a number of cabinet ministers

were also present to witness the event.

In the first six months after signing the agreement,

BRC implementation was positive as reflected by the 2011

Bank Business Plan, which contained a BRC implementation

action plan for 2011 as well as socialisation activates

internally and for the stakeholders, ways to enhance the

competence of human resources and preparations for

other forms of infrastructure. BRC is expected to become

an effective tool to encourage the banks to transform

themselves to become more competitive and play a more

significant role in local communities. Awareness and strong

commitment from the stakeholders, including the local

government, directors and commissioners as well as human

resources of BPD, to transform from a comfort zone into

a culture of competition will largely determine the success

of each respective regional bank in the achievement of its

vision “to become a leading bank in local areas through

competitive products and services with a broad network

that is managed professionally under a framework of

promoting regional economic growth.”

4.4. COMPILATION OF A FINANCIAL CURRICULUM

FOR SCHOOLS

Bank Indonesia together with the Ministry of

Education has integrated financial education into the formal

curriculum of primary and middle schools, commencing

with the 2011/12 school year. This represents efforts to

introduce pupils as early as possible to financial education,

in particular to foster a culture of saving, which is part of

the follow-up efforts to Gerakan Indonesia Menabung

(GIM) (Indonesian Saving Movement) announced by

President SusiloBambangYudhoyono in February 2010.

Phased implementation will begin in six cities, namely

Medan, Bandung, Semarang, Surabaya, Banjarmasin and

Makassar, by appointing 12 schools as pilot projects.

Financial education will be integrated as part of

social sciences, not only in the form of intra-curricular

lessons but also extracurricular activities that discuss the

following topics:

The Meaning of Money

1. Money and its benefits.

2. Allowance books.

3. Introducing types of currency.

4. Identifying genuine currency.

5. Types of securities.

6. Types of payment instruments.

Banking Functions

1. The role of banks.

2. Types of banking institutions.

3. Benefit of banking products.

4. Electronic banking system.

5. Types of bank profit.

6. Bank security.

69


The integration process of financial education will not

only involve Bank Indonesia and the Ministry of Education

but also academics from the Indonesian University of

Education (UPI-Bandung) and the department of education

in each respective city. In addition, Bank Indonesia will host

workshops for teachers of social sciences, who later will

be responsible for classroom teaching and extracurricular

activities. In order to maintain quality, a number of

products will support the integration process as follows:

1. Preparation of academic materials;

2. Preparation of integrated financial education

materials with the social sciences curriculum for

primary schools and middle schools.

3. Preparation of an intra-curricular and extracurricular

learning strategy; and

4. Monitoring and evaluating the financial education

program at primary and middle schools.

Financial education activities will subsequently be

broadened to incorporate more schools in the six areas

withexisting pilot projects. This includes involving banks

to facilitate the learning process in the classroom and

outside.

In addition to financial education, the GIM program,

which constitutes part of customer protection under

the Indonesian Banking Architecture, will adhere to the

following strategy:

1. Provide low-cost saving products, hence avoiding a

reduction in public savings as a result of administrative

costs. In this context, 70 commercial banks and a

number of rural banks agreed to launch a savings

product known as ‘TabunganKu’(MySavings), which

totalled 1.8 million bank accounts in July 2011 will

total nominal savings of Rp1.8 trillion;

2. Broaden stakeholder access to education through

an ongoing program. Since November 2010, Bank

Indonesia has hosted student-focused activities and it

is hoped that this program will reach other segments

of society nationally or in line with the individual

requirements and characteristics of each local region;

and

3. Empower the general public to optimally manage

their finances. Bank Indonesia along with the Ministry

of Manpower and Transmigration are currently

preparing a business model to manage the finances

of Indonesian migrant workers, thereby allowing

them to plan and manage their finances, which

will ensure that future foreign exchange generated

can be managed andchannelled into productive

businesses.

71

Article 1. Optimisation of Bank Portfolio Composition in Indonesia

Article

72

Article 1. Optimisation of Bank Portfolio Composition in Indonesia1


73


Optimisation of Bank Portfolio Composition in Indonesia1

Article 1

Iman Gunadi2 and Advis Budiman3

Understanding bank behaviour is a crucial aspect of the decision-making process at a central bank and banking

authority in order to formulate policy that is efficient and on target. In addition, a model that can be used

to conduct policy simulations would be extremely useful for decision-makers. A bank model is developed

in this paper that can be used for policy simulation. The model is designed for use with banks in Indonesia

and is a refinement on various previous models due to the issuance of several new policies. The dynamic

function of this model is one advantage that can be used for the forecasting process.

Keywords: Capital buffer, Procyclicality, Business cycle

JEL Classification: E32, G21

1. INTRODUCTION

1.1 Background

In conducting their business, banks are greatly

affected by economic conditions as well as the array of

policies instituted by the banking and monetary authorities

of a country. Consequently, a lot of research has been

performed to understand bank behaviour in conducting

their operational activities. From the perspective of a bank

as a business, banks tend to optimise their portfolio in

order to increase revenue. Notwithstanding, some research

studies bank behaviour to observe a particular economic

phenomenon, like for instance a credit crunch (Blum and

Hellwig (1995), Diamond and Rajan (2000) and Agung et

al (2001)), bank disintermediation (Alamsyah et al, 2005)

or undisbursed loans (Zulverdy, Muttaqin and Prastowo,

2004) and others.

Under a framework of studying bank behaviour,

a number of models have been developed to assist

policymakers run policy simulations, which are used to

present a broader picture of the potential impacts of a new

draft policy. In Indonesia, policy simulation models are

more commonly developed to help understand the impact

of a particular change in monetary policy on a number of

macroeconomic indicators, including the overarching goal

of monetary policy, namely inflation.

Not a lot of models have been developed for

the case of Indonesia. Zulverdy et al (2004) claimed to

model banks in Indonesia. Agung et al (2001), Zulverdy,

1 The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of Bank Indonesia.

2 Senior researcher at the Bureau of Financial System Stability, Bank Indonesia, Jalan M.H. Thamrin no 2, Jakarta, Indonesia. Email: [email protected], Tel.: +62-21-3817166.

3 Guest researcher at the Bureau of Financial System Stability, Bank Indonesia. Email: advis.budiman@ gmail.com

74


Muttaqin and Prastowo (2004) and Alamsyah et al (2005)

placed more emphasis on specific phenomena in the

Indonesian economy, which involved the role of banks in

its development. However, Zulverdy, Gunadi and Pramono

(2005a, 2005b) developed a bank model to analyse the

impact of a change in policy on bank portfolio in Indonesia.

Nevertheless, with the further development of banking

conditions in Indonesia and the plethora of banking policy

changes, the models mentioned must be reviewed again

and recalibrated accordingly.

A bank optimisation model is built in this paper to

simulate policies instituted by the central bank, specifically

in Indonesia, using a range of new banking and monetary

policies. Several example simulations are also discussed in

order to provide a comprehensive picture of how the model

simulates the different scenarios used. For each scenario

the model also gives portfolio optimisation projections

based on macroeconomic projections and the inclusion

of dynamic elements.

1.2. Methodology

The bank model developed in this paper is tailored

to several of the latest banking policies utilising a modified

version of the banking industry organisation approach

used by Monti (1972) and Klein (1971). Although other

methods like the mean-varied expected utility approach

are more commonly used to study the behaviour of a bank

(Kane and Malkiel (1965), Keeley Furlong (1990), Stiglitz

and Greenwald (2003), Wibowo (2005), Hou (2008) and

others), this method proves to be more difficult if the

objective function is accompanied by many constraints

that represent banking and monetary policy. Freixas and

Rochet (1997) identified a number of weaknesses in this

approach.

Each theory has its own unique characteristics and no

method dominates over the others, therefore, observing

bank behaviour can be achieved using a modified flexible

method, which is powerful enough to overcome the

issues faced in daily bank operations. Accordingly, the

industrial organisation approach is used in this paper. This

method is very simple and easy to understand yet effective

in observing and analysing the impact of an economic

indicator, banking indicator and policy on the behaviour of

a bank, particularly in terms of optimal changes in interest

rates and portfolio.

1.3. Motivation

The research and bank model developed in this paper

for the case of Indonesia is motivated by the following:

1. A recent change in banking regulations in Indonesia,

like the statutory reserve requirement (GWM) and full

implementation of Basel II in 2011, coupled with a

lack of literature to document these changes;

2. A lack of reliable bank models to observe bank

behaviour in Indonesia;

3. A lack of policy simulation tools that can help with

the analysis of banking policy in Indonesia.

2. LITERATURE REVIEW

Bank models using the industrial organisation

approach began appearing in the 1980s. Using this

approach Dermine (1986) explored deposit insurance

and Elyasiani, Kopecky and VanHoose (1995) investigated

the cost of changes in portfolio on the separation of the

optimal value of bank portfolio. In addition, Pausch and

Welzel (2003) conducted research into the affect of the

capital adequacy ratio on a bank’s ability to extend credit to

the real sector and Gunadi (2009) researched the sensitivity

of banks in response to monetary policy in light of changes

in policy and economic conditions.

Although much criticism has been levelled at

this model for the inability to include risk factors when

setting the optimal value (Nys (2004) and Matthew and

Thompson (2008)), several other papers (Dermine (1986),

75


Prisman, Slovin and Sushka (1986), De Bondt, Mojon and

Valla (2005) Pausch and Welzel (2003) and others) have

argued that bank models using the industrial organisation

approach incorporate uncertainty when determining a

bank’s optimal portfolio solution.

A number of empirical studies have been conducted

using this approach. Putkuri (2005) developed an empirical

study of the banking sector in Finland for an oligopolistic

market using quarterly data from 1994-2005. Guevara,

Maudos and Perez (2003) used a bank model to analyse

the evolution of interest rate convergence and level of

competition between banking systems in the euro area

in the period from 1993-2001. In addition, Maudos

and Nagore (2004) provided evidence for the impact

of financial policy, institutions, the macroeconomy and

structure on bank competition in 58 countries between

1995 and 1999.

For the case of Indonesia, Zulverdy et al (2004) used

a dynamic approach to resolve the problem of maximising

bank profit over time accompanied by a number of

constraint functions including the bank balance sheet,

deposit supply function, credit demand function, statutory

reserve requirement and capital adequacy ratio. Zulvery,

Gunadi and Pramono (2005a, 2005b) used this model

to observe to impact of disparity in the statutory reserve

requirement and exchange rate on the optimisation of

bank portfolio.Alamsyah et al (2005) used the model

developed by Zulverdy et al (2004) to observe the

phenomenon of banking disintermediation and its effect

on monetary policy.

The industrial organisation approach (Monti (1972)

and Klein (1972)) assumes that banks continuously strive

to maximise profit, taking into consideration several

factors as constraint functions. Monti used three objective

function approaches. First, banks will maximise profit with

consideration of the deposit supply function. Second,

banks will maximise funds consisting of deposits by

considering the minimum profit that must be achieved.

Third, banks will maximise their utility function made up

of profit and fund mobilization.

Equation 1. Max U= (Π,D) where , D>0

In the three approaches mentioned, banks

simultaneously seek to optimise portfolio, which will

maximise profit and maximise fund accumulation from

the general public. Of the three approaches, the profit

function can be defined most simply as:

Equation 2. Π=rLL + rLiq - r

DD - r

KK

Where L, Liq and K are defined respectively as credit,

liquid assets and bank capital, while rL, r and r

k are the

lending rate, policy rate and cost of capital.

The objective function can be optimised if the first

order condition is equal to zero. However, finding the value

of the parameter used is not simple, there are numerous

technical constraints when using econometric techniques,

significance, signs and stationarity, which are difficult to

consolidate in the bank model. Therefore, the approach

used by Freixas and Rochet (1997) must be modified in

order to simplify the simulations.

3. MODEL

3.1. Model Framework

Assuming that banks operate in perfect market

competition, this paper follows the model developed by

Monti (1972) with the three approaches; however, the

bank objective function is adjusted in two ways. First,

banks maintain adequate liquidity to support financial

system stability. In the model developed by Monti, liquidity

is interpreted as maximum capital accumulation from the

general public. With this approach large credit liquidity

shortfalls will remain. Therefore, including a minimum

∂U ∂U

∂Π ∂

76


liquidity ratio that must be met by the banks is hoped to

alleviate liquidity risk.

Second, banks with the objective of obtaining

maximum profit can be noted from the return on assets,

which is also at a maximum. This ratio already takes into

account effectiveness and efficiency. In order to include

these two modifications, the objective function in Equation

2 can be rewritten as follows:

Equation 3. Max U = π - (liq - ρT d)2

Where π = is the return on assets (ROA), while

liq and d are the ratio of liquidity to total assets and ratio

of deposits to total assets respectively. α is the parameter

adjustment and ρT is the percentage of liquidity that must

be maintained by the bank. In Indonesia, this percentage

is the secondary reserve requirement plus the liquid assets

required for the bank’s operational activities.

In addition to the two modifications mentioned,

the statutory reserve requirement is also included in the

model developed. To this end, this policy construct will be

taken from the model developed by Gunadi (2009) and

Gunadi and Harun (2010) where the GWM ratio is tied to

the bank’s loan-to-deposit ratio (LDR). A higher LDR will

lower the GWM ratio. The relationship between GWM

and LDR can be written as follows:

Equation 4. gwm = ( ρ + ρD ) d - l

Where ρ is the primary reserve requirement and ρ +

ρD is the minimum reserve requirement that must be borne

by the bank if the bank does not extend any credit. In this

context, the bank’s loan-to-deposit ratio is zero. LDR is

the target LDR set by the central bank, and is the

lower GWM incentive in the event of credit allocation.

gwm, d and l are the ratios of GWM, deposits and credit

to total assets. By making each respective portfolio ratio

to total assets, then bank liabilities and assets can simply

be expressed as follows:

Equation 5. d + k = 1 ( Liability )

Equation 6. l + liq + gwm = 1 ( Aset )

Or by substituting equation 4 with equation 6, bank

assets can be written as follows:

Equation 7. l ( 1 - ) + liq + d ( ρ + ρD ) = 1

In order to adopt the bank capital requirement as

stipulated in Basel II, the capital equation in this model

will follow that developed by Pausch and Welzel (2003),

Zulverdy et al (2004) and Gunadi (2009)4, the capital

equation can be expressed as follows:5

Equation 8. Ω =

By substituting equation 8 with 5, bank liability can

be written as follows:

Equation 9. d + Ωl =1

While the function of bank profit, after dividing by

total assets is as follows:

Equation 10. ROA = π = rL l + rliq - r

Dd - r

K Ωl

Assuming perfect market competition, banks will

be price takers. In other words, the policy rate, deposits

and credit as well as the cost of capital are determined

4 Analysis of inequality in the bank capital equation can be found in Pausch and Welzel (2003) and Gundi (2009).

5 Based on Basel II, risk-weighted assets can be split into three categories, namely credit risk, market risk and operational risk. Equation 10 indicates credit risk for a credit portfolio with a 100% weighting, while liquid assets are assumed to have a risk weighting of 0%. For operational risk, CAR can be calculated during the simulation.

α

2 ρD

LDR

k

l

ρD

LDR

77


exogenously. The bank’s problem is maximising its utility

function, namely equation 3, where ROA is defined

according to equation 10 with several constraint functions

like in equations 7 and 9.6

In order to find the optimal solution, the Lagrange

function of the bank equation can be found using the first

order condition.

Equations:

Where , while λ1 and λ

2 are the Lagrange

functions for equations 7 and 9.

By solving equations 7, 9 and 11-13, the solution to

the bank’s problem above is:

Equations:

Optimising the model determines the optimal ratio

of leverage, namely:

Equation 18.

Calculating the leverage ratio supports central bank

policy when determining bank capital in line with the risk

exposure of the bank.

3.2. Parameters and Baseline

By taking the bank data position at the end of

September 2010, the baseline used in this model for the

case of banks in Indonesia is as follows:

6 For the time being, remunerations for the statutory reserve requirement are not included in the model because it would only add to the number of unnecessary parameters when seeking the optimal solution. After an optimal solution is found then this parameter can more simply be included into the optimal solution.

BI rate 0.065

Deposits interest rates 0.096

Credits interest rates 0.137

Cost of capital 0.010

LDR-Target 0.800

Primary reserve requirements 0.080

Incentive reserve requirements 0.080

Liquidity Ratio 0.200

Adj CAR 0.082

Adjustment 6.870

Parameters Baseline Value

By taking a composition of parameters similar to

those above, the optimal composition of bank portfolio

is presented in the following table.

Deposits 0.9384

Credits 0.7507

Capital 0.0616

Liquid Assets 0.1742

Reserve Requirements 0.0751

LDR 0.8000

ROA (profit) 0.0198

CAR 0.0800

Leverage Ratio 16.2440

Portfolio Composition

It can be interpreted from the table above that by

setting the target LDR at 80% and CAR at 8% then optimal

deposits, credit and liquid assets are 94%, 75% and 17%

of total bank assets respectively, with a leverage ratio of

around 16 times the bank’s capital. From these results

78


it can also be interpreted that if the parameters reflect

the current interest rate and policy conditions, then the

bank will turnover larger profits if its liquid assets are less

than the required liquidity ratio, namely around 17% of

deposits.

3.3. SIMULATIONS

3.3.1. A 1% increase in the Bank Indonesia Rate

This simulation was run to find changes in the bank

portfolio composition in the event of a change in the BI

rate. Against a scenario of a 1% hike in the BI rate (to

7.5%), ceteris paribus, the optimal portfolio composition

is presented in the following table.

the composition of liquid assets. A lower composition of

credit coupled with higher deposits would reduce bank

LDR by 14 bps, which is below the target. This scenario

also demonstrates that with higher lending rates banks

can still increase their profits.

3.3.2. A 1% increase in the Primary Reserve

Requirement

This simulation aimed to observe the changes in

bank portfolio composition due to a change in the primary

reserve requirement. Against a scenario of a 1% increase

in the primary reserve requirement to 9%, ceteris paribus,

the optimal portfolio composition is as follows:

Deposits 0.9384 0.9385

Credits 0.7507 0.7495

Capital 0.0616 0.0615

Liquid Assets 0.1742 0.1753

Reserve Requirements 0.0751 0.0752

LDR 0.8000 0.7986

ROA (profit) 0.0198 0.0178

CAR 0.0800 0.0800

Leverage Ratio 16.2440 16.2707

Deposits 0.9384 0.9393

Credits 0.7507 0.7400

Capital 0.0616 0.0607

Liquid Assets 0.1742 0.1743

Reserve Requirements 0.0751 0.0857

LDR 0.8000 0.7878

ROA (profit) 0.0198 0.0183

CAR 0.0800 0.800

Leverage Ratio 16.2440 16.4804

A 1% increase in the primary reserve requirement to

9% causes the composition of deposits and liquid assets

to increase and the composition of credit to total assets

to decrease. Referring to previous research (Zulverdy et

al (2004), Gunadi (2009)), nominally bank deposits and

liquid assets will decrease due to an increase in the primary

reserve requirement. This indicates that total bank assets

will decrease more than the decline in deposits or liquid

assets. In addition, the composition of credit to total bank

assets also decreases, which reduces the LDR. The decline

in the portion of credit is also affected by the decrease in 7 The relationship between lending and savings rates and the BI rate is explained in more detail in Section 4.

Against a scenario of an increasing BI rate, lending

and savings rates will also increase.7 The savings rate and

lending rate increase respectively by 10.1% and 13.9%.

Therefore, this change in the BI rate will have a direct

and indirect impact through lending and savings rates,

which will alter the composition of deposits and credit.

Banks become more attractive places to invest when the

composition of deposits increases. On the other hand,

a decline in the composition of credit would also raise

Portfolio PortfolioComposition Composition

79


capital, which increases the bank leverage ratio. Ultimately,

bank profit will decline.

3.3.3. Resilience of Bank Capital

This simulation is one way to calculate the optimal

amount of bank capital. Before determining the optimal

amount of bank capital, an assumption is required

concerning the magnitude of the desired intermediation

function by all banks. This is critical because a larger

intermediation function not only requires more bank capital

nominally, but also a larger capital buffer is necessary to

absorb the risk that emerges, thereby alleviating potential

instability in the financial system. The capital buffer is

calculated by comparing the level of CAR achieved with the

level of CAR required pursuant to prevailing regulations,

in this case 8%. Consequently, in this simulation several

values of LDR are used to reflect the varying magnitude

of intermediation. Accordingly, previous bank capital will

determine the size of the capital buffer required to support

the bank’s operational activities. In order to obtain a

better policy in terms of capital, the bank’s leverage ratio

is calculated as a supporting value.

The simulation of varying levels of bank

intermediation returned the following results:

4. MODEL APPLICATION

4.1. Projection Framework

In this research banks are assumed to operate under

perfect market competition, where banks are price takers,

hence, the policy rate (BI rate), savings rate and lending

rate are exogenous variables with the exception of the

cost of capital. To find a value for the BI rate additional

data and information is required from different sources.

Furthermore, these exogenous variables are required

when projecting the portfolio composition of a bank.

No discussion is contained within this paper regarding

the methodology to find the value of these exogenous

variables. Consequently, the variables used are taken from

other research.

In order to project the interest rate, this model

utilises the short-term forecast for the Indonesian economy

(SOFIE) model (Bank Indonesia, 2008). Using the SOFIE

model, future savings rates can be calculated if the

current savings rate is known and the BI rate has been

set. Meanwhile, lending rates are affected by savings

rates and non-performing loans. A model can be used to

project non-performing loans, which was developed for

stress testing as part of the Financial Sector Assessment

Program conducted by the International Monetary Fund

(IMF). The projected value of non-performing loans is

influenced by the BI rate, economic growth, inflation and

the real effective exchange rate.

4.2 Simulation Projection Model

The simulations were conducted using assumptions

for the Macroeconomy, SBI, real effective exchange rate

and GDP. Using these assumptions, savings rates, lending

rates and NPL were projected.

80% (baseline) 8% 0.0% 16.2440

83% 10.8% 2.8% 11.9203

85% 12.5% 4.5% 10.1837

90% 16.5% 8.5% 7.5711

95% 20.1% 12.1% 6.1155

100% 23.3% 15.3% 5.1880

LDR CAR CapitalBuffer

LeverageRatio

The higher the loan-to-deposit ratio of a bank, the

level of capital that has to be maintained increases and

the leverage ratio declines.

80


5. SIMULATION PROJECTION MODEL

Other models that could map macro variables with

the bank itself supported the simulation projection model

for a particular bank. Several models were used to explain

the magnitude of savings and lending rates based on the

available macro variables. In order to observe the dynamic

behaviour in this model, a forecast was used in this research

for three variables, namely savings rates, lending rates and

non-performing loans (NPL). The forecasts used were taken

from previous research.

The results of the simulation are presented in the

following table:

Deposits interest rates rD 8.2500 8.8436 8.8690 8.8700 8.8700 8.8700

Credits interest rates rL 14.1509 14.9338 15.0624 15.0766 15.0722 15.0807

NPL 2.9790 2.6248 2.5551 2.3822 2.0207 1.8657

SBI 0.0650 0.0650 0.0650 0.0650 0.0650 0.0650

Deposits interest rates 0.0825 0.0884 0.0887 0.0887 0.0887 0.0887

Credits interest rates 0.1415 0.1493 0.1506 0.1508 0.1507 0.1508

Cost of capital 0.0100 0.0100 0.0100 0.0100 0.0100 0.0100

LDR 0.7800 0.8000 0.8300 0.8500 0.8500 0.8500

NPL NPL 0.0298 0.0262 0.0256 0.0238 0.0202 0.0187

Primary Reserve Requirements 0.0800 0.0800 0.0800 0.0800 0.0800 0.0800

LDR Reserve Requirements 0.0780 0.0800 0.0830 0.0850 0.0850 0.0850

Liquid Assets 0.2000 0.2000 0.2000 0.2000 0.2000 0.2000

CAR 0.0802 0.0802 0.0802 0.0802 0.0802 0.0802

Adjustment 6.8700 6.8700 6.8700 6.8700 6.8700 6.8700

Deposits 0.9396 0.9397 0.9399 0.9401 0.9401 0.9400

Credits 0.7532 0.7527 0.7497 0.7477 0.7478 0.7478

Capital 0.0604 0.0603 0.0601 0.0599 0.0599 0.0600

CAR 0.0802 0.0802 0.0802 0.0802 0.0802 0.0802

Liquid Assets 0.1737 0.1722 0.1720 0.1720 0.1719 0.1719

Reserve Requirements 0.0731 0.0751 0.0782 0.0803 0.0803 0.0803

LDR 0.8016 0.8010 0.7977 0.7953 0.7954 0.7955

Leverage Ratio 16.56 16.57 16.64 16.68 16.68 16.68

ROA (Profit) 3.66% 3.69% 3.73% 3.72% 3.76% 3.79%

CAR (w oprisk) 8.01% 8.01% 8.01%

Capital_buffer 6.0% 7.7% 9.4% 11.1% 12.8% 14.6%

CAR (adjustment) 0.0782 0.0782 0.0782 0.0782 0.0782 0.0782

Additional capital 0 0 0 0 0 0

CAR buffer 0.00% 2.21% 4.51% 6.85% 9.16% 11.51%

Dec - 10

Dec - 10

Dec - 11

Dec - 11

Dec - 12

Dec - 12

Dec - 13

Dec - 13

Dec - 14

Dec - 14

Dec - 15

Dec - 15

Years

Years

81


Simulations were run using baseline parameters with

due regard for the performance of savings and lending

rates. The portfolio composition is presented in the table

above. The composition of term deposits in the portfolio

increased in line with the higher savings rate. Meanwhile,

in terms of assets the portion of credit experienced a

decline while liquid assets increased. Additionally, bank

LDR posted a slight decline.

With the consideration that profit accumulation

is included in capital, it can be seen that bank assets

(assuming that bank assets in 2010 are 100) continue

to increase. Furthermore, bank capital increases, which

indicates that the bank in question has increasingly strong

capital considering that there is a target LDR and the bank’s

liquid assets are maintained.

Several simulations were conducted covering a

variety of scenarios in order to observe the impact of a

policy on the optimal composition of a bank. Furthermore,

the model also tried to project the bank’s portfolio

composition taking into consideration macroeconomic

projections and banking indicators. The dynamic model

was developed using different scenarios, which is expected

to provide policymakers with a clearer picture of the

conditions of a particular bank over time.

6.2. Implications and Recommendations

Despite the weaknesses, the bank model developed

in this research has a number of advantages in simulating

the impact of policy on the banking system. Therefore,

this model can be used as an additional tool to assist

policymakers at the central bank with the supplementary

information required when formulating new polices. By

using this model as an operational tool, the weaknesses

of the model will be further exposed and possible

enhancements will be forthcoming. Further development of

this model is required in order to increase its usefulness.

6.3 Follow-up Research

Looking at the results of this research there are a

number of measures that can be taken to improve the

results. Further research and development could include:

1. The type of market in the model developed in this

research should be further developed to represent

an oligopoly, which can better capture market

conditions and interaction between the banks and

money market.

2. The types of deposits and credit could be developed

to be more diverse although the optimal solution

would become more complex. Nevertheless, this

kind of model would be more useful in simulating

capital policy in line with Basel II, which includes a

variety of risks.

Asset 100.00 111.95 125.88 141.57 158.78 178.30

Deposits 93.96 105.19 118.31 133.08 149.26 167.61

Credits 75.32 84.26 94.38 105.84 118.73 133.33

Capital 6.04 6.76 7.57 8.49 9.52 10.69

Liquid Assets 17.37 19.28 21.65 24.35 27.30 30.64

Reserve

Requirements 7.31 8.40 9.85 11.37 12.76 14.32

ROA (Profit) 3.66 4.14 4.69 5.27 5.97 6.75

Net Profit 3.58 4.05 4.60 5.17 5.85 6.62

2010 2011 2012 2013 2014 2015

Years

6. CONCLUSION

6.1. Conclusion

This research is the development and recalibration

of previous models from several research papers used

to simulate policy, in particular in the banking system of

Indonesia. Differing from past research, this paper uses the

respective ratios of bank balance sheet items against the

total assets of the corresponding bank. A number of issues

that developed were accommodated under a framework

of reducing liquidity risk and credit risk, thereby bolstering

financial system stability.

82


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85

Article 2. Procyclicality Of Banks’ Capital Buffer In Asean Countries

Procyclicality Of Banks’ Capital Buffer In Asean Countries

Article 2

Elis Deriantino, Bank IndonesiaEmail: [email protected]

Abstract. By developing two models to estimate the effect of business cycle on bank’s capital buffer and

the effect of capital buffer on bank’s loan supply on annual panel data (1997-2009) of 63 commercial banks

in five ASEAN countries, we find strong evidence of procyclicality pattern of capital buffer among banks in

ASEAN countries. Banks are found to reduce their loan growth when business cycle turns downwards due

to the impaired lending capacity as a result of a need to raise capital buffer to cover increasing riskiness

of the credit default. Nevertheless, this procyclicality effect is somewhat small, given that a decrease of 1

percentage point in GDP growth will reduce loan growth by around 0.4 percentage points due to the rise

of capital buffer. As Basel Committee for Banking Supervision (2010) proposes a new capital requirement

regime to address issue of procyclicality of capital requirement, this empirical finding may become input for

country’s bank regulator in determining optimal capital buffer level in such a way that it will effective to

prevent volume of credit from being excessive during the upturn sides of business cycle while provide banks

greater resilience that enable them to continue reasonable lending activities during the downturn sides of

business cycle.

Keywords: Capital buffer, Procyclicality, Business cycle

JEL Classification: E32, G21

1. IntroductIon

The risk sensitivity of capital requirement as proposed

by Basel (1988 Basel Standard and Basel II) framework

is considered leading to a certain degree of cyclicality in

capital requirement that potentially will amplify business

cycle fluctuation through decreasing bank’s lending

activity during the downturns side of business cycle

hence pose a threat to the stability of macroeconomic

and financial system, in a so-called procyclicality of capital

requirement. Many previous studies, among those are

the works by Bikker & Metzmeker (2004), Ayuso et al.

(2002), Chiuri et al. (2001) and Drumond (2009) confirm

the procyclicality of capital requirement by pointing out

to negative co-movements between business cycle and

banks’ capital. However, in practice, most banks hold

more capital (capital buffer) than the regulatory minimum.

Stronger supervision for market discipline, lesson learnt

from the past crises and the need to adopt a sound

risk management to anticipate increasing probability of

default during economic downturns are some factors

that motivate banks to hold more capital despite the fact

it may more costly for banks to hold more capital (Borio,

86


et al (2001) and Ayuso et al. (2002)). This additional

buffer should provide banks with greater resilience that

also enable them to maintain a reasonable volume of

lending activities during economic downturns. Study by

Jokipii & Milne (2006) finds that capital buffers of RAM

(10 countries that joined the European Union (EU) in May

2004) banks correlate positively with the business cycle and

banks in these countries tend to hold more capital buffer

than those of banks in other EU regions. This confirms

well capitalized bank may have countercyclical prudent

behavior. Nevertheless, the above studies focus to identify

the existence of procyclicality of capital requirement but

lack in detail assessment on effect of the pattern on

banks’ lending activity. Thus, even though it is generally

considered that the capital requirement is procyclical, it still

needs to assess whether this pattern will have substantial

impact to the volume of credit to economy. This implies

two policy questions, ie. (i) do bank’s capital buffer actually

exhibit a significant procyclical pattern and (ii) does this

pattern of capital buffer constraint loan supply of banks

substantially?

The aim of this paper is to answer the two policy

questions. We employ annual bank-level panel data of

63 listed banks with coverage period 1997-2009 in five

Association of South East Asian Nations (ASEAN) countries:

Indonesia, Singapore, Malaysia, Thailand and Philippine.

To the best of our knowledge, none of existing studies has

explored the evidence from ASEAN countries using data

period that covers two major crises that hit the region:

the 1997/98 Asian Financial crisis and the 2008/09 Global

Financial crisis. By examining the ASEAN data, the present

study will contribute to the literature on this area.

By developing two models to estimate the effect

of business cycle on banks’ capital buffer and the effect

of Capital buffer on bank’s loan supply we find strong

evidence of procyclicality pattern of capital buffer among

banks in ASEAN countries. Banks are found to reduce their

loan growth during economic downturns due to a rise in

capital buffer as a result of impaired loan quality (rising

NPL). Nevertheless, this procyclicality effect is somewhat

small, given that a decrease of 1 percentage point in GDP

growth will reduce loan growth by around 0.4 percentage

points due to the rise of capital buffer while during the

observed period banks’ loan growth average in those

ASEAN countries is around 11%. Moreover, the results

also indicate that risk proxy NPL has significant and positive

relationship with capital buffer, meaning that banks with

a relatively risky credit portfolio tend to hold more capital

buffer. This evidence which is also supported by the fact

of ASEAN banks tendency to hold sizeable buffer above

minimum requirement (the average of banks’ capital buffer

is around 13.5% above the country’s minimum regulatory

capital during the observed period) shows these ASEAN

banks are adopting relatively sound risk management that

has contributed to moderate the effect of procyclicality of

capital requirement. These prudently capitalized banks

come up after years of strengthened prudential regulation

and supervisory framework as a result of lesson learnt from

the region own financial crisis in 1997/98.

2. data, Methodology & eMpIrIcal Models

2.1. data

We employ annual unbalanced bank-level panel

data of 63 listed banks with coverage period 1997-2009

in five ASEAN countries: Indonesia, Singapore, Malaysia,

Thailand and Philippine. Due to the data availability, we

select banks that minimum have data coverage period

from 2004-2009. The data period covers full business cycle

in respective countries and two major crises that hit the

region: the 1997/98 Asian Financial crisis and the 2008/09

Global Financial crisis.

Banks indicators data are obtained from Bankscope

while macro economy data of each country are from

CEIC.

87


2.2. Methodology & empirical Models

To address the two policy questions, we adopt the

strategy of Wong et al (2010) by developing two models,

ie:

1. estimating the effect of business cycle on

banks’ capital buffer

In this model, capital buffer (Buffer) is modeled as

a function of business cycle (proxied by real GDP growth)

with control variables as prescribed in previous empirical

studies including Return on Equity (ROE) as proxy for cost

of holding capital and ratio of Non Performing Loan (NPL)

as proxy for banks’ risk profile:

Bufferi,t = α0 + α1Buffer

i,t-1 + α2GDP

j,t + α3NPL

i,t +

α4ROEi,t + μ

i + ε

i,t …………………………..(1)

Where i= individual bank index, 1,2…,N; j=country

index, 1,2…,M; t=year index, 1,2…,T; μi captures

individual bank time invariant idiosyncrasies effect and

εi,t is an error term.

The dependent variable Buffer is defined as additional

capital set by individual bank in a country above country’s

minimum regulatory capital1, ie. bank’s Capital Adequacy

Ratio - country’s regulatory minimum requirement.

The inclusion of the first lag of Buffer as one of

independent variable is intended to capture bank’s

adjusting cost (Ayuso et al, 2002).

Real GDP growth (GDP) is a proxy for business cycle

indicator. A negative co-movement between GDP and

Buffer indicates the procyclicality pattern of capital buffer.

On contrast, a positive relationship between capital buffer

and business cycle indicates banks adopt prudent capital

behavior by increasing its capital during the upturns side

of business cycle in order to have adequate buffer to

cover loss that most likely to increase as economic enter

downturn phase (Borio et al, 2001).

The cost of holding capital is proxied by Return on

Equity (ROE), and its effect on Buffer is expected to be

negative.

Banks’ risk profile is proxied by Non Performing Loan

ratio (NPL) and its impact on capital buffer is also expected

to be negative.

Given the dynamic nature of this model due to the

inclusion of lagged Buffer as an independent variable,

we estimate the model by employing two steps System

Generalized Method of Moments system (GMM Sys)

method. We choose GMM Sys over differenced GMM

because when T is small and series persistency is high

(α1 close to 1), the differenced GMM estimator has poor

finite sample bias and low precision since lagged levels

of the series provide weak instruments for subsequent

first differences while utilizing GMM Sys will reduce this

finite sample bias and increase the precision of estimator

due to the exploitation of additional moment conditions

(Blundell et al, 2000, Bond et al, 2001). By utilizing

Monte Carlo simulation, Soto (2009) provides evidence

that GMM Sys generates lower bias and higher efficiency

than other estimators for panel data with small number of

cross section N and T and high persistency series. We also

estimate the model using Least Square Dummy Variable

(LSDV) and Ordinary Least Square (OLS) methods to check

whether or not the coefficient of lagged capital buffer of

GMM Sys estimation is biased. An unbiased coefficient of

lagged capital buffer should lie between those estimated

by FELS and OLS, given the fact that LSDV estimators are

downward biased due to the negative correlation between

the transformed lagged dependent variable and the

transformed error term whilst OLS estimators are upward

biased due to the positive correlation between the lagged

dependent variable and the individual effects.

1 Minimum regulatory capital ratio for Indonesia and Malaysia: 8%, Thailand:8.5%, Philipine:10% and Singapore: 10% since May 2004 (12% before May 2004).

88


2. estimating the effect of capital buffer on

bank’s loan supply.

In this stage, we model loan growth (Loan) as a

function of banks’ capital buffer (Buffer), business cycle

(GDP) and interbank market interest rate (IR):

Loani,t = β

0 + β

1GDP

j,t + β

2IR

j,t + β

3Buffer

i,t+

νi + ζ

i,t …..…...(2)

Where i= individual bank index, 1,2…,N; j=country

index, 1,2…,M; t=year index, 1,2…,T; νi captures individual

bank time invariant idiosyncrasies effect and ζi,t is an error

term.

The procyclicality impact of capital buffer on bank

loan growth will be indicated by negative co-movement

between Buffer and Loan. Both business cycle and interest

rate are proxies for demand side factors of loan growth.

Business cycle is expected to have positive correlation with

loan growth while interest rate will have negative impact

on loan growth.

We estimate model (2) using LSDV method. Finally,

the procyclicality effect of capital buffer on lending activity

is then calculated as a multiplication of sensitivity of banks’

capital buffer to GDP growth in model (1) and sensitivity

of loan growth to capital buffer in model (2):

(α2*(mean GDP/mean Buffer) / (1-α

1)) *( β

3*(mean

Buffer/mean Loan))

3. eMpIrIcal fIndIng

3.1. descriptive statistics

Table 1 below shows that in general banks in

ASEAN hold a sizeable capital buffer. The resilience and

risk profile of banking system during the global financial

crisis 2008/09 is much improved than a decade ago when

Asia financial crisis hit the region in 1997/98 as indicated

by almost double Buffer for period of 2008/09 than that

of 1997/98 as well as lower NPL in 2008/09 than that of

1997/98. The ASEAN region has also been considered

to have high potential to emerge as another economic

force in the world. Recent economic development as

indicated by GDP growth has provided evidence of greater

resilience of ASEAN countries in weathering the economic

downturn caused by the 2008/09 global financial crisis,

particularly Indonesia and Philippine that despite lower

economic growth than those of previous years, still

experience positive economy growth during the 2008/09

global crisis.

table 1.descriptive statistics

Mean Min Max st.dev

period: 1997-2009Buffer 13,46 -8,5 133,3 18,10Loan 10,53 -237,53 194,40 35,74NPL 9,52 0,13 89,98 11,30ROE 13,69 0,00 59,55 8,72GDP 3,82 -13,13 9,24 4,24IR 7,55 0,44 51,06 5,77

period: 1997-1998asian financial crisis

Buffer 6,58 -8,00 37,20 9,95Loan -21,18 -135,05 68,81 46,49NPL 12,74 0,14 57,07 14,08ROE 12,51 0,00 53,76 11,37GDP -0,93 -13,13 8,55 7,53IR 17,89 1,50 51,06 15,21

period: 2008-2009global financial crisis

Buffer 11,46 1,88 121,00 15,54Loan 11,82 -83,50 193,42 23,03NPL 4,01 0,17 15,43 2,99ROE 11,59 0,23 37,39 6,41GDP 1,93 -2,30 6,01 3,95IR 2,87 0,44 11,24 3,35

3.2. regression result

The results on the table below suggest that strong

evidence of procyclicality pattern of capital buffer among

banks in ASEAN countries. Banks are found to reduce their

loan growth during economic downturns due to a rise in

capital buffer as a result of impaired loan quality (rising

NPL). Nevertheless, this procyclicality effect is somewhat

small, given that a decrease of 1 percentage point in GDP

growth will reduce loan growth by around 0.4 percentage

points due to the rise of capital buffer, while during the

observed period banks’ loan growth average in those

ASEAN countries is around 11%. The estimation result

of model (2) also indicates that credit rationing during

89


economy downturn in ASEAN banks is driven more by

demand side factors rather than by the supply-driven

capital buffer.

4. conclusIon and polIcy IMplIcatIon

By developing two models to estimate the effect of

business cycle on banks’ capital buffer and the effect of

Capital buffer on bank’s loan supply on annual panel data

(1997-2009) of 63 commercial banks in ASEAN countries,

we find strong evidence of procyclicality pattern of capital

buffer among banks in ASEAN countries. Banks are found

to reduce their loan growth during economic downturns

due to a rise in capital buffer as a result of impaired loan

quality (rising NPL). Nevertheless, this procyclicality effect

is somewhat small, given that a decrease of 1 percentage

point in GDP growth will reduce loan growth by around

0.4 percentage points due to the rise of capital buffer.

As Basel Committee for Banking Supervision (2010)

proposes a new capital requirement regime to address issue

on procyclicality of capital requirement, of which banks

are required to set conservative capital and countercyclical

capital buffer, this empirical finding may become input for

country’s bank regulator when considering implementing

this new capital regime. Taking into account the nature

of their banks procyclicality effect, banks’ regulator may

determining optimal capital buffer level in such a way

that it will effective to prevent volume of credit from

being excessive during the upturn sides of business cycle

while provide banks greater resilience that enable them to

continue reasonable lending activities during the downturn

sides of business cycle.

5. references

Ayuso, J., A. Gonzales, J. Saurina. 2004. Are capital buffers

pro-cyclical?: Evidence from Spanish panel data.

Journal of Financial Intermediation 13,249-264.

Basel Committee on Banking Supervision. 2010.

Countercyclical capital buffer proposal. Consultative

document. Bank for International Settlements.

Bikker, J., P. Metzemakers. 2004. Is bank capital

procyclical? A cross country analysis. DNB Working

table 2.regression result

LoanEstimation Method OLS LSDV GMM Sys LSDVIndependent variablec -0,38 2,57 0,51*** 21,31***

[-0,26] [1,04] [2,96] [4,17]

Buffer(i,t-1) 0,88*** 0,65*** 0,80***[26,08] [9,57] [293,56]

GDP(j,t) -0,27** -0,18** -0,45*** 1,88**[-2,26] [-2,03] [-20,40] [2,30]

NPL(i,t) 0,28** 0,33* 0,49***[2,38] [1,65] [41,87]

ROE(i,t) 0,08 0,04 0,02[1,61] [0,78] [1,61]

IR(j,t) -1,30***[-4,30]

Buffer(i,t) -0,51***[-4,75]

Adj-R -sqr 0,79 0,81 0,19DW 1,92 1,93 1,70

AR (1) (p-val) -1,92 (0,06)*AR (2) (p-val) 0,48 (0,63)Sargan test (p-val) 55,71 (0,37)

dependent Variable

Buffer

Note: *,**,*** indicate a level of confidence of 90%, 95% and 99%, respectively.

Moreover, the results of model (1) also indicate that

risk proxy NPL has significant and positive relationship

with capital buffer, meaning that banks with a relatively

risky credit portfolio tend to hold more capital buffer. This

evidence shows that banks in ASEAN region are adopting

relatively sound risk management that has contributed to

moderate the effect of procyclicality of capital requirement.

This relatively sound risk management is also supported

by the evidence of the tendency of ASEAN banks to

hold sizeable buffer above minimum requirement (the

average of banks’ capital buffer is around 13.5% above

the country’s minimum regulatory requirement during the

observed period). These prudently capitalized banks come

up after years of stronger supervision as a result of lesson

learnt from the region own financial crisis in 1997/98.

90


Paper No.009/2004, De Nederlandsche Bank NV.

Blundell, R., Bond, S., and Windmeijer, F. 2000. Estimation

in dynamic panel data models: improving on the

performance of the standard GMM estimators.

The Institute of Fiscal Studies Working Paper, No.

00/12.

Bond. S., Leblebiciouglu, A., and Schiantarelli, F., 2004,

GMM estimation of empirical growth models,

mimeo, September 2001.

Borio,C.,C.Furfine, and P. Lowe. 2001. Pro-cyclicality of

the Financial System and Financial Stability: Issues

and Policy Option, BIS Papers, No. 1.

Chiuri M C, Ferri G and Majnoni, G, 2001. The

macroeconomic impact of bank capital requirements

in emerging economies; past evidence to assess the

future, mimeo, World Bank.

Financial Stability Forum, 2009. Addressing Procyclicality

in the Financial System.

Soto, M. 2009. System GMM estimation with a small

sample. Institut d’Analisi Economica, Barcelona.

Wong, E., Fong, T., and Choi, H. 2010. An empirical

assessment on procyclicality of loan-loss provisions

of banks in EMEAP Economies. Presentation delivered

at 11th Annual Bank of Finland/CEPR conference,

Helsinki 7-8 October 2010.

Drumond, I. (2009). Bank Capital Requirements, Business

Cycle Fluctuations and the Basel Accords: A Synthesis.

Journal of Economic Surveys, Vol. 23, Issue 5, pp.

798-830.

Jokipii, T and Milne, A. (2006). The cyclical behavior of

European bank capital buffer. Research Report.

Swedish Institute for Financial Research.

91

Attachment : Summary of Bank Indonesia Regulations concerning Financial System Stability (Semester I-2011)

AttachmentSummary of Bank Indonesia Regulations

concerning Financial System Stability

(Semester I-2011)

92



93


In 2011, Bank Indonesia promulgated an array

of regulations in order to create and maintain financial

system stability. The regulations were introduced to directly

legislate banking activity as follows:

1. Bank Indonesia Regulation No.13/1/PBI/2011,

dated 5th January 2011, regarding ratings and risk

assessment for commercial banks.

A change in business complexity and risk profile,

the application of consolidated supervision as well

as a different approach to assessing bank conditions

internationally all affected the way in which bank

soundness is evaluated.

2. Bank Indonesia Regulation No.13/2/PBI/2011, dated,

12th January 2011, concerning the Implementation

of commercial banks’ compliance function.

The compliance function is a preventative measure to

ensure that policy, regulations, systems, procedures

and business activity conducted by a bank remain

pursuant to prevailing Bank Indonesia regulations

and existing laws, including the principles of Islamic

banking (for Islamic banks and Islamic business units),

and to ensure bank compliance to their commitments

to Bank Indonesia and other relevant authorities.

3. Bank Indonesia Regulation No.13/3/PBI/2011

regarding the status of bank supervision.

The background and aim of this regulation is

to provide a time limit for each level of bank

supervision as well as demand clear efforts from the

management and shareholders to resolve troubled

banks, otherwise the level of supervision will be

increased.

4. Bank Indonesia Regulation No.13/4/PBI/2011, dated

21st January 2011, legislating the repeal of Bank

Indonesia Regulation No.10/22/PBI/2008 regarding

the fulfilment of the domestic corporate requirement

for foreign exchange at banks.

This regulation aims to provide assurance of sufficient

foreign exchange on domestic markets for the

domestic corporate sector. With the improvement in

the domestic economy and domestic forex market,

local firms can now meet their requirement for

foreign exchange through a general mechanism on

the domestic market.


24th January 2011 stipulates the maximum financing

limit for Islamic rural banks.

The application of prudential principles is required

in the allocation of funds, among others, with the

diversification of funds allocated in order to avoid

credit risk centring on customers or a group of

customers using certain facilities. Therefore, an

adjustment was required to regulation No.31/61/KEP/

DIR, dated 9th July 1998, regarding the maximum

lending limit for rural banks.


24th January 2011, determines the handling of

Islamic rural banks under special surveillance.

In order to maintain public confidence in the Islamic

rural banking industry and propel sound industry

growth, restructuring was required for systemic

Islamic rural banks. Follow-up measures in line with

the capacity of the Islamic rural bank, commitment

Summary of Bank Indonesia Regulations concerning Financial System Stability (Semester I-2011)

94


from the owners as well as alternative opportunities

are required to optimise the restructuring of troubled

Islamic rural banks.


28th January 2011, amends a previous regulation,

PBI No.7/1/PBI/2005, on offshore bank loans.

This regulation reintroduces certain restrictions on

the daily balance of short-term offshore bank loans,

namely that it must not exceed 30% of the bank’s

capital written off on 14th October 2008 as a policy

response to anticipate the impact of the global crisis

triggered by the Lehman Brother’s bankruptcy. At

the time, outflows began to surge, which led to tight

bank and domestic forex liquidity. This regulation

aims to: 1) apply macroprudential principles in the

management of short-term foreign bank loans; 2)

encourage longer-term offshore bank loans; and

3) support the achievement of macro and financial

system stability.


8th February 2011, which amends the prior regulation

PBI No.10/18/PBI/2008 dated 25th September 2008,

regarding restructuring the financing of Islamic banks

and Islamic business units.

This regulation was issued as a follow-up to Bank

Indonesia Regulation No.13/13/PBI/2011, dated 24th

March 2011, regarding the assessment of earning

assets for Islamic banks and Islamic business units,

which aims to explain more clearly the criteria used

to determine the quality of earning assets in the form

of financing.


dated 9th February 2011, regarding an amendment

to Bank Indonesia Regulation No.12/19/PBI/2010

about the minimum statutory reserve requirement

for commercial banks at Bank Indonesia in rupiah

and foreign currency.

This regulation was issued due to the inundation

of foreign capital flows that significantly raised

the amount of bank forex liquidity. The goal is

to strengthen bank liquidity management as well

as manage the flows of foreign capital by Bank

Indonesia through a policy to raise the statutory

reserve requirement for foreign currency.


dated 3rd March 2011, regarding the repeal of Bank

Indonesia Regulation No.3/2/PBI/2001 about the

allocation of small business loans and Bank Indonesia

Circular No 3/9/BKR concerning the guidelines for

extending credit to small businesses.

This regulation was issued due to the promulgation of

Act no 20, 2008, regarding micro, small and medium

enterprises, on 4th July 2008, which superseded Act

no 9, 1995, on small businesses, which broadened

the criteria for micro, small and medium enterprises

that had previously only acknowledged small

businesses.


17th March 2011, which amends Bank Indonesia

Regulation No.5/26/PBI/2003 regarding the monthly

report of Islamic banks.

This regulation was issued due to the increase in

information included on the daily commercial bank

report, for instance information regarding short-term

offshore loans, business funds, the Jakarta interbank

offered rate (JIBOR) as well as the new enhancement

system that boosted performance and availability of

information.


regarding the asset quality assessment of Islamic banks

and Islamic business units, which supersedes Bank

Indonesia Regulation No.8/21/PBI/2006 on the asset

quality assessment of sharia compliant commercial

banks and amendments to PBI No.9/9/PBI/2007 and

PBI No.10/24/PBI/2008.

95


This regulation was issued in light of Act no 21,

2008 on Islamic Banking, in order to bolster robust

industry growth and development while adhering

to prudential principles and Islamic principles, as

well as harmonising with existing regulations for

conventional banks. Assessing asset quality in the

form of provisions for earning asset losses is a form

of risk management that aims to ensure Islamic banks

and Islamic business units are able to absorb their

expected losses.


regarding assessing asset quality for Islamic rural

banks, which repeals Bank Indonesia Regulation

No.8/24/PBI/2006 regarding assessing asset quality

for Islamic compliant rural banks.

This regulation was issued due to the amendment

to Act no 21, 2008, regarding Islamic banking,

in order to bolster robust industry growth and

development while adhering to prudential principles

and Islamic principles, as well as harmonising

with other prevailing Bank Indonesia regulations.

Assessing the quality of assets and the formation of

provisions for earning asset losses covers productive

assets, non-productive assets and placements held

at conventional commercial banks.


dated 23rd June 2011, regarding the supervision

of foreign exchange activity at non-bank financial

institutions.

The issuance of this regulation was motivated by the

requirement for LLD data with a shorter time lag, as

well as more complete and accurate information,

and to reduce the burden on the reporting institution

by minimising redundancy in the reports submitted

to Bank Indonesia. This regulation is expected to

complete and boost the accuracy of LLD data and

information as well as reduce data redundancy in the

reports submitted to Bank Indonesia like those for

foreign debt and trade in foreign exchange. Several

aspects of the LLD report were refined, particularly

relating to the scope of data and reporting, as well

as periodization and sanctions.


22nd September 2011, regarding the amendment

to Bank Indonesia Regulation No.8/12/PBI/2006 on

periodic commercial bank reports (State Gazette of

the Republic of Indonesia No 91, 2011; Supplement

of the State Gazette of the Republic of Indonesia

Number 5240).

This regulation was promulgated due to the

requirement to expedite the submission process of

several reports in order to optimize the benefits of

other reports. The report formula was refined as well

as additional reports requested, including: i) a report

of the calculation for risk-weighted assets pertaining

to credit risk using the standard method; and ii) a

report of the prime lending rate. Several regulations

were amended to remain in harmony with other

reporting regulations.

DIRECTOR

Wimboh Santoso Suhaedi Linda Maulidina

COORDINATOR & EDITOR

Dwityapoetra S. Besar Iman Gunadi

WRITERS

Agusman, Pungky P. Wibowo, Anto Prabowo, Endang K. Saputra, Wini Purwanti, Henry R. Hamid,

Bambang Arianto, Ita Rulina, Sri Noerhidajati, Wahyu S. Hidayat, Fernando R. Butarbutar, Noviati,

Diana Yumanita, Januar Hafidz, Reska Prasetya, Kurniawan Agung, Nuraini Yuanita, Risa Fadila, Heny

Sulistyaningsih, Mestika Widantri, Elis Deriantino, Hero Wonida, Primitiva Febriarti, Advis Budiman,

Harris Dwi Putra, Louvti Sidabalok

CONTRIBUTOR

Directorate of Credit, Rural Bank Supervision and SMEs

Directorate of Bank Licensing and Banking Information

COMPILATOR, LAYOUT & PRODUCTION

Suharso, Ratih Maharani, I Made Yogi, Farah Fadilla, Dyta Tri Utami, Arliza Putri Wardhani

Financial Stability ReviewNo. 17, September 2011

Financial Stability Review

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