Bank Indonesia, Financial Stability Review No.10, March 2008

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∆.

Published by:

Bank Indonesia

Jl. MH Thamrin No.2, Jakarta

Indonesia

This edition was launched in March 2008 and is based on data and information available as of December 2007, except where

stated otherwise.

The complete Financial Stability Review is available for download in PDF format from Bank Indonesia»s website : http://www.bi.go.id

Any 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 foster public awareness regarding domestic and global financial system stability issues;

To analyze potential risks confronting the domestic financial system;

To evaluate progress and issues related to financial system stability; and

To recommend policies to relevant authorities for promoting a stable financial system.

Financial Stability Review( No. 10, March 2008 )

iii

Foreword vi

Overview 3

Chapter 1 Macroeconomic Conditions and

the Real Sector 9

Macroeconomic Conditions 9

Conditions in the Real Sector 14

Box 1.1. Macroeconomic Stress Test 19

Box 1.2. Potential Pressure from Foreign Debt 20

Chapter 2 Financial Sector 25

Structure of the Indonesian Financial System 25

Banks 25

Funding and Liquidity Risk 25

Credit Growth and Credit Risk 27

Market Risk 34

Profitability and Capital 36

Non-Bank Financial Institutions and the Capital

Market 39

Finance Companies 39

Capital Market 40

Box 2.1. Insurance Industry Performance and

Potential Risk on the Financial System 45

Chapter 3 Prospects of the Indonesian Financial

System 51

Economic Prospects and Risk Perception 51

Bank Risk Profile: Level and Direction 52

Prospects of the Indonesian Financial System 53

Potential Vulnerabilities 54

Box 3.1.Impact of Fuel Price Increases on Financial

System Stability 56

Box 3.2.Natural Disasters, Life Cycles and Financial

System Stability 57

Chapter 4 Financial Infrastructure 61

Payment System 61

Payment System Performance 61

Payment System Policy and Risk Mitigation 62

Credit Information Bureau 63

Financial System Risk Mitigation 65

Financial System Stability Forum 65

Crisis Management Protocol 65

Articles

Article 1 Property Industry Survey:

Observing Potential Pressure on

Repayment Ability 69

Article 2 Household Balance Sheet Survey :

Significant Indicators in Financial System

Stability Surveillance 77

Glossary 89

Table of Contents

iv

1.1 Global Economic Indicators 10

1.2 Indonesia»s Non-oil/gas Exports by Country 10

1.3 Indonesian Economic Growth 13

1.4 Impacts of Exchange Rate to Conglomeration

Equity 16

1.5 Competitiveness Rating √ World Economic

Forum 17

2.1 Price Index Performance of Several Regional Stock

Exchanges 41

2.2 Sectoral Price Index 42

3.1 Consensus Forecasts of Several Economic

Indicators 51

3.2 Indonesian Risk Perception 52

4.1 Settlement Value and Volume Development in

BI-RTGS System 62

4.2 Payment Card Transactions 62

4.3 Comparisons of DIS Regulations 64

Table Box:

2.1.1 Insurance Company Expansion 2003-2006 45

3.1.1. Projected Gross NPL in 2008 against Various Oil

Price Scenarios 56

1.1 Global Stock Price Index 9

1.2 Indonesian Non-Oil/Gas Exports 10

1.3 Value of Indonesian Non-Oil/Gas Imports 10

1.4 Price Index of Several Commodities 11

1.5 International Interest Rate 11

1.6 Real Interest Rate in Indonesia and USA 11

1.7 Standard & Poor»s Outlook Sovereign Rating for

Indonesia 11

1.8 Moody»s Outlook Sovereign Rating for

Indonesia 12

1.9 Fitch Outlook Sovereign Rating on Indonesia 12

1.10 Capital Inflow Composition 12

1.11 Composition of Foreign Portfolio Capital Flow 12

1.12 Investment Portfolio Ratio 12

1.13 Rupiah Exchange Rate Performance 13

1.14 Foreign Exchange Rate 13

1.15 Indonesian inflation and BI Rate 13

1.16 Domestic Interest Rate 14

1.17 Variance between Loan and Fixed Deposit Rates 14

1.18 Consumer Confidence Index Performance 14

1.19 Consumption Credit 15

1.20 Growth of ROA and ROE 15

1.21 Debt-to-Equity Ratio 15

1.22 Non Financial Public Listed Companies

Probability of Default (December 2007) 15


Probability of Default (June 2008) 15


Probability of Default (December 2007 and

June 2008) 16

1.25 Net Foreign Exchange Liabilities to Capital Ratio 16

1.26 Sectoral GDP Growth 17

1.27 Financing of Public Listed Companies and their

Expansion (Asset Growth) 17

1.28 Unemployment Rate in Indonesia 17

1.29 Growth of DER and TL/TA 18

2.1 Financial Institutions» Assets 26

2.2 Growth in Deposits by Currency (m-t-m) 26

2.3 Growth in Deposits by Component (m-t-m) 26

2.4 Liquid Asset Ratio of Banks 27

2.5 Average Interest Rate of O/N Inter-Bank Money

Market 27

List of Tables and Figures

Table Graph

v

2.6 Credit Growth 28

2.7 Composition of Productive Assets 28

2.8 Foreign Currency Loans 28

2.9 Growth by Loan Type 28

2.10 Credit Allocation by Economic Sector 29

2.11 Undisbursed Loans 29

2.12 Non-Performing Loans 30

2.13 NPL Nominal 30

2.14 Nominal NPL by Bank Group 30

2.15 Gross NPL by Bank Group 30

2.16 Nominal NPL by Economic Sector 31

2.17 NPL Share by Economic Sector 31

2.18 NPL by Loan Type 31

2.19 NPL Share based on Loan Type 31

2.20 Gross NPL Performance 32

2.21 Gross NPL Ratio for Consumption Credit 32

2.22 Nominal NPL of the Corporate and MSME

Sectors 33

2.23 Gross NPL of the Corporate and MSME Sectors 33

2.24 NPL of Foreign Currency and Rupiah

Denominated Loans 33

2.25 Stress Test of NPL against CAR 34

2.26 Credit, NPL and Loan Loss Provisions 34

2.27 Interest Rate and Exchange Rate Performance 35

2.28 Lending Rate by Bank Group 35

2.29 Rupiah Maturity Profile 35

2.30 Foreign Exchange Maturity Profile 35

2.31 Growth of NOP (Overall) 36

2.32 SUN Ownership by Banks 36

2.33 Bank NII 37

2.34 ROA Ratio by Bank Group 37

2.35 Komposisi Pendapatan Bunga Bank 37

2.36 CAR Ratio by Bank Group as of Semester II 2007 37

2.37 Core Capital Ratio to Risk Weighted Assets and

CAR 37

2.38 Map of Core Capital Performance 38

2.39 Integrated Stress Test 38

2.40 Operational Activities of Finance Companies 39

2.41 Financing Activities of Finance Companies 39

2.42 Performance of Finance Companies 39

2.43 National Private Finance Companies» Source of

Funds 40

2.44 Joint Finance Companies» Source of Funds 40

2.45 Inflows to SUN-SBI-Shares 41

2.46 Asian Stock Market Volatility 41

2.47 Regional Stock Exchange: Share Index

Performance 41

2.48 Stock Market: Transaction Value & JSX 42

2.49 Market Efficiency Coefficient 42

2.50 Stock Market: Capitalization Value & Issuance

Value 42

2.51 Price Performance of Several Series of SUN 42

2.52 Yield of 5-Year Tenure Investments 43

2.53 SUN Ownership 43

2.54 SUN: Market Liquidity of Various Tenures 43

2.55 Issuance and Position of Corporate Bonds 43

2.56 Net Asset Value of Mutual Funds by Type 44

2.57 Mutual Funds: Net Asset Value & Participating

Units 44

2.58 Mutual Funds: Redemptions and Subscriptions 44

2.59 Composition of Mutual Funds» Net Asset Value 44

3.1 Bank Risk Profile and Direction 53

3.2 Financial Stability Index 53

4.1 Payment System Transaction Activities in

Semester II 2007 61

Graph Box :

1.2.1 Foreign Debt 20

1.2.2 Debt Burden Indicators of Indonesia 20

1.2.3 Indonesia ULN Payment Plan 20

2.1.1. Insurance Capital 2003-2006 45

2.1.2. Assets-Premiums-Claims: 2003-2006 45

2.1.3. Insurance Profits: 2003-2006 45

2.1.4. Several Insurance Company Indicators 46

2.1.5. Investments by Insurance Companies:

2003-2006 46

2.1.6. Premiums: Unit Link and Total: 2003-2006 46

2.1.7. Investment Return: Unit Link against Total:

2003-2006 46

3.1.1. Bank NPL and Global Oil Price 56

vi

By expressing thanks and praise to God Almighty, we are pleased to present the Financial Stability Review (FSR)

No. 10, March 2008. The FSR is one of the reports presented to our stakeholders regarding the implementation of

Bank Indonesia»s primary function, which aside from safeguarding monetary stability is also to maintain financial

system stability.

As with previous reviews, this edition features analysis results on current sources of instability, risk mitigation measures

and future financial stability prospects. In addition, this particular edition includes two articles pertaining to the results of

recent property credit and household financial balance surveys. The inclusion of these articles is deemed pertinent because

history has demonstrated that financial crises can stem from a collapse in the property sector and the inability of the

household sector to repay outstanding liabilities to financial institutions.

The publication of this FSR is also deemed strategic considering the mounting challenges facing the Indonesian

financial sector. The greatest challenge emanates from the global economy, mainly as a result of the subprime mortgage

crisis that is sweeping major countries across the globe. This crisis has also triggered escalating uncertainty and shattered

the confidence of business players in the global financial market. In addition, the soaring global prices of oil and basic

food commodities have sparked the threat of rising inflation amidst sluggish global economic growth. Domestically, the

challenges come from the intense frequency of natural disasters plaguing the country and macroeconomic conditions

that still yet to reach the levels in 2007.

The unrelenting challenges we face require the focused attention of all related stakeholders in the financial sector.

To support awareness, up-to-date information is critical coupled with detailed reviews of financial sector issues. Through

the publication of FSRs, it is expected that such information and reviews will be routinely available for the benefit of all

related parties, including business players, government officials, academics and analysts.

It is important to note that the year 2007 was one of the finest years in the context of financial system stability. The

Indonesian financial sector was well maintained, whereas banks, which dominate the financial sector, continued to shine.

The intermediation function improved with credit growth reaching 25.5%, whereas gross non-performing loans (NPL)

dropped below 5% for the first time since the crisis. In the future, one key challenge is to direct credit growth towards

more productive purpose and promote the advancement of micro, small and medium enterprises, which have proven to

be resilient to the crises.

Foreword

vii

With respect to the above expectations, once again we welcome the publication of this edition of the Financial

Stability Review. For that, we would like to extend our sincere gratitude to all parties who have directly and indirectly

contributed to the publication of this review. May the fruits of this review prove useful in maintaining future financial

system stability that can safeguard the macroeconomic stability for the prosperity of the general public.

Jakarta, March 2008

DEPUTY GOVERNOR

BANK INDONESIA

Muliaman D. HadadMuliaman D. HadadMuliaman D. HadadMuliaman D. HadadMuliaman D. Hadad

1

Overview

Overview

2

Overview

This page is intentionally blank

3

Overview

Indonesian financial system stability during the second semester of 2007

was well maintained and future prospects remain upbeat. This was achieved

through the sustained support of macroeconomic stability as well as real

sector performance, which continued to improve although not quite as well

as expected. Financial sector performance, in particular the banking sector,

also picked up, which stimulated growth in loan extension as well as improved

the quality of the loans. Non-bank financial institutions and the capital markets

carried on expanding amid increasing pressure stemming from global financial

markets. The securities market also experienced satisfactory growth despite

confronting pressure several times during 2007, for which the negative

impacts were mitigated. Looking towards the future, the persisting sources

of instability require close monitoring and the negative impacts must be

mitigated, among others through the Crisis Management Protocol jointly

coordinated between the relevant authorities for banking, the capital markets

and non-bank financial institutions.

1. SOURCES OF INSTABILITY

In the second semester of 2007 financial system

stability was beset by even greater challenges than were

faced during the previous period. The sources of instability

that have prevailed since the preceding semester continued

amid dynamic developments in the financial sector.

In general, pressure on the financial system during

the second semester of 2007 mainly emanated from the

external environment. This was primarily reflected by

fluctuations in the global financial market. In fact, global

stock markets were corrected more frequently due to

increasing uncertainty and waning confidence among

business players in the global financial market, which

represented the second-round effects of the subprime

mortgage crisis. There has been no direct involvement of

Indonesian banks in subprime mortgage transactions.

However, due to ever increasing integration between the

domestic and global economies, global financial market

volatility triggered by the subprime mortgage crisis

Overview

4

Overview

promptly affected the domestic financial sector. As a

consequence, any pressure on the global stock market

rapidly led to a deep correction in Indonesia»s equity market.

Such conditions can jeopardize the financial system,

especially if a simultaneous sudden reversal of capital flows

occurs.

Increasing external volatility was also attributable to

the elevated global prices of oil as well as basic

commodities. In the reporting period, the global price of

oil passed the USD110 per barrel mark. Meanwhile, the

prices of basic commodities have also risen sharply,

particularly the prices of farm and mining products as well

as natural resources. These price hikes spurred the threat

of high inflation, which could undermine public purchasing

power, both globally and domestically. In terms of the

financial sector, high inflation would reduce debtor

repayment capacity, potentially leading to an increase in

non-performing loans (NPL).

Another significant issue that contributed to

increasing external volatility was sluggish global economic

performance, principally caused by the heavy economic

burden currently befalling the United States. Following the

subprime mortgage crisis economic growth in the United

States has been slow, with several experts in the field even

expecting an impending recession. A slowdown in global

economic growth will exert additional pressures on the

financial sector as it weakens the performance of exporters

as the customers of banks and other financial institutions.

Meanwhile, high dependence on bank financing,

constraints in the real sector and high concentration on

consumer loans persist as the prevailing sources of

instability. With such high dependence on bank financing,

any fluctuations or crises in the banking sector would

rapidly affect other industries in the financial sector. The

protracted resolution of the various issues currently

affecting the real sector, such as unemployment and limited

infrastructure, may encumber investment activities and

disrupt operations in the business community.

Despite the slightly higher rise in working capital

credit growth compared to consumption credit during the

reporting period, ongoing vigilance is imperative in order

to avoid over concentration on consumption credit. Such

a concentration could imperil the financial sector,

particularly if household income becomes insufficient to

repay outstanding loans to banks and other financial

institutions. In addition, concentration on consumption

credit may diminish the willingness of banks to extend

productive loans, which are, in fact, crucial to support

sustainable economic growth.

Natural disasters have plagued Indonesia regularly

in recent years, which constitute yet another source of

instability that should be carefully observed. Regardless of

the various measures undertaken by Bank Indonesia in

terms of regulating the special handling of bank loans in

affected areas, if wide-reaching natural disasters persist,

financial system stability will almost certainly be affected.

Another important source of instability is associated

with the ever increasing integration of banks and non-

bank financial institutions that has led to a blurring of the

distinction between the products offered by banks and

those offered by other financial institutions. Innovation of

financial products that is not supported by comprehensive

risk mitigation and sufficient product transparency may

harm the consumers and endanger financial system

stability.

Furthermore, the possibility of security disruptions

due to the upcoming General Election should be taken

into account. Even though previous general elections have

passed relatively peacefully and the public are becoming

increasingly familiar with the dynamics of democratic

parties, the financial sector should remain cautious and

try to anticipate any potential disturbances to financial

5

Overview

system stability, including those associated with

preparations for the General Election.

2. RISK MITIGATION

To reduce the possibility of financial sector instability,

several risk-mitigation steps have been implemented. First

was strengthening bank risk management. During the

reporting period, the implementation of risk management

has been improved, partially as a result of risk-management

certification for bankers as well as the additional

preparations taken by banks in accordance with Basel II

implementation. Additionally, the introduction of risk-

based supervision by bank supervisors has encouraged

banks to implement better risk management.

Risk mitigation has also been reinforced through

more effective surveillance on the financial system.

Therefore, the review and development of various

surveillance methods and approaches should continue to

be pursued, either quantitatively through stress tests and

simulations, or qualitatively through the regular monitoring

of sectoral performance for sectors with direct and indirect

impacts on financial system stability, for example the real

and household sectors.

To reduce dependence on banks, risk mitigation can

be applied, among others, through financial deepening

which allows non-bank financial institutions to play larger

roles in the financial sector. Financial deepening also allows

the development of hedging and derivative markets,

therefore, financial institutions and business players alike

can employ sound risk management.

To reduce the risks associated with volatility in the

global market, closer coordination between the relevant

authorities for banking, the capital markets and other

financial institutions is critical and must be pursued further.

Through close coordination anticipative steps can be

formulated prior to the problem spreading. Furthermore,

prioritizing the role of the Financial System Stability Forum

(FSSF) and expediting draft legislation for the Financial

Sector Safety Net Act represent two more important

avenues which must be explored in more depth.

Notwithstanding, Crisis Management Protocol, which sets

out the procedures and steps to be taken during a crisis, is

critical in the context of maintaining financial system

stability.

3. OUTLOOK FOR FINANCIAL SYSTEM STABILITY

In the future, financial system stability is expected to

be maintained despite facing more arduous challenges in

2008, particularly stemming from the economic downturn

in the United States and the oil price hikes, as well as

contagion from the intense pressure building in the global

financial market. This positive view is supported by

improved bank risk management and tighter surveillance

of financial system stability, both in terms of the method

and coverage area. In addition, various stress tests that

have been conducted strongly indicate that banks, as the

foundation of the financial sector, are resilient to the risks

associated with credit, the interest rate and exchange rate

as well as the price of government debt securities/

government bonds (SUN).

Stronger bank capital has further raised optimism

for the future. Regulations stipulating a minimum core

capital (tier 1) of Rp80 billion by the end of 2007 have

been met by all commercial banks. Furthermore, the

requirement for all commercial banks to retain a minimum

core capital of Rp100 billion by 2010 is expected to

strengthen bank capital enabling the banks to confront

larger risks.

Amid rising uncertainty in the global financial market,

the prospects of the Indonesian financial system remain

positive due to stronger commodity prices and better risk

management. Despite the rising trend in commodity prices

6

Overview

attributable to uncertainty, it is also important to note that

rising prices will open new business opportunities in sectors

like mining (coal), alternative energy and plantations (crude

palm oil, soybean and sugar cane).

Efforts to maintain financial system stability require

adequate information regarding all relevant sectors. To

gauge property sector performance earlier an Early

Warning System (EWS) model was developed which

explains property credit behavior. The resultant model

indicates that property NPL over the upcoming 6 months

will decrease but then rise again in the subsequent 12

months. Furthermore, the results of a household balance

sheet survey conducted at six locations (Bodetabek, D.I.

Yogyakarta, West Java, Central Java, East Java and West

Sumatra) demonstrated that all households surveyed are

able to repay their outstanding liabilities to the banks and

non-bank financial institutions. This implies that the

resilience of the financial system stemming from the

household sector, especially at the six locations surveyed,

is not a cause for concern. In the future, to illustrate a

more complete picture regarding the role of the household

sector in maintaining financial system stability, the

household balance sheet survey should be expanded to

cover more locations throughout Indonesia.

7

Chapter 1 Macroeconomic Conditions and the Real Sector

Chapter 1Macroeconomic Conditionsand the Real Sector

8



9


1.1. MACROECONOMIC CONDITIONS

The performance of the global economy during the

second semester of 2007 was dominated by volatility due

to the widening impacts of the subprime mortgage crisis

and the soaring global price of oil. The subprime mortgage

crisis represents the turning point of the high-risk credit

scheme provided by financial institutions to finance

housing. The crisis struck in 2006; however the impacts

only began to spread early in the second semester of 2007.

Reports of losses by major investors in subprime

mortgage loans, including highly reputable banks in the

United States (US) and Europe, followed by reports of

increasing delinquency and foreclosure rates on subprime

mortgage debtors, triggered negative sentiment and forced

investors to make huge redemptions at that time. The

redemptions affected the financial markets of other

countries, including emerging markets, thus weakening

the global stock market index. However, conversely, the

Indonesian stock market index continued to climb up to

the end of December 2007, despite increased volatility.

The relatively small impact of the subprime mortgage crisis

Throughout the second semester of 2007, macroeconomic stability in

Indonesia was well protected from volatility in the global financial market.

Economic expansion continued, despite the expectation of a slowdown in

2008 triggered by the soaring global oil price. During the reporting period,

inflation remained under control and the domestic interest rate started to

decline, providing the opportunities for economic activity.

on Indonesia»s domestic financial market was principally

due to the absence of financial institutions in Indonesia

that directly invest in such loans. In addition, the buoyant

domestic equity market was also bolstered by improving

macroeconomic fundamentals.

The second round effects of the subprime mortgage

crisis weakened the purchasing power of consumers in

the US. Lackluster household consumption spending

limited corporate sector revenue, which triggered waves

of redundancies. As household consumption spending is

the primary contributing factor of economic growth in the

Graph 1.1Global Stock Price Index

Source: Bloomberg

2006 20070

5,000

10,000

15,000

20,000

25,000

30,000

35,000

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000Singapore HongkongNew York Dow JonesIndonesia Nikkei

Macroeconomic Conditionsand the Real Sector

Chapter 1

10


US, such a decline undermined the US economic growth

in 2007, declining by 0.4% to 2.2%. It is therefore

reasonable that many economists form a conjecture that

the US is approaching an impending recession.

As the US represents almost 20% of the global

economy, when the US sneezes the whole world catches

a cold. Consequently, in 2007, the IMF estimated global

economic growth to slow down to 4.9%. The deceleration

is primarily attributable to sluggish growth in developed

economies. On the contrary, economic growth remained

robust in developing countries; particularly China and India.

grew by 16.5% (y-o-y), slightly below growth for 2004-

2006, which averaged 18.8% per annum.

USA 14.61 14.07 14.00 13.19 12.00Canada 0.80 0.71 0.70 0.67 0.59Singapore 10.46 10.86 10.60 9.82 9.57Malaysia 4.80 5.01 4.92 4.84 5.05India 3.53 3.94 4.34 4.37 5.26Japan 14.44 15.17 14.76 15.21 14.35China 5.64 6.09 6.01 6.98 7.31South Korea 3.74 3.27 4.03 4.23 4.10Europe 18.31 16.51 16.24 16.11 15.72

Table 1.2Indonesia»s Non-oil/gas Exports by Country

Country 2003 2004 2005 2006 2007

Source: BI

Graph 1.2Indonesian Non-Oil/Gas Exports

Graph 1.3Value of Indonesian Non-Oil/Gas Imports

Source: BI

Millions of USD Millions of USD

2006 2007

ManufacturingMining and Quarrying

Agriculture, Hunting, FishingTotal

0

1000

2000

3000

4000

5000

6000

7000

8000

0

1000

2000

3000

4000

5000

6000

7000

8000

Millions of USD Millions of USD

Source: BI

2006 2007

ManufacturingMining and QuarryingAgriculture, Hunting, FishingTotal

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

The continuing economic decline of the US has the

potential to undermine economic growth in emerging

market countries in line with tighter competition between

exports among countries, particularly in Asia. This is due

to the diminishing purchasing power of households in the

US, who are the main consumers of exported products

from Asian countries. In Indonesia, however, such

conditions have relatively insignificant effects on export

value and volume. Up to November 2007, the export value

of Indonesia grew rapidly despite a slightly slower rate.

During the first 11 months of 2007, Indonesian exports

World Output*) 4.4 5.0 4.9 4.1

Advanced Economies*) 2.5 3.0 2.6 1.8

Emerging & Developing Countries*) 7.0 7.7 7.8 6.9

Consumer PriceAdvanced Economies 2.3 2.3 2.1 2.0

Emerging & Developing Countries1) 5.2 5.1 5.9 5.3

(exclude Zimbabwe)

LIBOR2)

US Dollar Deposit 3.8 5.3 5.2 4.4

Euro Deposit 2.2 3.1 4.0 4.1

Yen Deposit 0.1 0.4 0.9 1.1

Oil Price (USD) - average3) 41.3 20.5 6.6 9.5

Table 1.1Global Economic Indicators

Category 2005 2006

%%%%%Projection

2007 2008

Source: World Economic Outlook - IMF October 2007*) World Economic Outlook Update Projection - IMF January 2008

Indonesia»s relatively high export value is mainly

supported by the rising price of export commodities in the

international market, particularly oil, CPO, tin and rubber.

11


suppressing the negative sentiment prevalent in the

market. As a result, the indices of global stock exchanges,

which had plummeted due to redemptions, began to

slowly rebound.

The sharp reduction in the Fed fund rate spurred a

higher interest rate differential in emerging markets

countries against the interest rate of the US. Economic

growth in these emerging market countries remained

relatively strong with bullish expectations of a high

investment return, which generated positive sentiment in

emerging market countries, including Indonesia. The higher

real interest rate in Indonesia compared to the US, better

rupiah returns and the improving sovereign rating awarded

to Indonesia by international ratings agencies, have all

helped generate more foreign investment inflows to

Indonesia.

Graph 1.5International Interest Rate

Furthermore, increasing diversification amongst Indonesia»s

export target countries, trending more towards Asian

countries, particularly China and India, also supports strong

export performance. The increase in exports to these two

key countries may compensate the decline in exports

stemming from economic problems in the US.

In an attempt to recover the US» economy, the Federal

Reserve (Fed) reduced its federal funds rate to 4.25% in

December 2007, reducing it further to 2.25% in March

2008. In addition to the reduction in the interest rate, the

Fed also injected large amounts of liquidity into the banking

system and financial market to prevent any further

deepening of the potential economic crisis in the US. In

addition, a number of other central banks also undertook

such measures. The steps taken by the Fed and several

other central banks were sufficiently effective in

% %

SIBOR ECB FFR LIBOR

Source: Bloomberg

0

1

2

3

4

5

6

2001 2002 2003 2004 2005 2006 2007 20080

1

2

3

4

5

6

Graph 1.4Price Index of Several Commodities

Graph 1.6Real Interest Rate in Indonesia and USA

Graph 1.7Standard & Poor»s Outlook Sovereign Rating

for Indonesia

Sources: Bloomberg, BI, BPS

% %

2005 2006 2007

US

Indonesia

-8

-6

-4

-2

0

2

4

-8

-6

-4

-2

0

2

4

Jul-92 Sep-94 Dec-96 Feb-99 Apr-01 Jul-03 Sep-05 Nov-07

SD

CCC+

B

B+

BB-

BB

BB+

BBB-

BBB

BBB+

SD

CCC+

B -

B

B+

BB-

BB

BB+

BBB-

BBB

BBB+

SD

CCC+

B-

B

B+

BB-

BB

BB+

BBB-

BBB

BBB+

Source: Bloomberg

Stable Outlook

Source: BI

2000 2001 2002 2003 2004 2005 2006 20070

50

100

150

200

250

300

350

400

450

500

0

50

100

150

200

250

300

350

400

450

500Oil CopperTin GoldPalm Oil CoffeeRice RubberAluminium

12


However, uncertainty regarding the possible further

propagation of the subprime mortgage crisis led to extreme

caution on the part of investors. They tended towards

short-term investments in the form of financial asset

portfolio. In 2007, the share of the capital flow portfolio

in the capital flow component reached 55%, whereas the

share of Foreign Direct Investment (FDI) was 45%.

Meanwhile, investment share in Bank Indonesia Certificates

(SBI) vastly increased to 14%. On a regional scale, the

portfolio ratio of Indonesia in terms of the Capital Account,

FDI and foreign exchange reserves were higher than

Thailand and Malaysia, but remained lower than the

Philippines.

Greater export performance and persistent portfolio

investment inflows to Indonesia supported the Indonesia

Balance of Payments (BoP) surplus in 2007, which

surpassed that of 2006. The growing BoP surplus helped

increase forex reserves to USD56.92 billion in December

2007; equal to 5.7 months of imports and foreign debt

repayments.

Along with the BoP surplus, an attractive return on

the rupiah and well-maintained risk factors, the rupiah

Graph 1.8Moody»s Outlook Sovereign Rating for Indonesia

Graph 1.9Fitch Outlook Sovereign Rating on Indonesia

Graph 1.10Capital Inflow Composition

Graph 1.11Composition of Foreign Portfolio Capital Flow

Graph 1.12Investment Portfolio Ratio

Jun-97 Dec-98 Jun-00 Dec-01 Jun-03 Nov-04 May-06 Nov-07

CCC+

B

B

B+

BB-

BB

BB+

BBB-

BBB

CCC+

-

B

B+

BB-

BB

BB+

BBB-

BBB

Source: Bloomberg

Positive Outlook

Mar-94 Jun-96 Oct-98 Jan-01 May-03 Aug-05 Nov-07Caa1

B3

B2

B1

Ba3

Ba2

Ba1

Baa3

Baa2

Source: Bloomberg

Stable Outlook

% of Total Liabilities, BOP

37

72

57

45

63

28

43

55

2004 2005 2006 2007

Direct investment (in Indonesia)Portfolio investment (Liabilities)

0

10

20

30

40

50

60

70

80

Source: BI

% of Total Liabilities, BOP

11

1822

1615

63

14

40

-1

1923

-4

6

-2

3

Bond & Note (Public)Others - SBI (Public)Equity Securities (Private)Debt Sec. (Private)

-10

-5

0

5

10

15

20

25

30

35

40

45

2004 2005 2006 2007Source: BI

%

PI/CAPI/FDIPI/Int»l Reserve

Thailand Malaysia Philippines Indonesia

Source: BI

0.00

0.50

1.00

1.50

2.00

0.100.24

1.040.94

0.28

0.80

2.18

1.63

0.03 0.03 0.120.20

13


exchange rate in 2007 appreciated, on average, by 0.44%

reaching Rp9,125 by year end. However, when the rupiah

is compared to several other currencies during 2007, the

rupiah exchange index remained the lowest despite

volatility staying under control.

Controlled exchange rate volatility and consistent

monetary policy to maintain price stability improved inflation

expectations. During the second semester of 2007, the

inflation rate remained manageable. In general, the inflation

rate in 2007 stayed within the corridor set by Bank Indonesia

(BI), namely 6%±1%. Controlled inflation rate expectations

enabled the BI rate (policy interest rate) to decline gradually

and measurably, reaching 8.00% in December 2007.

Increases of exports and consumption power,

supported by well-maintained macroeconomic stability,

Graph 1.13Rupiah Exchange Rate Performance

Graph 1.15Indonesian inflation and BI Rate

Graph 1.14Foreign Exchange Rate

controlled inflation and a declining interest rate, stimulated

the Indonesian economy to continue growing apace

despite the slowdown in the global economy. In 2007

economic growth reached 6.33%, which exceeded the

previous year of 5.48%.

IDR/USD

Source: Bloomberg

IDR/USD

9,47

49,

255

9,15

78,

929

9,01

89,

366

9,12

89,

093

9,15

59,

174

9,13

89,

087

9,07

59,

077

9,17

29,

095

8,84

28,

981

9,06

79,

358

9,10

59,

102

9,26

79,

356

8,500

8,600

8,700

8,800

8,900

9,000

9,100

9,200

9,300

9,400

9,500

9,600

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 122006 2007

9,238

9,181

8,968

9,109

9,295

9,108 9,124 9,1349,125

9,165 9,210

9,0399,129

9,201

Monthly AverageQuarterly AverageAnnual AverageSemester Average

8,500

8,600

8,700

8,800

8,900

9,000

9,100

9,200

9,300

9,400

9,500

9,600

Source: BloombergNote: rising index = stronger exchange rate

2 0 0 7

SGD PHP KRW EURJPY IDR THB

Index Index

85

90

95

100

105

110

115

Jan Feb Mar Apr May Jun Jul Ags Sep Oct Nov Dec85

90

95

100

105

110

115

1 January 2007 = 100

Sources: BPS & BI

2005 2006 2007

% %

Inflation (y-o-y)

BI-rate

0

4

8

12

16

0

4

8

12

16

GDP Growth (%) 5.60 5.48 5.99 6.34 6.52 6.47 6.33

- Sisi Pengeluaran

- Consumption 4.41 3.91 4.57 4.60 5.43 6.92 5.41

- Investment (Gross

Fixed Capital Form) 9.93 2.91 7.82 6.96 8.83 9.75 8.37

- Exports 8.60 9.16 8.95 9.78 7.78 9.14 8.00

- Imports 12.35 7.57 8.45 7.29 8.15 9.64 8.38

Table 1.3Indonesian Economic Growth

Indicator 2007

%%%%%

2007

Q I Q II Q III Q IV2005 2006

Source: BI

The risks stemming from external sector

vulnerabilities are expected to remain high in the future.

This is primarily attributable to the potential expansion

of the subprime mortgage crisis in the global economy

through the financial markets, as well as inflationary

pressures due to price hikes affecting global oil and food

commodities. In addition, uncertainty remains prevalent

regarding a global economic recession induced by a

weaker U.S. economy, especially if the economic

stimulation package introduced by the U.S. Government

14


fails to abate the declining conditions currently

compounding their domestic economy. Against this

unfavorable backdrop, global economic growth in 2008

-estimated by IMF in October 2007 to reach 4.8%- was

corrected in January 2008 down to 4.1%. Such conditions

also decreased the domestic economic growth projections

to a level of 6.5% according to the IMF. This figure is,

however, in harmony with BI estimates which put growth

in 2008 at 6.2%-6.8%.

Such macroeconomic performance affected

financial sector resilience. This was evident, among others,

from macro stress tests concerning credit risk in the

banking industry (see Box 2.1). In addition to the

macroeconomic factors, financial sector resilience was

also influenced by foreign debt. Analysis on potential

pressure emanating from foreign debt is elaborated in

Box 2.2.

1.2. CONDITIONS IN THE REAL SECTOR

Improved economic fundamentals enabled a gradual

decrease in the BI Rate which was closely followed by other

domestic rates. By end of the second semester of 2007,

interest rates for investment credit, working capital credit

and consumption credit dropped by 98 bps, 88 bps and

78 bps respectively compared to the end of the previous

semester, to 13.01%, 13.00% and 16.13%. The reduction

in the BI Rate was partially transmitted to the lending rates,

illustrated by a relatively wide spread between lending rates

(particularly consumption credit) and the deposit rate.

However, expectations of low interest rates and well-

maintained macroeconomic stability encouraged positive

sentiment. This, in turn, prompted consumer confidence

(demand) and producer optimism (supply) regarding future

economic growth.

From the demand side, greater consumer confidence

was reflected by the upsurge in the Consumer Confidence

Index, which boosts private consumption.1 This was also

evidenced by the rise in consumer loans. Increasing private

consumption was, among others, caused by the decreasing

interest rate and also supported by stronger public

1 Consumer Survey in December 2007. The survey has been routinely conducted everymonth since October 1999 by the Directorate of Economic and Monetary Statistics,Bank Indonesia

Graph 1.17Variance between Loan and Fixed Deposit Rates

%%

0

2

4

6

8

10

0

2

4

6

8

10

2005 2006 2007

Source: BI

Average Working CapitalLoans

InvestmentLoans

ConsumerLoans

Graph 1.16Domestic Interest Rate

Source: BI

% %

Consumer Loans

Investment Loans

Working Capital Loans

BI-rate 1-month SBI

1-month Rp Time Deposits

Savings Deposits

0

5

10

15

0

5

10

15

2005 2006 2007

Graph 1.18Consumer Confidence Index Performance

Optimis

Pesimis

Index150.0

125.0

100.0

75.0

50.0

25.0

2005 2006 20072 3 4 5 6 7 8 9 1011121 2 3 4 5 6 7 8 9 1011121 2 3 4 5 6 7 8 9 1011121

Index of Current Economic Conditions

Index of Consumer ExpectationsIndex of Consumer Confidence

Source: BI

15


purchasing power as well as seasonal factors such as

religious holidays and New Year festivities during the

second semester of 2007.

Meanwhile, on the supply side, in accordance with

favorable macroeconomic conditions the financial

performance of the corporate sector in 2007, in particular

public listed non-financial companies, improved relatively

compared to previous years. This was indicated by an

increase in ROA and ROE as well as lower leverage.

However, improved corporate sector performance

has, so far, failed to yield adequate business expansion. In

fact before the corporate sector improved, it was beset

with volatility in the financial market, for example

stemming from the subprime mortgage turmoil, as well

as soaring oil and basic commodity prices. Such volatility

has the potential to impede corporate sector performance

Graph 1.19Consumption Credit

Source: BI

2004 2005 2006

Trillions of Rp %

NPL (left axis)

Loans (left axis)

Growth (right axis)

0

50

100

150

200

250

0

5

10

15

20

25

300 30

Outstanding

Graph 1.20Growth of ROA and ROE

Graph 1.21Debt-to-Equity Ratio

-100

0

100

200

300

400

500

600

-100

-50

0

50

100

150

200

250

300

350

2003 2004 2005 2006 2007Q 1 Q 2 Q 3 Q 4 Q 1 Q 2 Q 3 Q 4 Q 1 Q 2 Q 3 Q 4 Q 1 Q 2 Q 3 Q 4 Q 1 Q 2 Q 3

ROE (right axis)ROA (left axis)

Source: BEI

0.00

0.20

0.40

0.60

0.80

1.00

1.20

2005 2006 2007

Q 1 Q 2 Q 3 Q 4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

Source: BEI

in the future. In line with this, the estimated probability

of default (PD) for non financial public listed companies

indicates that the number of companies with a PD above

0.5 is expected to rise from 21 at the end of December

2007 to 22 by the end of June 2008. This indicates a

0.0-0.1 0.1-0.2 0.2-0.3 0.3-0.4 0.4-0.5 0.5-0.6 0.6-0.7 0.7-0.8 0.8-0.9 0.9-1.0

181

2 1 0 0 2 0 0 019

Distribusi Forecast Probability of Default June 2008

Graph 1.22Non Financial Public Listed Companies Probability of

Default (December 2007)

0.0-0.1 0.1-0.2 0.2-0.3 0.3-0.4 0.4-0.5 0.5-0.6 0.6-0.7 0.7-0.8 0.8-0.9 0.9-1.0

178

3 0 0 2 0 0 0 022

Distribusi Forecast Probability of Default December 2007


Default (June 2008)

16


potential decline in corporate sector performance which

will raise credit risk in the real sector in the future. The

sectors projected to experience a rise on PD include the

trade, service and investment sectors, as well as

miscellaneous industry.

In addition to a potential rise on credit risk, companies

in the real sector will also be exposed to exchange rate

risk. The results of stress tests on 47 large companies and

conglomerates in Indonesia showed that conglomerate

performance should remain relatively solid even if the

rupiah depreciates to Rp9,500/USD. However, should the

rupiah weaken to Rp14,000/USD, this has the potential

to disrupt one conglomerate; reducing its capital by 100%.

Although, in general, the conglomerates appear sufficiently

resilient to exchange rate volatility, due to recent global

and domestic economic developments, however, it is critical

to prudently remember that numerous conglomerates

currently have a ratio of net foreign exchange liabilities to

capital above 25%.

Graph 1.25Net Foreign Exchange Liabilities to Capital Ratio

Net Foreign Exchange Liabilitiesto Capital Ratio > 25%

%

(50)

(25)

0

25

50

75

100

125

150

175

200

A C E G I K M O Q S U W Y AA AC AE AG AI AK AM AO AQ

Agri Mining Bsc Idty& Che

Misc Idty Cnsmr Gds Property Infrstrctr Trade,Invstmt

Dec-07 Jun-08

0.00.0

10.010.0

9.89.8 12.1

12.1

9.49.4

6.96.9

7.17.1

16.2

18.9

%


Default (December 2007 and June 2008)

Meanwhile, despite the investment components of

Gross Domestic Product (GDP) structure indicating growth,

such growth was in fact limited. The expansion primarily

originated from the non-traded sector (transportation,

communications, electricity, gas and water, as well as

services and finance). On the other hand, the

manufacturing industrial sector, which was expected to

10% 0 1 6 6 8 7 8 8 7 6 3 0 0 0

20% 0 0 1 6 1 5 6 5 3 3 5 0 0 0

30% 0 0 0 1 5 4 0 2 5 4 2 0 0 0

40% 0 0 0 0 1 2 5 1 0 2 5 1 0 0

50% 0 0 0 0 0 1 1 4 1 0 0 2 0 0

60% 0 0 0 0 0 0 1 1 4 2 1 2 0 0

70% 0 0 0 0 0 0 0 1 1 3 3 3 2 0

80% 0 0 0 0 0 0 0 0 1 1 1 0 0 0

90% 0 0 0 0 0 0 0 0 0 1 1 0 0 0

100% 0 0 0 0 0 0 0 0 0 0 1 14 20 22

00000 11111 77777 1313131313 1515151515 1919191919 2121212121 2222222222 2222222222 2222222222 2222222222 2222222222 2222222222 2222222222

PenguranganEquity

Rupiah Exchange Rate (IDR/USD)45,000

9,000 9,500 10,000 10,500 11,000 11,500 12,000 12,500 13,000 13,500 14,000 25,000 35,000

Table 1.4Impacts of Exchange Rate to Conglomeration Equity

Jmlh KonglomerasiJmlh KonglomerasiJmlh KonglomerasiJmlh KonglomerasiJmlh Konglomerasibermasalahbermasalahbermasalahbermasalahbermasalah

17


be the main driver of economic growth due to its large

multiplier effect on other economic sectors, did not grow

as hoped: just 4.9%. These are not dissimilar conditions

to the previous semester.

Agriculture; Industrial; Construction; Transportation

and Communications; Services; Mining and Excavation;

Utilities (electricity, gas and clean water); Trade, Hotels and

Restaurants; Finance, Rental and Services.

In general, limited investment growth was due to

the constraints still challenging corporate sector expansion,

particularly infrastructure and employment. Considering

the prolonged resolution of these issues, there has been

no significant improvement in Indonesia»s investment

competitiveness. According to the World Economic Forum

East Asia (June 2007), the average rating of Indonesia»s

investment competitiveness among ASEAN countries is just

above Vietnam and the Philippines.

Graph 1.26Sectoral GDP Growth

(Growth, yoy)

2005 2006 2007

AgribusinessManufacturingConstructionTransportationDan CommunicationServices

Mining & QuarryingElectricity, Gas and WaterTrading, Hotel,and RestaurantFinancial, Rent,and Services

Source: BI

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

Amid higher business risk pressure, the corporate

sector tends to conduct business by utilizing internal funds

rather than external fund sources such as bank loans. In

spite of the declining interest rate trend, credit extended

by banks has not yet been optimally exploited. This also

elucidates why credit extension by banks, particularly

investment credit, remains below potential. The tendency

of corporations to finance using internal resources is clearly

evidenced by the relatively high ratio of own capital to

total assets in listed companies.

Table 1.5Competitiveness Rating √ World Economic Forum

Indonesia 54 54

Malaysia 21 19

Vietnam 68 64

Thailand 28 28

China 34 35

Philippines 71 75

Singapore 7 8

GCI 2007- 2008 GCI 2006-2007(of 131 countries) (of 122 countries)

Country

Graph 1.27Financing of Public Listed Companies and their Expansion

(Asset Growth)

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Growth of Assets (left axis)Self Financing (right axis)

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Source: BEI

On one hand, the tendency to finance using internal

funds reflects the improved financial condition of the

corporate sector as they are not dependent on bank credit.

However, on the other hand, such a tendency has the

potential to restrict companies from fully expanding their

businesses due to limited internal funds. If this remains

Graph 1.28Unemployment Rate in Indonesia

%

2001 2002 2003 2004 2005 Feb-06 Aug-06 Feb-07 Aug-07

Source: BPS

0

2

4

6

8

10

12

18


Graph 1.29Growth of DER and TL/TA

2005 2006 2007

0.00

0.20

0.40

0.60

0.80

1.00

1.20

0.00

0.20

0.40

0.60

0.80

1.00

1.20

Debt Equity Ratio

Total Liabilities/Total Assets

Q 1 Q 2 Q 3 Q 4 Q 1 Q 2 Q 3 Q 4 Q 1 Q 2 Q 3 Q 4

Source: BEI

the status quo, new employment opportunities will be

limited which will undermine efforts to reduce the relatively

high unemployment rate.

Meanwhile, capital inflows -generally in the form of

financial assets- have not fully financed the real sector,

particularly the investment sector. Amidst the surging

capital inflows to Indonesia, the debt-to-equity ratio of

public listed non financial companies has tended to

decrease. This suggests that the capital inflows have not

been absorbed by the corporate sector, in particular public

listed companies.

In the future, arduous developmental challenges are

expected to remain in the real sector associated with

potential inflationary pressure and the knock-on effects

of the global economic slowdown. In order to stimulate

robust, sustainable economic growth, support from various

stakeholders is required to overcome the constraints faced

in the real sector. In this context, the role of the Micro,

Small and Medium Sector, which has long proved its

resilience in crisis conditions, should be prioritized in the

economy. Thus, improvements in macroeconomic

conditions will essentially be followed by progress in the

real sector. Furthermore, as consequence, this will

strengthen the resilience of the economy and domestic

financial sector towards external shocks.

19


Macroeconomic Stress TestBox 1.1

To assess the impact of macroeconomic conditions

on bank credit risk, a macroeconomic stress test was

applied using a fixed-effect panel data model. The

model developed is a linear regression model based on

the General Unrestricted Model as follows:

Where:

Yit : credit risk (LLP/TL and NPL/TL)

Xit : macroeconomic variables (GDP, Petrol Price,

Diesel Price, M1, M2, JCI, INF, EXRATE)

ai : individual effect of each bank

eit : residual, where et~N(0, σ 2)

t : time period

LLP = Loan Loss Provisions

M1 = Narrow Money

NPL = Non-performing Loans

M2 = Broad Money

TL = Total Loans

JCI = Jakarta Composite Index

GDP = Gross Domestic Product

INF = Inflation

XRATE = Exchange Rate

By using data for 15 major commercial banks

in Indonesia from December 1995 to May 2005, the

results indicated that changes in credit risk,

particularly the LLP/TL variable, were significantly

influenced by changes in macroeconomic indicators

such as M2 and inflation. This implies that, in general,

shocks stemming from macroeconomic factors

intensified the credit risk of banks. Consequently,

each development in the macroeconomic

environment, either domestic or international, must

be thoroughly observed and anticipated by

stakeholders in the financial sector. Failure to monitor

or anticipate macroeconomic developments could

endanger the banking industry and the financial

system in general.

Yit =αi + δt+Σk

j = 1

γi Yit - j +Σn

m = 0

βi Xit - m + εit

20


Potential Pressure from Foreign DebtBox 1.2

One important aspect that requires close

consideration in relation to macroeconomic

performance is the potential pressure stemming from

foreign debt. Up to December 2007, Indonesia»s foreign

debt totaled US$136.6 billion, dominated by the

Government (51.0%) followed by the Private sector

and others (49%).

However, additional caution is required due to

several signs of increasing potential pressure

emanating from foreign debt. First, the value of

foreign debt has increased. Compared to the position

in 2006, foreign debt grew by 7%. An increase was

also apparent in short-tenure foreign debt; from

US$16.5 billion to US$23.1 billion or up 40.2%. As

a consequence, the short-tenure foreign debt ratio

to foreign exchange reserves also increased; from

38.7% (end of 2006) to 40.6% (end of 2007).

Furthermore, the growth in foreign exchange

reserves falls short of the increase in short-tenure

foreign debt.

It is critical to monitor such developments in

foreign debt considering the impacts on financial

sector resilience as foreign debt or inflows of foreign

capital are principally invested in SBI and government

bonds (SUN), and tending to increase. By the end of

2007, SBI and SUN ownership by foreign investors

totaled US$11.3 billion; up US$3.2 billion (39.3%)

over the previous year. Pressures on financial sector

resilience may emerge should the foreign capital

invested in domestic securities experience a sudden

reversal. In addition, pressures may also appear due

to the relatively large value of foreign debt in the

payment plan. For 2008, the payment plan amounts

Graph Box 1.2.1Foreign Debt

Millions of USD

-

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

2000 2001 2002 2003 2004 2005 2006 2007

GovernmentPrivateOthers

In general, Indonesia»s foreign debt appears

sustainable. This is evidenced by indicators such as the

external debt to GDP ratio, external debt to exports

ratio and debt service ratio (DSR). These three ratios in

2007 were below the benchmark values set by the

World Bank and consequently can be declared as

sufficiently safe.

Graph Box 1.2.2Debt Burden Indicators of Indonesia

%200

180

160

140

120

100

80

60

40

20

0

%300

250

200

150

100

50

01997 1998 1999 2005 2006 2007

ED / EXPORT (RHS)ED / GDP (RHS)DSR (LHS)ST ED / RESERVE (LHS)

Graph Box 1.2.3Indonesia ULN Payment Plan

Source : Dint/PPLN2008

Millions of USD

0

400

800

1,200

1,600

2,000

2,400

2,800

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

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

Government (lhs) Private (lhs) Total (rhs)

Millions of USD

21


to US$23.7 billion, consisting of Government foreign

debt payments to the tune of US$9.1billion (38.3%)

and Private foreign debt payments totaling US$14.6

billion (61.7%). Therefore, the Government and

Private sector will have to manage their foreign debts

and ensure their timely repayment to avoid any

potential reputational risk and prevent a rise in the

international perception of Indonesia»s country risk.

22


Halaman ini sengaja dikosongkan

23

Chapter 2 Financial Sector

Chapter 2Financial Sector

24



25


2.1. STRUCTURE OF THE INDONESIAN FINANCIAL

SYSTEM

The structure of the Indonesian financial system has

not significantly changed since the previous edition of the

Financial Stability Review (FSR No. 9). The financial system

still constitutes commercial banks, rural banks and the non-

bank financial industry which includes insurance, pension

funds, finance institutions, securities and pawn brokers.

Data indicates that banks continue to dominate the sector

but with a shrinking share; amounting to 79% of total

assets of the financial system as a whole. Additionally, the

banking industry is still dominated by 15 major banks with

a share of around 70% of total bank assets.

In addition to banks, finance companies have also

witnessed a declining share. Meanwhile, the share of

securities companies has increased significantly, followed

In the second semester of 2007, Indonesian financial sector stability was

well maintained. The banking industry, which continued to dominate the

financial sector, performed favorably with high credit growth. However, the

need for more productive loans remains. Credit quality improved, as reflected

by the gross NPL ratio dipping below 5% in December 2007 for the first

time since the crisis. Banks remained liquid and controlled market risk as

well as maintaining sufficient capital and their profitability. Non-bank financial

institutions and the capital market also expanded amid mounting pressure

stemming from the global market.

Financial SectorChapter 2

by insurance companies. As an aggregate, total funds

managed by the financial sector amount to 64% of

Indonesia»s GDP.2

2.2. BANKS

2.2.1. Funding and Liquidity Risk

Deposits

Deposits, as the banks» primary source of funds

continued to increase during the second semester of 2007.

By year end, total deposits held by the banking industry

reached Rp1,510.7 trillion, representing a rise of Rp157.0

trillion (11.60%) in one semester. However, this was not

marked by the preference of investors to invest in foreign

currency as was common during the previous semester.

2 Nominal price GDP

26


During the reporting semester, rupiah deposits grew by

13.62%, whereas deposits in foreign currency only

increased by 1.36%.

towards more profitable alternative investments, such as

mutual funds, as the return on term deposits fell.

Consequently, during the second semester of 2007 the

net asset value (NAV) of mutual funds grew rapidly by

36.4%.

Liquidity Adequacy

Bank liquidity was relatively well managed during

the second semester of 2007. Banks maintained sufficient

liquidity, reflected by the high ratio of liquid assets3 to

non-core deposits (NCD)4 . Higher growth of liquid assets

compared to short-term liabilities raised the reported liquid

asset ratio from 138.9% in the previous semester to

147.7% by the end of the reporting semester.

Term deposits continued to command the largest

share of total deposits, however, growth of demand

deposits and savings accounts outpaced that of term

deposits during the second semester of 2007. Demand

deposits and savings accounts grew by 9.25% and 23.69%

respectively, yet term deposits grew by 6.15%. This is in

line with the banks» strategy to generate cheaper fund

sources due to cost efficiency. High growth in savings

accounts throughout the reporting period was accredited

to the numerous innovations made in savings products,

such as debit cards and termed savings products with

higher interest rates.

Meanwhile, slower growth in term deposits was in

line with the lower interest rate offered on term deposits

following reductions in the BI Rate. Customers tended

3 Liquid assets include cash and placements at BI (BI demand deposits, SBI and Fasbi)4 Assumption for non-core deposits (NCD) is 30% demand deposits and savings + 10%

termed deposits up to 3 months.

Graph 2.1Financial Institutions» Assets

2005

Share of Total Assets of Financial Institution

2006

Source: BI and others

Commercial Banks Rural BanksInsurance Companies Pension FundsFinance Companies Securities CompaniesPawn Brokers

81.5%

1.1%7.3%

3.5%5.3%

0.3%

1.0%

79.0%

1.1%

8.2%3.2% 4.6% 3.7% 0.3%

Graph 2.3Growth in Deposits by Component (m-t-m)

Demand Deposits

Deposits

-3

0

3

6

9

12

2006 June 2007 2007

Semester IISemester I

Savings Deposits

%

Graph 2.2Growth in Deposits by Currency (m-t-m)

%

Rp Deposits

Foreign Exchange Deposits

Semester I

Semester II

-6

-3

0

3

6

9

2006 June 2007 2007

27


Inter-Bank Money Market (PUAB)

In the second semester of 2007, PUAB remained

stable despite some interest rate fluctuations. It was noted

that the highest overnight (O/N) PUAB interest rate was

21% in the second week of September due to a

concomitant liquidity contraction, principally emanating

from the settlement of Indonesian Retail Bonds (IRB) and

tax payments. Nevertheless, conditions were adequately

managed, for instance through the Repo SBI facility, and

no volatility appeared.

Meanwhile, the lowest PUAB interest rate was less

than 1% in mid October. This was partially due to below-

normal financial transaction activity after the religious

holiday of Idul Fitri, indicated by a PUAB transaction volume

of just 70% compared to the previous week. In addition,

the Fasbi window was closed during the religious holiday,

which prevented the liquidity supply from Fasbi and SBI

being reabsorbed and, therefore, added the market

liquidity.

2.2.2 Credit Growth and Credit Risk

Credit Growth

Improving economic conditions, in particular the low

interest rate supported by policies to stimulate

intermediation in 2007, indicated very satisfactory results

in the reporting period. During the second semester of

2007, bank loans significantly increased (Rp141.5 trillion

or 15.7%) over the previous period (Rp 71.1 trillion or

8.5%), with total credit growth reaching 25.5%; exceeding

the target of 22%.

In general, banks tended to focus on extending less

risky credit, however, the riskier credit, for example to the

industrial sector and foreign currency denominated credit,

also witnessed quite significant growth. Nonetheless, this

credit growth was more selective compared to the pre-

crisis era, mainly due to better risk management applied

Placements of liquid assets in liquid and low-risk

instruments such as SBI (Bank Indonesia Certificates) and

Fasbi (Bank Indonesia Deposit Facility) increased. By the

end of the second semester of 2007, bank placements

in SBI and Fasbi reached Rp250.70 trillion, representing

a rise of 11.86% in 6 months. With the relatively high

return and low risk, liquidity placements in SBI and Fasbi

are advantageous and beneficial for l iquidity

management because deposits, as banks» primary source

of funds, remain concentrated on short-term funds that

are vulnerable to sudden withdrawal. By the end of the

reporting semester, short-term funds accounted for

93.3% of deposits. This percentage will continue to rise

if banks persist with their strategy to generate cheap fund

sources.

Graph 2.5Average Interest Rate of O/N Inter-Bank Money Market

%

Afternoon

Domestic

Morning

Foreign

0

4

8

12

16

Jan'07 Mar'07 May'07 July'07 Sep'07 Nov'07

Graph 2.4Liquid Asset Ratio of Banks

Liquid Assets NCD Liquid Assets/NCD

Trillions of Rp

0

80

160

240

320

400

480

Dec'06 Jun '07 Sept'07 Dec '0760

120

180

%

28


by banks. The preference to extend credit with more

controlled risk was indicated by higher growth in working

capital and consumption credits compared to investment

credit, and the tendency of extending credit to existing

borrowers rather than to new borrowers. Accordingly, the

share of credit in bank assets grew.

Meanwhile, the low interest rate did not discourage

the public from depositing their funds at banks, which

was evidenced by the surge in bank deposits totaling

Rp157.0 trillion (11.6%). The surge in deposits did not

exceed loan growth during the second semester of 2007,

therefore, the loan-to-deposit ratio (LDR) by the end of

December 2007 reached 69.2%; surpassing the ratio at

the end of June 2007, namely 66.8%.

Rp590/USD. Loans extended in foreign currency grew

significantly by 21.8%; making up 27% of the total rise in

bank loans during the reporting period. Nevertheless, the

share of foreign currency denominated loans in total bank

credit was relatively stable at around 20% (21.0% at the

end of December 2007). In terms of risk, the growth in

foreign currency loans has not so far created any problems

as the share remains relatively small.

Graph 2.6Credit Growth

Graph 2.7Composition of Productive Assets

0%

20%

40%

60%

80%

100%

Jun-07 Dec-07

LoansBISecuritiesABA

55.1%

13.7%

20.8%

10.1%

58.4%

14.0%

19.5%

7.8%

Graph 2.8Foreign Currency Loans

Trillions of Rp

100.0

120.0

140.0

160.0

180.0

200.0

220.0

2005 June 2006 June 2007 June Dec

Nominal (left axis)YOYYTD

-10.0

-5.0

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

%

Compared to other types of loans, Working Capital

Credit (WCC) recorded the largest rise in value and highest

growth in the second semester of 2007. Working capital

credit accounted for 62.5% of the total rise in credit during

the reporting semester, growing by 28.6% (y-o-y). That

increase was followed by Consumption Credit (CC) which

represented 23.6% of the total increase in credit, growing

by 24.6% (y-o-y).

Graph 2.9Growth by Loan Type

line = YOYbar = YTD

-10.0

-5.0

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

2006 Jun 2007 Jun Dec

Working CapitalLoan

InvestmentLoan

ConsumerLoan

-5.0

0.0

5.0

10.0

15.0

20.0

25.0

30.0

2006 June 2007 June Dec

%

Bank loans denominated in foreign currency

increased along with the expansion in import and export

activities as well as rupiah depreciation against the USD to

29


which in the reporting period reached Rp60.0 trillion

(22.5% y-o-y). This increase means that credit to the MSM

sector represented 40.7% of the total increase in bank

loans during the reporting period and reached 50.2% of

total bank credit.

It is projected that in the first semester of 2008, credit

growth will slow down compared to the reporting period

but still exceed that of the first semester of 2007. This is

due to sufficiently large undisbursed loans until the end

of 2007. During the reporting period undisbursed bank

loans (UL) rose by Rp32.7 trillion or 18.6%. By the end of

December 2007, UL totaled Rp208.3 trillion or as a

percentage 20.7% of total bank loans. This has remained

relatively stable since the crisis within the range of 20%-

21%.

Credit share is still dominated by WCC (53.5% of

total bank loans), followed by CC with a share of 28.2%,

and finally investment credit. As mentioned previously, the

dominant shares of WCC and CC indicate the banks»

preference to extend credit with more controlled risk. WCC

is generally a short-term, relatively high-value loan

extended to borrowers already known to the banking

industry, whereas CC generally covers lower value loans

to households as the majority borrowers. Banks opted to

concentrate on WCC and CC to mitigate the mismatch of

fund resources dominated in the short-term. However, to

support higher economic growth in the future, the

proportion of productive loans (for investment and working

capital) should be expanded.

Graph 2.10Credit Allocation by Economic Sector

Trillions of Rp

120.0

140.0

160.0

180.0

200.0

220.0

240.0

260.0

280.0

300.0


OthersIndustrialTradeCombined

The preference for controlled risk is also evidenced

by credit allocation based on economic sector. The trade

sector, which generally demands working capital credit,

grew the most reaching 24.6% of the total increase in

bank loans during the reporting period; a rise of 32.7% y-

o-y. This was followed by the Others Sector, which generally

applies for consumption credit, with growth accounting

for 23.4% of the total rise in credit (24.7% y-o-y). The

share of the Trade Sector reached 21.6%, surpassing the

Industrial Sector with 20.5%. The preference for loans with

more controlled risk is also indicated by growth in credit

extended to micro, small and medium segment (MSM),

Graph 2.11Undisbursed Loans

Trillions of Rp

140

150

160

170

180

190

200

210

220

UL (left axis)Credit

2006 Jun 2007 Jun Dec700

750

800

850

900

950

1000

1050

Trillions of Rp

Credit Risk

Improved macroeconomic conditions acutely

supported the bank loan restructuring process, thus for

the first time since the crisis, the gross ratio of NPL was

below 5%. This is also in line with a more effective risk

management by banks and as a result of various policies

instituted by Bank Indonesia and the government, which

are conducive to improve the quality of bank credit. Non-

performing loans decreased the most in the major state-

owned banks, hence risk pressure on the financial system

also dissipated.

30


During the second semester of 2007, total non-

performing loans decreased by Rp9.0 trillion, which

represents a 15.5% decline compared to the Rp0.6 trillion

drop (1.0%) in the previous period. Therefore, nominal

NPL has now lowered to Rp48.6 trillion. The three types

of credit that make up NPL (sub-standard (SS), doubtful

(D) and loss (L)) decreased by 30.2%, 34.5% and 10.3%

respectively. Meanwhile, loans placed ≈Special Mention∆

also declined nominally by 6.6% compared to late June

2007. The quality of credit has improved in line with the

increasing total loans by Rp141.7 trillion or 15.7% during

the reporting semester, therefore, the gross NPL ratio

declined from 6.4% to 4.6%. On the other hand, the

reduction in nominal NPL lowered the loan loss provisions

by Rp2.1 trillion or 4.8%. After calculating the loss

provisions Net NPL decreased from 2.9% to 1.9%; the

lowest since the crisis.

The lower quantity of non-performing loans in the

major banks group dispersed pressure on financial system

stability. During the second semester of 2007, nominal

NPL for major banks significantly fell (Rp8.5 trillion or

18.5%) and was followed by a noteworthy increase in

credit allocation. As a consequence, gross NPL of this group

declined from 7.4% to 5.2%. The decrease in NPL of the

major banks was principally attributable to restructuring

and write-offs by state-owned banks. However, non-

performing loans increased for the group of foreign bank

branches to the tune of Rp0.5 trillion or 14.3%. Therefore,

gross NPL of this group equaled the gross NPL of the major

banks group for the first time, namely 5.2%.

Graph 2.12Non-Performing Loans

% Trillions of Rp

NPL Gross

NPL Nominal NPL Net

-

1

2

3

4

5

6

7

8

9

10

11

2003 2004 2005 2006 2007 Dec25

30

35

40

45

50

55

60

65

70

75

Graph 2.13NPL Nominal

Trillions of Rp

Sub-standard (left)

Loss (right)Doubtful (left)

Total NPL

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

22.0

30.0

35.0

40.0

45.0

50.0

55.0

60.0

65.0

70.0

75.0


Trillions of Rp

Graph 2.15Gross NPL by Bank Group

Graph 2.14Nominal NPL by Bank Group

Billions of Rp

-10000 -8000 -6000 -4000 -2000 0 2000

Large Banks

Medium Banks

Small Banks

Mixed

Foreign

%

0.0

3.0

6.0

9.0

4.0

7.4

4.0

3.1 3.0

5.15.2

3.2

2.21.8

5.2

3.63.33.8

8.4Dec-06Jun-07Dec-07

Large Medium Small Mixed Foreign

The two economic sectors with the largest nominal

NPL, namely the manufacturing sector and trade sector,

showed favorable improvements in loan quality. Improving

macroeconomic conditions during the reporting semester

31


coupled with a BI-Rate decline of 50 bps raised borrower

outlook during the restructuring process. Nominal NPL in

the manufacturing sector went down significantly by Rp4.0

trillion or 21.7%, therefore, the gross NPL ratio declined

from 10.0% to 7.10%. However, recent data showed that

the manufacturing sector continues to dominate NPL share,

accounting for 35.3% of total bank NPL. Thus, credit

extension to this sector should be tightly monitored so

that its quality can be assured to avoid disrupting financial

sector stability. Meanwhile, credit quality in the trade sector,

which has the second largest share of nominal NPL, also

picked up. Nominal NPL in the trade sector declined by

Rp2.2 trillion or 19.6%, therefore, the gross NPL ratio fell

from 6.1% to 4.1%.

Graph 2.16Nominal NPL by Economic Sector

Trillions of Rp

-5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0

Agriculture

Mining

Industrial

Electric

Construction

Trade

Transportation

Business Services

Social Services

Others

Graph 2.17NPL Share by Economic Sector

the manufacturing sector and trade sector indirectly raised

the quality of WCC, which constitutes the largest share of

NPL in total bank NPL. Nominally, NPL of WCC dropped

by Rp6.1 trillion or 23.3%, therefore, the gross NPL ratio

declined from 5.8% to 3.7%. In accordance with such an

improvement, the NPL share of WCC in total bank NPL

also went down from 52.1% to 48.8%. Meanwhile,

nominal NPL IC decreased by Rp2.9 trillion or 19.1%. As a

Other manufacturings = Mining, Electricity, Services, Construction, Transportation

0

20

40

60

80

100

2000 2001 2002 2003 2004 2005 2006 2007 Dec

Agribusiness

Industry

Trading

Others Sectors

Business Services

%

It is worth noting that during the reporting semester,

of all economic sectors only credit extended to the mining

sector experienced a modest decline in quality, whereas

the other nine sectors showed improvement. In terms of

financial system stability and the bank intermediation

function, conditions were conducive. Towards the future,

such improvements should be prolonged while

simultaneously improving the quality of credit extended

to the mining sector.

In terms of credit type, the quality of Working Capital

Credit (WCC) and Investment Credit (IC) improved

significantly. The aforementioned rise in credit quality to

Graph 2.18NPL by Loan Type

Trillions of Rp

-7.0 -6.0 -5.0 -4.0 -3.0 -2.0 -1.0 0.0

Working Capital

Investment

Consumer

Graph 2.19NPL Share based on Loan Type

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2002 2003 2004 2005 2006 2007 Dec

Working Capital Investment Consumption

32


loans, personal and uncollateralized loans). From these

three components of consumption credit, by the end of

the second semester of 2007, the highest gross NPL ratio

was for credit cards, totaling 12.0%, whereas the gross

NPL ratios for housing loans and others were 3.02% and

1.90% respectively. The high gross NPL ratio for credit cards

was, among others, due to taxation constraints concerning

credit write-offs. However, in general banks maintained

sufficient provisions; therefore, the net NPL ratio for credit

cards was actually relatively low.

result, the gross NPL ratio is lowered from 9.1% to 6.6%.

Against this encouraging backdrop, the IC share of nominal

NPL was noted to reach 30.0% of total bank NPL by the

end of semester II 2007.

As the NPL shares of WCC and IC in total bank NPL

are relatively large, tight monitoring is prerequisite to

maintain credit quality in order to avoid undermining bank

resilience. Strict monitoring is also important because credit

such as IC commonly targets corporate borrowers over a

long tenor and with a relatively full range of facilities.

Furthermore, IC is often denominated in foreign currency;

therefore, borrowers are exposed to exchange rate risk

which can raise the potential of default.

Graph 2.21Gross NPL Ratio for Consumption Credit

Graph 2.20Gross NPL Performance

Investment (left axis)

Working Capital (left axis)

Consumer (right axis)

2.0

7.0

12.0

17.0

22.0

2002 2003 2004 2005 2006 2007 Dec1.5

2.0

2.5

3.0

3.5

4.0% %

The final type of credit is consumption credit (CC).

During the reporting period, the quality of this credit

improved slightly, denoted by a declining nominal NPL by

Rp0.01 trillion or 0.1%, therefore, the gross NPL ratio of

CC went down from 3.5% to 3.1%. The nugatory

improvement in credit quality clearly evidences the plight

of the household sector, for which economic conditions

are yet to become favorable, particularly in terms of

income. Conversely, this could also be interpreted as

households» inability to manage their incomes

appropriately.

In general, there are three components of

consumption credit that must be analyzed, including credit

cards, housing loans and others (such as motor vehicle

The quality of credit for the Micro, Small and Medium

segment (MSM) also improved, indicated by the decline in

nominal NPL by Rp2.0 trillion or 10.0%. Consequently,

gross NPL went down from 4.8% to 3.5%. This

improvement in credit quality was supported by conducive

economic conditions and various policies promulgated by

the government and Bank Indonesia directed at MSM

business expansion. This type of loan is not expected to

heap pressure on financial system stability in the short term

as it is typically diversified with a relatively small credit

ceiling and a large number of borrowers. Furthermore, it

is also concentrated on consumption.

Improvements were also witnessed in non-MSM

credit, for which borrowers are predominantly provided

with a loan facility of above Rp5 billion. During the second

semester of 2007, nominal NPL for non-MSM credit fell

0

3

5

8

10

13

15

2002 2003 2004 2005 2006 2007 Dec

KPRCredit CardOthers

%

33


by Rp7 trillion or 23.8%, therefore, the gross NPL ratio

went down from 7.3% to 4.6%. Even though the share

of non-MSM credit in total bank loans was only 48.9%

(less than the share of MSM credit), the decline in NPL of

the non-MSM segment is very satisfactory as non-MSM

borrowers are typically from the corporate sector with a

large amount of facilities, long tenure periods and often

in the form of foreign currency, which can disrupt the

financial system if the loans are not repaid. The crisis that

befell the Indonesian economy in 1997/1998 proved that

corporate borrowers are particularly vulnerable to financial

crisis.

loans. The success of the restructuring process reduced

foreign currency denominated nominal NPL by Rp2.1

trillion or 21.4%, therefore, gross NPL dropped from 7.9%

to 5.1%. Meanwhile, the nominal NPL of rupiah

denominated loans declined by Rp6.8 trillion or 16.9%,

reducing the gross NPL ratio from 5.3% to 3.8%.

Graph 2.22Nominal NPL of the Corporate and MSME Sectors

Graph 2.23Gross NPL of the Corporate and MSME Sectors

Corporation (left axis)

MSME (right axis)

-

5

10

15

20

25

30

35

40

45

50

0

5

10

15

20

25

2001 2004 `2005 2006 2007 Dec

Trillions of Rp Trillions of Rp

Corporation (left axis)

MSME (right axis)

4.0

5.0

6.0

7.0

8.0

9.0

10.0

11.0

12.0

13.0

2003 2004 `2005 2006 2007 Dec2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5% %

Despite rupiah depreciation, the performance of

foreign currency denominated loans improved, which

eased the risk pressure on banks. In reality, the majority of

corporate debtors that were restructured by state-owned

banks were borrowers of foreign currency denominated

Graph 2.24NPL of Foreign Currency and Rupiah Denominated Loans

% Billions of USD

2001 2002 2003 2004 2005 2006 2007 Dec0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

-

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

NPL Foreign Exchange (USD)NPL Gross (left axis)

Stress Test

In determining the resilience of the banking system

against fluctuating credit risk, a stress test was performed

to illustrate the effect of a rise in NPL against bank capital.

For this purpose, banks were categorized into three groups,

namely the group of 15 major banks, medium-sized banks

and small banks. Meanwhile, the rising NPL scenario is

supplemented with several alternatives and linked to the

NPL position as per the end of semester II 2007. The results

demonstrate that the banks would be able to overcome

shocks in the form of an NPL rise up to 25% above the

reported position. In particular for the group of 15 major

banks, average CAR would only drop by about 1% (lowest

0% and highest 5.5%) from 18.0% to 16.9%. The CAR

of medium and small banks would even tend to be

persistently higher than the CAR of the major bank group

for every scenario. A bank»s ability to address such a rise in

NPL is due to the high profit generated to cover the

additional allowance for credit loss provisions, as well as

strong capital.

34


revised the investment package to allay uncertainty in the

business community, which also indirectly alleviated credit

risk exposure to banks. In the context of credit

restructuring, the promulgation of Government Regulation

No. 33/2006 on Procedures for Writing Off State-Owned

Receivables, is also expected to assist credit risk mitigation,

particularly for state-owned banks.

Policies instituted by Bank Indonesia also paved the

way for banks to mitigate credit risk. Conducive monetary

policy will help banks prepare to improve credit quality as

well as enhance their intermediary function, in particular

for productive loans. Meanwhile, a range of banking

policies has been issued to encourage the implementation

of effective risk management. Additionally, the Credit

Information Bureau was established to help disseminate

credit information required by the business community in

order to reduce credit risk stemming from asymmetric

information.

2.2.3. Market Risk

More favorable macroeconomic conditions, which

enabled a BI Rate reduction, tended to curb banks» market

risk exposure. The managed reduction of the interest rate

that has persisted since 2007 continued into the second

semester despite a slowdown by year end. The average

interest rate of the 1-month term deposits fell by only 27

bps in the reporting semester, compared to a 150-bps

decline in the previous semester. Meanwhile, the interest

rates of working capital credit, investment credit and

consumption credit declined by 88 bps, 98 bps and 78

bps respectively.

Even though the magnitude of the interest rate

decline for consumption credit was outpaced by the other

lending rates, the decrease surpassed that of the previous

semester. The slow interest rate decline at year end was

associated with the sluggish decline in the BI Rate.

Risk Mitigation

Several efforts have been taken to ease bank credit

risk. Banks mitigate credit risk through the implementation

of risk management on all business lines; also by expanding

capacity with a risk management certification program.

Basel II implementation is also expected to strengthen the

future application of credit risk management. Another

important step taken by banks to mitigate credit risk is to

maintain adequate loan loss provisions. During the

reporting period, loss provisions were reduced by Rp2.1

trillion or 4.8% in line with the drop in nominal bank NPL.

Despite the reduction, the loss provisions remain sufficiently

conservative to anticipate potential losses.

Graph 2.26Credit, NPL and Loan Loss Provisions

Trillions of Rp

Nominal NPL (left axis)

APLL (left axis)

Loans (right axis)

30

40

50

60

70

80

90

100

2000 2001 2002 2003 2004 2005 2006 2007200

300

400

500

600

700

800

900

1000

1100

Credit risk mitigation is also well supported by

government policies, for example, the government

guarantee for Rural Community Loans. As a result, the

risks borne by banks are lower. In addition, the government

Graph 2.25Stress Test of NPL against CAR

NPL Increasing Scenario

15.0

17.5

20.0

22.5

15 Large Banks Middle Bank Small Bank

Start 1 2 3 4 5 7 10 15 20 25

%

35


However, in general, banks seemed more willing to lower

their lending rates. By the end of December 2007, the

interest rates for WCC and IC (13.00% and 13.01%

respectively) had reached their lowest levels since 2001.

Only the interest rate for CC remained relatively high at

16.13%. This primarily emanated from the joint-venture

banks group and the group of foreign bank branches,

which averaged over 30%.

previous year»s position, particularly for the foreign

exchange portfolio. The increasing trend of foreign

exchange portfolio should be monitored with caution,

particularly for the short-term portfolio with net short

position, even though the number is relatively small. Banks

are projected to overcome exchange rate volatility as they

are cushioned by relatively high capital, however, effective

risk management is also necessary.

Stress Test

With the prevailing conditions of the maturity profile,

potential interest rate risk will intensify should a swing in

the interest rate occur. The underdeveloped hedging and

derivative markets has forced banks to be more cautious

when confronting the possibility of an interest rate swing.

Stress test results indicate that a 1% increase in the interest

rate would lower CAR by an average of 34 bps.

Graph 2.27Interest Rate and Exchange Rate Performance

% Trillions of Rp

4

7

10

13

16

19

22

2002 2003 2004 2005 2006 20077500

8500

9500

10500

11500

1-month deposits(left axis)

Investment Loan(left axis)

Consumer Loans (left axis)

Exchange Rate(right axis)

Working CapitalLoans (left axis)

Graph 2.28Lending Rate by Bank Group

%

0

10

20

30

40

WC = Working CapitalI = InvestmentC = Consumer

Jun06 Dec06

Jun07 Dec07

WC I C WC I C WC I C WC I C WC I CState-Owned

BanksRegional Dev.

BanksDomestic Private

BanksForeign & JointVenture Banks

All Banks

With the prevailing decline in the interest rate during

the second semester of 2007, banks implemented interest

rate risk management by maintaining net short position

for short-term portfolio and net long position for long-

term portfolio. Consequently, banks could generate profit

when interest rates fell. This maturity profile composition

was evident for both rupiah and foreign exchange

portfolios with an increasing trend compared with the

Graph 2.30Foreign Exchange Maturity Profile

Billions of USD

(15)

(10)

(5)

0

5

10

Dec05 Jun06Dec06 Jun07Dec07

sd 1 month 1 - 3 months 3 - 6 months 6 - 12 months > 12 months

Graph 2.29Rupiah Maturity Profile

Trillions of Rp

(450)

(300)

(150)

0

150

300

450

Dec05 Jun06Dec06 Jun07Dec07

sd 1 month 1 - 3 months 3 - 6 months 6 - 12 months > 12 months

36


Fluctuations in the exchange rate by the end of the

second semester of 2007 did not trigger any instability as

banks maintained a relatively low Net Open Position (NOP)

(4.47%). However, this position increased quite

significantly compared to the position in the previous

semester of 3.92% due to the increase in the maturity

profile of short position for the short-term portfolio.

While the average NOP is far below the maximum

limit of 20%, any rising trend should be carefully monitored

by improving risk management and preparing an adequate

contingency plan. Based on stress test results concerning

the impact of rupiah appreciation/depreciation on capital

(CAR), it has been noted that banks can generally maintain

CAR above 8%.

In line with the declining interest rate trend, SUN

ownership by banks, particularly in the trading portfolio,

also witnessed growth. Ownership of trading portfolio by

banks rose by Rp12.5 trillion compared to the end of the

previous semester, expanding its share in total SUN

composition from 61.2% to 64.3%. Such conditions can

leave banks more exposed to market risk associated with

SUN prices. The expanding share of trading portfolio

composition has not been excessive; nevertheless attention

must be paid to recent volatility in the global financial

market.

Hitherto, the leading strategy employed by banks to

mitigate the market risks associated with SUN prices is by

maintaining a low proportion of SUN for trading purposes.

The strategy has, so far, been successful as it is also

reinforced by strong bank capital. Consequently, pressure

on capital will only be experienced if the SUN price drops

significantly. Results of stress tests indicate that the CAR

of banks would drop below 8% if the SUN price decreased

by 20% or more. In the future, besides relying on strong

capital, banks should continue to strengthen their risk

management.

2.2.4. Profitability and Capital

Profitability

The profitability of banks improved during the second

semester of 2007 compared to the previous semester.

Contrasted against the same position of the previous year,

the net interest income (NII) of banks during semester II

2007 rose to Rp50.0 trillion from Rp46.4 trillion in the

previous semester. This was due to a rise in interest income

from Rp87 trillion (during semester I 2007) to Rp89 trillion

(during semester II 2007), and a reduction in interest expense

from Rp40.6 trillion to Rp39 trillion. The rise in profitability

was in line with a higher increase in loans compared to

deposits, supported by higher quality loans and the tendency

of banks to move away from expensive funding sources.

Meanwhile, the return on assets (ROA) decreased

slightly from 2.81% to 2.78% as the rise in NII was offset

Graph 2.32SUN Ownership by Banks

Trading Government Bonds to Total Assets (right axis)Trading (left axis)Investment (left axis) Government Bonds to Total Assets (right axis)

0

25

50

75

100

Dec»05 Jun»06 Dec»06 Jun»07 Dec»075

9

13

17

21% %

Graph 2.31Growth of NOP (Overall)

16.9

14.7

16.915.3

17.419.2

0

4

8

12

16

20

24

Sep Dec Mar Jun Sep Dec2006 2007

%

Domestic Private Banks

Foreign Banks

Joint Venture Banks

All Banks

Regional Dev. Banks

The highest of NOP

State-Owned Banks

37


by an increase in assets. By differentiating banks into two

groups, a drop in ROA was only experienced by the «others»

bank group; from 3.26% to 2.98%. Conversely, the large

banks groups saw an increase in ROA from 2.62% to 2.69%.

Rate, income from BI Certificates fell from 11.8% to

10.2%.

Capital

The rise in total credit extended during the reporting

period increased the risk weighted assets of banks. The

increase in risk-weighted assets outpaced the growth in

capital which drove down the capital adequacy ratio (CAR)

from 20.7% to 19.3%. The drop in CAR was experienced

by all banks groups. The largest decline was borne by the

others bank group, more specifically from 23.8% to

22.1%, whereas the least significant decrease was for the

large banks group (19.3% to 18.0%).

Graph 2.33Bank NII

Trillions of Rp

-

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

Dec «03 Jun «04 Dec «04 Jun «05 Dec «05 Jun «06 Dec «06 Jun «07 Dec «07

Interest Income Interest Expenses NII

Graph 2.34ROA Ratio by Bank Group

0

0.5

1

1.5

2

2.5

3

3.5

4Jun'07 Dec'07

Dec'07

Large Bank Others Bank Industry

The share of interest income from loans continued

to expand along with greater credit extension, rising from

63.5% to 64.7%. Furthermore, the share of interest

income from securities increased slightly from 16.8% to

16.9%. Oppositely, in line with the reduction of the BI

Graph 2.35Komposisi Pendapatan Bunga Bank

OthersLoansSecuritiesBI

Dec «05 Jun «06 Dec «06 Jun «07 Dec «076.01 8.75 10.37 11.78 10.2

22.0 22.9 21.4 16.8 16.9

63.1 59.2 60.1 63.5 64.7

8.90 9.16 8.21 7.88 8.3

%

Graph 2.36CAR Ratio by Bank Group as of Semester II 2007

0

5

10

15

20

25%

Dec'07Jun'07

Large Bank Others Bank Industry

Despite the decline, the CAR of Indonesia»s banks

remains the highest in Asia. Bank capital mostly consists

of core capital (Tier I) with a ratio to risk-weighed assets

of 16.8% by the end of December 2007. A high core

Graph 2.37Core Capital Ratio to Risk Weighted Assets and CAR

0

5

10

15

20

25

30CAR

Tier 1 to Risk WeightedAssets Ratio

A B C D E F G H I J K L M N O

B a n k s

15 B

ig B

anks

Fore

ign

Bank

s

Join

t Ven

ture

Ban

ks

Othe

rs

All B

anks

38


capital ratio to risk-weighted assets indicates the solvability

of banks is sufficient to absorb business risks and to provide

more room for banks to expand credit.

It is important to note that even though aggregate

bank CAR is fairly high, there remain several medium and

small banks with marginal CAR (between 9% and 12%).

Such banks are particularly vulnerable to risk, especially if

they do not apply apposite risk management.

Whereas, full bank compliance to the minimum core

capital requirement for commercial banks of Rp80 billion

by the end of 2007 has been accomplished. Nevertheless,

as banks are further required to meet a minimum core

capital requirement of Rp100 billion by 2010, future

surveillance will emphasize the satisfactory fulfillment of

this requirement. By the end of December 2007, 20 banks

had a core capital of between Rp80 billion and Rp100

billion.

Stress Test

To observe the resilience of 15 large banks against

unfavorable economic conditions, integrated stress tests

were used covering a number of economic variables as

follows:

A rising interest rate against the net maturity profile

of bank assets and liabilities under 3 months. In this

case, banks with a long position or greater assets than

liabilities will reap positive benefits and vice versa;

A weakening exchange rate against the bank»s net

open position. In this case, a bank with a long position

is best suited to obtain benefits.

Furthermore, stress tests were supplemented with a

scenario incorporating lower SUN prices, below par in

terms of their specified percentage and rising bank NPL.

The impacts of such a scenario are first transmitted to the

profit and loss of the bank and then to the bank»s capital.

In addition to gauging market risk, this stress test

also measures credit risk using unfavorable credit conditions

in each category. The scenario assumes a 5% rise in the

NPL of standard credit, followed by 5% of sub-standard

credit becoming doubtful and then 5% of doubtful credit

becoming loss. Notwithstanding, the stress test was further

complemented using a scenario which assumes a 3% rise

in the interest rate that will affect the assets and liabilities

of the bank, especially with maturity below 3 months; a

Rp500 drop in the exchange rate against the net open

position and a decline in the value of SUN by 5% from

normal. The impacts of such a scenario on a bank»s capital

depend heavily on the condition of NPL, foreign exchange

assets and liabilities, sufficient loan loss provisions, the size

of the banks profit and loss as well as the bank»s capital.

Based on the scenario described above, the results

of the stress test on 15 large banks indicate that the CAR

of one bank would drop below the prevailing regulation.

On average the decline in CAR is 1.5%, namely from

Graph 2.38Map of Core Capital Performance

30

9

23

39

2925

9

25

41

30

9

2025

43

33

0

5

10

15

20

25

30

35

40

45

50

< 80 M 80 M - 100 M 100 M - 200 M 200 M -1 T > 1 T

Data SIMWAS, sebelum judgement pengawas

Dec'06Jun'07

Dec-07

Graph 2.39Integrated Stress Test

%30

25

20

15

10

5

0A B C D E F G H I J K L M N O

CAR AWALCAR BARU

39


risk due to the expectation of lower motor vehicle demand

as a result of the soaring global oil price. The high risk of

consumer financing is also evidenced by increasing

consumer financing NPL, climbing from 1.24% (December

2006) to 1.52% (October 2007).

The profitability of finance companies increased;

indicated by the 11% rise in profit before tax to Rp4.48

trillion, whereas in the previous year it fell by 13%.

However, ROE dropped to 19% (November 2007) from

21% (December 2006) principally due to less effective asset

management by national private finance companies.

18.0% to 16.5%. However, in general bank capital is

strong enough to overcome the various simultaneous

shocks tested in the model.

2.3. NON-BANK FINANCIAL INSTITUTIONS AND

THE CAPITAL MARKET

Up to the end of semester II 2007, non-bank financial

institutions and the capital market continued to grow amid

pressures stemming from global market shocks.

Meanwhile, increasing consumer financing NPL from

finance companies should be monitored to avoid any

additional pressure on bank resilience and the financial

system. Such surveillance is critical because despite a more

robust financial market, short-term volatility has increased.

2.3.1. Finance Companies

In 2007 (up to November 2007), the performance

of finance companies improved greatly, indicated by a 16%

increase in total assets to Rp126.4 trillion, which

outstripped performance in the previous year (13%).

However, financing tended to slow down considerably,

with just 15.52% growth compared to 37.65% in the

previous year.

The financing offered by finance companies,

particularly national private finance companies, remained

concentrated on consumer financing, primarily motor

vehicle loans. This type of loan has relatively high potential

Graph 2.40Operational Activities of Finance Companies

0

20

40

60

80

100

120

140Billions of Rp

200420052006

NovJun 07

Assets Financing Funding Capital

Graph 2.41Financing Activities of Finance Companies

%

Sewa GunaUsaha

AnjakPiutang

CreditCard

ConsumerFinancing

100

90

80

70

60

50

4030

20

10

0

0%Domestic Private Finance Companies 3% 87%

Total 2% 1% 63%

Joint Venture Finance Companies 1% 2% 50%10%

34%46%

Graph 2.42Performance of Finance Companies

Dec 05 Dec 06 Nov 07

Thousands

ROA PPROE PP

ROA SNROE SN

Pembiayaan TotalPembiayaan SNPembiayaan Ptgn

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0

20

40

60

80

100

120

The efficiency of joint-venture finance companies

improved, reflected by the decline in the ratio of operating

expense to operating income from around 90%

40


trillion. Moreover, one company used right issues and one

company issued bonds abroad.

The proclivity of finance companies towards

consumer financing, primarily to purchase motor vehicles,

combined with increasing consumer financing NPL and

compounded by high dependence on banks for their

source of funds intensified risk exposure to banks.

Meanwhile, Bank Indonesia Regulation (PBI) No.8/6/PBI/

2006 regarding the Implementation of Consolidated Risk

Management for Banks Controlling Subsidiaries could

potentially spur losses for finance companies affiliated with

banks due to higher provisions costs in line with higher

NPL for consumer financing. As finance company losses

will be further reflected on the consolidated balance sheets

of banks, early caution is required.

2.3.2. Capital Market

Foreign Investor Portfolio

Entering semester II 2007, pressure on financial

system stability tended to be more intense, due for the

most part to more aggressive foreign investor behavior

utilizing short-term profit taking. Such behavior triggered

corrections in the domestic capital market. During the

reporting semester, foreign investment in rupiah financial

instruments continued to grow by around Rp49 trillion,

which is very similar to growth in the previous semester.

Such growth has led to foreign investment in BI Certificates,

SUN and shares to increase by almost Rp98 trillion. The

composition of this investment is respectively Rp35 trillion

(BI Certificates), Rp29 trillion (SUN) and Rp33 trillion (net

purchases of shares).

The relatively high yield of rupiah investments

maintained foreign investor appetite for rupiah financial

instruments. However, portfolio behavioral changes by

foreign investors, who mainly consist of hedge fund

managers, have been apparent. Foreign investors more

(December 2006) to 76% (November 2007). This was

mainly due to broader access to funding sources, further

supported by more diversified financing.

Loans from domestic banks remained as the primary

source of funds for national private finance companies. In

2007, total loans grew by 30% to Rp13.47 trillion.

Meanwhile, total loans from domestic banks to finance

companies increased by 19% to Rp35.47 trillion,

predominantly extended to joint-venture finance

companies. In addition to loans from domestic banks, joint-

venture finance companies also utilized funds from foreign

loans, accounting for 52% of total loans (November 2007).

Graph 2.44Joint Finance Companies» Source of Funds

Graph 2.43National Private Finance Companies» Source of Funds

Thousands

Domestic Bank LoansForeign Loans

Securities

0

2

4

6

8

10

12

14

16

Dec 05 Dec 06 Jun 07 Jul 07 Aug 07 Sep 07 Oct 07 Nov 07

Thousands

Domestic Bank Loans

Foreign Loans

Dec 05 Dec 06 Jun 07 Jul 07 Aug 07 Sep 07 Oct 07 Nov 07

Securities

0

5

10

15

20

25

30

35

In 2007, finance companies actively accumulated

funds through bonds issuances, therefore the ratio of

finance companies» borrowings to equity decreased from

3.98 (December 2006) to 3.90 (November 2007). In 2007,

nine companies publicly issued bonds to a value of Rp6.15

41


aggressively sought short-term profit taking and profit

realization, in particular to cover losses from the subprime

financial asset portfolio. Such behavior led to significant

corrections in the capital market and induced volatility.

Capital market corrections also led to negative sentiment,

which weakened the rupiah against the US dollar.

The Jakarta (JSX) Composite also experienced a sharp

correction; dropping 7% in August 2007 to reach its lowest

level of 1,908.64 on 17 August. Active stock investment

by foreign investors -mainly in the form of short-term profit

taking- triggered an upswing in prices and the JSX

Composite rallied to 2,745.83 by the end of December

2007. Therefore, as an aggregate for 2007, the JSX

strengthened by around 28%. By sector, strong index

performance was recorded in the agricultural sector, mining

sector and miscellaneous industrial sector.

On the one hand, portfolio behavior by foreign

investors stimulated a price increase, yet on the other hand

it also caused more volatile price fluctuations. The market

efficiency coefficients for stock exchanges in emerging Asian

Graph 2.46Asian Stock Market Volatility

Graph 2.45Inflows to SUN-SBI-Shares

-20

-10

0

10

20

30

StocksSecurities

Government Bonds


2 0 0 7

Trillions of Rp

0

10

20

30

40

50

60

70

2 0 0 7

JSX

KLCI

SET

PCOMM

STI

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

Equity Market

In semester II 2007, global equity markets experienced

significant corrections, mainly due to strong negative

sentiment stemming from deteriorating expectations

regarding the U.S. economic prospects as the fall out from

the subprime mortgage crisis continues to plague the global

economy. Such conditions have had a clear impact on equity

markets in emerging Asian markets as well as undermining

index performance in 2007. Moreover, several Asian bourses,

particularly in economies directly connected to the U.S.,

suffered from tumbling stock prices.

JSXJSXJSXJSXJSX 1,805.52 2,139.28 2,745.83 18.49 28.35

STISTISTISTISTI 2,985.83 3,548.20 3,445.82 18.83 -2.89KLCIKLCIKLCIKLCIKLCI 1,096.24 1,354.38 1,447.04 23.55 6.84

SETSETSETSETSET 679.84 776.79 858.10 14.26 10.47

PCOMMPCOMMPCOMMPCOMMPCOMM 3,940.47 5,148.42 4,422.22 30.65 -14.11HSCIHSCIHSCIHSCIHSCI 2,802.68 3,109.64 3,874.22 10.95 24.59

NIKKEINIKKEINIKKEINIKKEINIKKEI 336.39 356.40 301.09 5.95 -15.52

NASDAQNASDAQNASDAQNASDAQNASDAQ 3,415.29 2,603.23 2,674.46 -23.78 2.74DJIDJIDJIDJIDJI 12,463.15 13,443.75 13,365.87 7.87 -0.58

SIASASIASASIASASIASASIASA 6,979.53 13,202.68 18,658.13 89.16 41.32

KOSPIKOSPIKOSPIKOSPIKOSPI 1,434.46 1,743.60 1,897.13 21.55 8.81

Table 2.1Price Index Performance of Several Regional

Stock Exchanges

Sem II 07 2007

Growth (%)Dec 06 Jun 07 Dec 07

Graph 2.47Regional Stock Exchange: Share Index Performance

0

1000

2000

3000

4000

5000

6000JSX

SET

NIKKEI NASDAQ

PCOMM

STI KLCI

20072006

29Dec

29Jan

28Feb

29Mar

29Apr

29May

29Jun

29Jul

29Aug

29Sep

29Oct

29Nov

HSCI

42


markets were predominantly below 75%. This confirms that

market corrections have triggered more volatility in short-

term prices; however, the markets have remained resilient

so price stability in the long-term has been maintained.

Meanwhile, in 2007, financing through the equity

market increased as shown by the rise in share issuances

by around 17% to Rp328 trillion. This vastly outperformed

the previous year of just 5%. Impressive growth of stock

indices boosted market capitalization by 59% to around

Rp1,988.3 trillion. Meanwhile, the number of issuing

companies expanded by 24 to 468.

Bonds Market

In semester II 2007, the SUN (government bonds)

market, which acts as the reference of the domestic bonds

market experienced a mild correction and therefore

decreased by an average of 4%. The market correction

was principally due to a deferred reduction in the BI Rate,

which narrowed the potential SUN price increase. This

encouraged investors to switch portfolio from high-priced

SUN to SUN with below par prices, mostly through

purchases in the primary market. As a consequence, in

2007 the SUN price only grew around by 5% on average;

far below growth in 2006 which reached 20%.

Agriculture 1,190.71 1,680.12 2,754.76 41.10 63.96

Basic Industry 148.79 196.10 238.05 31.80 21.39

Cnstr, Property, RE 120.82 211.72 251.82 75.24 18.94

Consumer 390.19 437.01 436.04 12.00 -0.22

Financial 204.39 223.14 260.57 9.17 16.77

Infrastructure 754.54 750.43 874.07 -0.54 16.48

Mining 920.31 1,647.04 3,270.09 78.97 98.54

Miscellaneous 282.14 324.96 477.35 15.18 46.90

Trade Service 274.28 387.38 392.24 41.24 1.26

Table 2.2Sectoral Price Index

Sem II 07 2007

Growth (%)Dec 06 Jun 07 Dec 07

Graph 2.48Stock Market: Transaction Value & JSX

IndonesiaForeignJSX

0

500

1000

1500

2000

2500

3000Trillions of Rp JSX

Jan Feb Mar Apr May Jun Jul Ags Sep Oct Nov Dec

2 0 0 7

0

20

40

60

80

100

120

140

Graph 2.49Market Efficiency Coefficient

MEC-IHSG MEC-KLCI MEC-SETMEC-PCOMM MEC-STI

%

2 0 0 7

12Jan

12Feb

12Mar

12Apr

12May

12Jun

12Jul

12Aug

12Sep

12Oct

12Nov

12Dec

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

Graph 2.50Stock Market: Capitalization Value & Issuance Value

0

500

1,000

1,500

2,000

2,500

250

260

270

280

290

300

310

320

330

340(Capitalization Value, Trillions of Rp) (Emisi Value, Trillions of Rp)

Capitalization Value (BEJ)

Capitalization Value (BES)Emisi Value

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec2 0 0 7

Graph 2.51Price Performance of Several Series of SUN

90

95

100

105

110

115

FR0023 FR0025 FR0026 FR0027FR0028 FR0030 FR0043

2Jan

2007

2Feb

2Mar

2Apr

2May

2Jun

2Jul

2Aug

2Sep

2Oct

2Nov

2Dec

43


Keen interest from domestic investors in SUN was

reflected by burgeoning SUN ownership by banks and non-

bank residents. By the end of semester II 2007, domestic

bank ownership of SUN rose to Rp265 trillion, with a

relatively stable share of total SUN at around 58%. SUN

ownership by non-bank residents grew expeditiously, more

specifically by 19% to Rp116 trillion. Such growth

increased the share of non-bank residents» SUN ownership

from 22% (end of June 2007) to 25% (end of December

2007). Non-bank resident investors include individuals,

non-bank financial institutions, foundations and other

financial institutions.

The distribution of SUN liquidity concentrated around

tenors of 1 to 5 years, for which prices were too high and

above par. Expectations of a stall in the interest rate decline

in 2008 encouraged investors to reduce their ownership of

highly priced SUN and divert their investment to lower price

SUN. Concentration on 1 to 5 year tenors triggered switching

portfolio behavior and created pressure on SUN prices.

In 2007, company financing through the issuance

of corporate bonds increased dramatically. This was

primarily supported by the declining interest rate trend.

Corporate bond issuances went up by around 30% to

Rp134 trillion; comprehensively eclipsing the increase in

issuances the previous year (13%). In addition, the number

of companies issuing bonds expanded by 13 to total 175.

With such growth, financing through the issuance of

corporate bonds grew by 25% to around Rp85 trillion.

Mutual Funds

The declining trend of the interest rate throughout

2007 improved the performance of mutual funds. In 2007,

Graph 2.52Yield of 5-Year Tenure Investments

0

2

4

6

8

10

12%

2 0 0 7

2Jan

2Feb

2Mar

2Apr

2May

2Jun

2Jul

2Aug

2Sep

2Oct

2Nov

2Dec

Indonesia Philippines Thailand Singapore

Graph 2.54SUN: Market Liquidity of Various Tenures

Graph 2.53SUN Ownership

Banks Residents Foreign


Trillions of Rp

2 0 0 7

0

50

100

150

200

250

300

0

5

10

15

20

25

30

35

40

Years1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 29

FR VR ORI

Trillions of Rp

Graph 2.55Issuance and Position of Corporate Bonds

2006

155

160

165

170

175

180Emisi Position Emiten

2007

Emisi & Position, Trillions of Rp Emiten

0

20

40

60

80

100

120

140

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

44


the net asset value of mutual funds increased by 79% to

Rp91 trillion. This represents a slight increase on growth

in the previous year of 76%. Furthermore, it was also

supported by a persistently bullish equity market, which

boosted the net asset value of mutual funds in the form

of equity funds by around 300% to Rp35 trillion. The rise

in net asset value is in line with strong investor demand as

indicated by the expansion of participating units that grew

by approximately 47% and higher subscriptions (totaling

Rp122.8 trillion) compared to redemptions (reaching

Rp102.7 trillion).

alternatives including protected mutual funds, indexed

mutual funds and exchange traded funds. As a result of

diversification, the share of net asset value of each type of

mutual fund remained relatively equal, namely 23% (fixed

income), 38% (equity), 16% (mixed), 5% (money market)

and 18% (protected).

Graph 2.56Net Asset Value of Mutual Funds by Type

Graph 2.57Mutual Funds: Net Asset Value & Participating Units

Trillions of Rp

0

5

10

15

20

25

30

35

40


2 0 0 7

Fixed Income Stocks Mixed Money Market Protected

0

200

400

600

800

1000

1200

1400

1600

1800


NAB Triliun Rp - Unit Penyertaan Miliar NAB Unit Penyertaan

2 0 0 7

0

10

20

30

40

50

60

70

80

90

100NAB/Unit

Unit PenyertaanNAB

Graph 2.59Composition of Mutual Funds» Net Asset Value

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

%

StocksFixed Income Mixed

Money MarketProtectedIndex

Dec 03 Dec 04 Dec 05 Dec 06 Dec 07

Graph 2.58Mutual Funds: Redemptions and Subscriptions

Trillions of Rp

0

2

4

6

8

10

12

14Redemption Subscription


2 0 0 7

Corrections in the SUN market slowed growth in the

net asset value of fixed income mutual funds to around

11%. However, as a whole the corrections in the SUN

market did not actually affect the mutual funds market

due to the diversification of investments in various

In 2008, the net asset value of mutual funds is

projected to continue to rise due primarily to the

continuing, bullish equity market. Against this propitious

background, equity based mutual funds are expected to

prosper even further. Nevertheless, volatile equity prices

and potential risk stemming from new investment

alternatives that are not yet well understood by investors

may induce corrections in the mutual funds market. Thus,

greater diversification in mutual funds investment will be

the key in supporting stable growth in mutual funds.

45


Insurance Industry Performance and Potential Risk on theFinancial SystemBox 2.1

Insurance Industry Performance

One important industry in the Indonesian financial

system is the insurance industry. Based on the most

recent data, the number of insurance companies has

declined from 157 (2005) to 146 (2006), however,

capital has surged from Rp25 trillion (2005) to Rp34

trillion (2006). The implementation of risk-based capital

(RBC) has reduced the number of insurance companies

that are unable to strengthen their capital. Nonetheless,

the insurance business has expanded, as indicated by

the growing number of auxiliary institutions from 219

(2005) to 256 (2006).

In terms of performance, during 2006 assets

grew by 23% to Rp171 trillion, whereas premiums

and claims increased by around 14% to Rp52 trillion

and Rp38 trillion respectively. Most growth was

recorded in the life insurance industry, where assets

expanded by 31% to Rp71 trillion, and premiums and

claims went up by around 20% to Rp27 trillion and

Rp23 trillion respectively. The profit generated by the

life insurance industry nearly increased twofold to

Rp2.3 trillion.

In line with robust profit growth, the ROA, ROE,

ROI and investment yield from life insurance also

performed well. Life insurance became more active

and efficient in managing investment while remaining

prudent. Meanwhile, general insurance also became

Graph Box 2.1.1.Insurance Capital 2003-2006

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

2003 2004 2005 2006

Asuransi Jiwa Asuransi Kerugian

Reinsurance Asuransi Sos & JamsostekAsuransi PNS & TNI

Trillions of Rp

Graph Box 2.1.2.Assets-Premiums-Claims: 2003-2006

0

20

40

60

80

100

120

140

160

180

2003 2004 2005 2006

Assets Premi Klaim

Trillions of Rp

Graph Box 2.1.3.Insurance Profits: 2003-2006

2003 2004 2005 2006

Asuransi Jiwa Asuransi Kerugian

Reinsurance Asuransi Sos & Jamsostek

Asuransi PNS & TNI

Billions of Rp

0.0

500.0

1000.0

1500.0

2000.0

2500.0

I.I.I.I.I. Insurance CompanyInsurance CompanyInsurance CompanyInsurance CompanyInsurance Company

a. Life Insurance 60 57 51 45

b. Loss Insurance 104 101 97 92

c. Reinsurance 4 4 4 4

d. Social Insurance 5 5 5 5

II.II.II.II.II. Insurance AuxiliaryInsurance AuxiliaryInsurance AuxiliaryInsurance AuxiliaryInsurance Auxiliary

a. Insurance broker 120 128 134 154

b. Reinsurance broker 21 18 21 29

c. Insurance Adjuster 25 30 30 30

d. Actuarial Consultant 20 23 28 34

e. Insurance Agent 0 5 6 9

Table Box 2.1.1Insurance Company Expansion 2003-2006

2003 2004 2005 2006

46


customers, besides receiving coverage, also receive a

certain investment return.

more active in investment; however, in terms of

investment management it seemed to be less efficient

than life insurance.

In 2006, 21 companies offered Unit Link. The

Unit Link premium has continued to grow despite its

relatively low contribution to total life insurance

premiums; around 25%. Unit Link has enabled life

insurance to become more active in investment and

consequently market risk has intensified. This is clearly

indicated by poor investment returns during periods

of upward trending interest rates (2005) but vastly

improved investment returns when the interest rate

trends downwards (2006).

Strong life insurance performance is also well

supported by cooperation between life insurance

companies and banks through Bancassurance. By end

of 2007, 27 major banks carried Bancassurance, mainly

in the form of insurance product agents including Unit

Link. Bancassurance in this form is advantageous for

Graph Box 2.1.4.Several Insurance Company Indicators

Graph Box 2.1.5.Investments by Insurance Companies: 2003-2006

2005 2006

ROA-AJ ROA-AU ROE-AJ ROE-AU ROI-AJ ROI-AU Invyield- AJ

Invyield- AU

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

18.00

20.00

0

10

20

30

40

50

60

70

2003 2004 2005 2006

Trillions of Rp

Securities Deposits Stock & Bonds Mutual Funds

Regarding investment activities, insurance

companies became more active in investment, not only

in term deposits but also equity and bonds as well as

mutual funds. In 2006, investment by insurance

companies in equity and bonds leapt 158% to Rp60

trillion, whereas investment in mutual funds increased

by 29% to Rp10 trillion.

Risk Potential

It is worth noting that the relatively robust

performance of life insurance companies is principally

supported by the development of a non-conventional

insurance product known as Unit Link. The product

has the characteristics of both a conventional insurance

product as well as a savings product. Unit Link

Graph Box 2.1.6.Premiums: Unit Link and Total: 2003-2006

Graph Box 2.1.7.Investment Return: Unit Link against Total: 2003-2006

0

1

2

3

4

5

6

7

2003 2004 2005 2006

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

Hasil Inv Unit Link Hasil Inv Total Hsl Inv UL/Hsl Inv Total

Billions of Rp Hasil Inv UL/Hasil Inv Total

0

5

10

15

20

25

30

2003 2004 2005 2006

Premi Unit Link Total Premi Premi UL/T Premi

Billions of Rp % Premi UL/Premi Total

0.00

5.00

10.00

15.00

20.00

25.00

30.00

47


both parties. On the one hand, insurance companies

have access to a wider customer base; while on the

other hand, banks have the opportunity to boost their

fee-based income.

However, Bancassurance activities are still prone

to potential bank risk exposure, typically in the form

of reputational risk due to the following reasons:

Possibility of misselling due to poor understanding

by the banks» sales personnel regarding the

characteristics of insurance products.

Insurance products may develop becoming more

similar to bank products. Closer association to

bank products will lead to a more complicated

claims process;

With potential higher market risk and reputational

risk, banks should be more prudent in offering Unit

Link products and Bancassurance. Such prudence must

be developed through comprehensive understanding

of the products offered as well as risk mitigation steps

that have been prepared to anticipate loss potential.

48


Halaman ini sengaja dikosongkan

49

Chapter 3 Prospects of the Indonesian Financial System

Chapter 3Prospects of the IndonesianFinancial System

50



51


3.1. ECONOMIC PROSPECTS AND RISK

PERCEPTION

Despite recent inflationary pressures in the domestic

economy spurred by the slowdown in the global economy,

the prospects of the Indonesian economy remain positive

with projected growth exceeding 6%. Consensus forecasts

for the Asia Pacific region have projected that economic

growth will be supported by increases in international trade

and controlled inflation.

In addition, investment and exports have become

the foundations of economic growth rather than

consumption, which had supported the Indonesian

economy since the crisis. Such conditions have been

stimulated by a downward domestic interest rate trend

and steadily growing business confidence, despite the fact

that the economy has not quite recovered to pre-crisis

levels. Optimistic macroeconomic prospects have reinforced

financial system stability and supported sustainable

domestic economic growth.

Meanwhile, foreign investors still deem economic

conditions and investment instruments in Indonesia

attractive and relatively stable, despite several hikes in risk

perception as reflected by widening yield spread. However,

vigilance over investment inflows, particularly short term,

remains critical as they are vulnerable to external shocks

with the potential to trigger a sudden reversal.

The outlook of the Indonesian financial system remains positive amid rising

inflationary pressures and sluggish global economic growth. The internal

condition of the financial sector, particularly the banking industry, contributes

to this expectation. Strong capital and improvement in risk management will

help Indonesian banks in mitigating future risks. In addition, closer

coordination between the banking and the capital market authorities as well

as non-bank financial institutions will also support financial system stability.

Prospects of the Indonesian Financial SystemChapter 3

GDP (%yoy) 6.0 6.3 6.5 6.1 6.2 6.1 6.1 6.1

Inflation (% yoy) 6.4 6.0 6.5 6.6 6.4 6.7 6.4 6.6

Balance of Trade (US$ milliar) 7.9 8.4 8.1 8.7 8.5 8.9 9.4 10.4

Table 3.1Consensus Forecasts of Several Economic Indicators

2007 2008

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

Source: Asia Pacific Concensus Forecast

52


3.2. BANK RISK PROFILE: LEVEL AND DIRECTION

Indonesia is for the most part a bank-based economy,

and therefore, the level and direction of the bank risk profile

strongly influences financial system stability. In general,

the risks confronting banks were largely mitigated and their

near-term outlook appears stable. Pressures in the domestic

economy and global financial markets did not undermine

banking system resilience. Intermediary functions have

gradually returned to the pre-crisis level, whilst efficiency

improved and non-performing loans diminished. As a

result, profitability has increased despite a slight reduction

in CAR attributable to greater credit extension.

Meanwhile, the improved bank intermediary function

was balanced by a better risk control system (RCS) for credit

risk. Enhanced credit risk management, followed by credit

restructuring at several state-owned banks ameliorated

bank loan quality. As stated in Chapter 2, by the end of

2007, for the first time since the crisis, the gross ratio of

non-performing loans dropped below 5%.

However, amid various internal and external issues,

for example the imminent recovery of the real sector, the

high frequency of natural disasters, commodity price

shocks for staples, and the soaring global oil price, banks

are expected to confront potential increasing credit risk

exposure. Nevertheless, with the improved RCS, the rise

in credit risk exposure is not projected to be significant.

Meanwhile, liquidity risk remains low with a stable

trend in line with the high ratio of liquid assets against

non-core deposits. Bank liquidity was also well-

maintained, reflected by a lack of volatility in the Inter-

bank Money Market (PUAB) which can disrupt bank

performance. However, potential liquidity risk remains

due to the unbalanced structure of bank deposits, in

terms of tenure, volume and ownership. Possible shocks

in the global market that can be transmitted to the

domestic financial market have the potential to increase

liquidity risk.

Market risk stemming from the exchange rate is

relatively low and stable. Technically, exchange rate risk is

manageable due to the relatively low net open position of

banks, far below the maximum ratio of 20%. Whereas,

market risk emanating from the interest rate will remain

moderate and stable, in line with the bank maturity profile

that is short for the short term and long for the long term.

The maturity profile strategy has, hitherto, been effective

in overcoming interest rate risk, however, vulnerabilities

may occur if there is a swing in the interest rate. This is of

concern because the financial instruments that can be

utilized to control interest rate risk are relatively limited

due to the underdeveloped hedging and derivatives

markets in Indonesia.

Furthermore, market risk exposure from SUN prices

is also moderate and stable. The strategy undertaken by

banks to lower SUN price risk is to maintain a small

portfolio of SUN for trading purposes. Nevertheless,

caution must be exercised especially if the trading SUN

portfolio is expanded and accompanied by price shocks

because market volatility is generally beyond the control

of banks.

The near-term outlook for operational risk remains

difficult to predict. Numerous challenges beset Indonesian

banks in terms of assessing operational risk due system

and technological constraints. Moreover, limitation of loss

data availability has been a daunting challenge, and hence,

Indo 41 Ba3 (Moody's) 7.27 386.6 423.9

Indo 17 BB+ (S&P) 8.96 475.2 495.2

Indo 45 Ba3 (Moody's) 11.01 546.6 653.4

Table 3.2Indonesian Risk Perception

Source: Bloomberg

Bonds Rating Y-t-m (%)Yield Spread (bps)

Sep 2007 Dec 2007

53


modeling and quantifying the risk is an extremely arduous

task. Against this unfavorable backdrop, Bank Indonesia

will continue to boost capacity building of banks whilst

conducting rigorous supervision over the quality of banks»

internal control. Basel II implementation is expected to

improve competence and capacity in measuring and

controlling operational risk in the banking industry.

3.3. PROSPECTS OF THE INDONESIAN FINANCIAL

SYSTEM

Financial system stability was well preserved during

the second semester of 2007 with a positive near-term

outlook. This is in line with improved macroeconomic

conditions, relatively stable domestic financial markets, as

well as improved bank infrastructure and performance.

Financial system stability in 2007 was largely affected

by global economic developments, such as the subprime

mortgage debacle and the persistently soaring

international prices of oil, commodities, food and other

basic necessities. Growing pressures stemming from the

global economy slightly raised the financial stability index

from 1.21 in late June 2007 to 1.25 at the end of December

2007.

Entering 2008, increased uncertainty in global

financial markets as the second-round effects of the

subprime mortgage fiasco and deteriorating U.S. economy

will potentially undermine domestic financial markets and

corporate performance that constitute the main borrowers

from banks. Domestically, persistent natural disasters have

the potential to exacerbate non-performing loans. These

issues are expected to pressurize financial system resilience

in the first semester of 2008; therefore, the financial system

stability index will predictably rise slightly to 1.34 by the

end of June 2008.

Regardless of the potential decrease in financial

system stability originating from the corporate sector as

the predominant borrowers from banks, in general, banks

are projected to overcome this issue by accumulating

sufficient reserves of productive assets and capital.

Additionally, credit restructuring will continue and is

expected to raise the quality of bank credit.

Graph 3.1Bank Risk Profile and Direction

Smt-II 2007

Outlook

Smt-II 2007

Outlook

Smt-II 2007

Outlook

Inherent Risk

HighM

oderateLow

Strong Acceptable WeakRisk Control



Liquidity Risk Credit RiskMarket Risk

Exchange Rate

InterestRate

GovernmentBonds Price

Graph 3.2Financial Stability Index

2.5

2

1.5

1

0.5

0

1.251.271.34

M04 M08 M12 M04 M08 M12 M04 M08 M12 M04 M08 M12 M04 M08 M12 M04

2003 2004 2005 2006 2007 2008

FSIFSI (average)

54


Shocks and adverse developments occurring in the

domestic and global economy are challenges. The soaring

global price of oil and other basic commodities have, in

fact, fostered the search for new alternative energy

sources. Besides, since the crisis, strategic infrastructure

has not received the attention it deserves, consequently,

the government rolled out several policy packages to

accelerate infrastructure development. These efforts have

provided significant business opportunities to several

sectors such as crude palm oil, coal, sugar, infrastructure

and property. Expansion of these sectors should be

supported by a more auspicious investment climate, as

well as financing from financial institutions and the capital

market.

3.4. POTENTIAL VULNERABILITIES

The factors that induced potential vulnerabilities

during the previous semester are predicted to persist and

overshadow financial system stability. Externally, the most

significant vulnerabilities are associated with global

economic shocks, primarily the lasting impacts of losses

brought about by the subprime mortgage crisis, soaring

global oil and commodity prices, as well as sluggish global

economic growth.

Until now, the subprime mortgage crisis has endured

affecting several other segments. In the United States, the

crisis has triggered losses at major financial institutions,

and also monoline insurance companies, which ensure the

timely repayment of loans and interest from bonds or other

securities after default has occurred. The two largest

monoline insurance companies in the United States (Ambac

Financial Group Inc., and MBIA) suffered losses and saw

their ratings slip, which precipitated a very low stock price.

Such negative growth could lead to a narrow credit market

in the United States and other associated developed

countries.

Even though Indonesia avoided direct losses due to

the subprime mortgage crisis, impacts were felt in line with

greater integration between the domestic and global

economies. Meanwhile, global oil price hikes could lead

to higher production costs and trigger downstream price

hikes, which would weaken public purchasing power. As

a consequence, the prospect of non-performing loans

would be bleak, which in turn would place pressure on

the financial system (see Box 3.1).

Sluggish global economic growth, which was

engendered by a slowdown in the U.S. economy, has

further widened to encompass several European countries.

The Federal Reserve»s policy to slash interest rates in the

United States in order to stimulate economic growth, has

in fact hastened a wider interest rate differential that has

the potential to catalyze short-term capital inflows to the

domestic financial market. Vulnerability will appear should

a sudden reversal of these capital inflows transpire.

Domestically, vulnerabilities exist in the form of

frequent natural disasters that have decimated parts of

Indonesia. Furthermore, potential vulnerabilities may

emerge from soaring commodity prices as well as

preparations for the upcoming general election. Bank

regulations regarding credit extension to borrowers in

disaster zones have been enacted in response to the

potential credit risk stemming from persistent natural

disasters (see Box 3.2). Meanwhile, control of basic

commodity prices and anticipatory measures in preparation

for the upcoming General Election require firm action from

the Government.

Several challenges must be confronted by Indonesia»s

banks in the near future. The main challenges include bank

consolidation and the implementation of Basel II. Bank

consolidation will predictably improve competitiveness,

boost economies of scale of domestic banks and simplify

bank supervision. On the other hand, Basel II

55


implementation will foster higher quality bank risk

management.

Potential vulnerabilities can be lessened by placing

more emphasis on the Financial System Stability Forum

(FSSF), which aims to act as a medium to exchange

information and resolve risks in the economy that could

trigger a crisis. In the future, closer coordination between

the banking and the capital market authorities as well as

non-bank financial institutions should be perused to bolster

financial system stability.

56


Impact of Fuel Price Increases on Financial System StabilityBox 3.1

Approaching the end of 2007 and entering 2008,

the global oil price continued to soar to new heights,

even surpassing US$110 per barrel. As a result, extreme

vigilance is required as was evidenced by experience

from 2005 that indicated a rise in the oil price spurred

pressures on the financial system, particularly through

an increase in bank NPL.

However, when reviewing data from 2007, the

correlation between the global oil price and bank NPL

is not always in the same direction. As illustrated in

Graph 3.1.1, at times when the global oil price tended

to rise, bank NPL went down. This was possible because

during that period, bank NPL was most strongly

influenced by credit restructuring. However, the impact

of the global oil price will be noticeable in a few months;

therefore, stringent surveillance is required by banks

on borrowers sensitive to oil price fluctuations. With

prudent surveillance, a rise in NPL and the subsequent

provisions can be estimated.

Additionally, to investigate the impact of global

oil price changes on NPL, banks have begun

conducting simulations. The calculations in the

simulation are based on gross NPL at the end of

December 2007 (4.6%). Simulation results showed

that, ceteris paribus, each 10% increase in the global

oil price will generate three-month gross NPL ratio

of 0.20%. Thus, if the global oil price reached

USD115 and persisted, the gross NPL ratio for the

three subsequent months is estimated to be around

5.66% (see Table Box 3.1.1.).

The above figures demonstrate that the rise in

the global oil price could significantly impact the banks.

Therefore, it should not be neglected in terms of

financial system stability surveillance.

Graph Box 3.1.1.Bank NPL and Global Oil Price

USD/barel %

100

90

80

70

60

50

40

30

20

10

0

10.00

9.00

8.00

7.00

6.00

5.00

4.00

3.00

2.00

1.00

0.00Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov

2004 2005 2006 2007

NPL (right axis)Oil Price (left axis)

USD 75 USD 85 USD 100 USD 110 USD 115 USD 120 USD 125

Table Box 3.1.1.Projected Gross NPL in 2008 against Various Oil Price Scenarios

NPL gross Ratio (%) 4.82% 5.02% 5.37% 5.57% 5.66% 5.75% 5.82%

World OilPrice Scenarios

57


Natural Disasters, Life Cycles and Financial System StabilityBox 3.2

In recent times the full panoply of natural disasters

has befallen Indonesia. News of earthquakes, flooding,

landslides and tornados featured in the mass media

almost daily. Natural disasters have plagued Indonesia

primarily due to relentless environmental destruction.

Environmental destruction and the ensuing

natural disasters can have negative affects on financial

system stability. Natural disasters not only involve

astronomical economic costs, but can also decimate

infrastructure, which can disrupt financial services and

the payment system. For banks, natural disasters can

raise credit risk through burgeoning NPL and also

intensify operational risk. Furthermore, serious

operational disruptions can lead to reputational risk.

Thus, a proper Disaster Recovery Plan or Business

Continuity Plan should be thoroughly prepared.

There can be no doubt that saving the

environment is the best way to prevent natural

disasters. As the banking authority, Bank Indonesia

has endeavored to encourage banks to support

environmental concerns. This is reflected by Bank

Indonesia Regulation (PBI) No.7/2/PBI/2005 dated

20January 2005 on Productive Asset Evaluation for

Commercial Banks that mandates banks to evaluate

their environmental business activities when assessing

the business prospects of a borrower. Furthermore,

to support economic recovery following a natural

disaster, Bank Indonesia promulgated PBI No.8/15/PBI/

2006 dated 5 October 2006 regarding Special

Treatment of Bank Credit in Regions Affected by

Natural Disasters. Additionally, banks can also help to

protect the environment through project financing,

for example mitigating the greenhouse effect, seeking

alternative fuels, refuse recycling and industrial waste

processing.

A relatively new and hotly debated issue relating

to the environment is global warming. This topic

featured prominently at the United Nations Climate

Change Conference held in Bali on 3-14 December

2007. In this context, the most pertinent question is

how can the financial sector actively contribute in

mitigating global warming?

Indonesia has abundant natural resources, for

instance the awe-inspiring forests that account for

25% of forests in East Asia and the Pacific. A report

from World Bank states that Indonesia is a nation

characterized by mega biodiversity. With such

expansive forested areas, Indonesia has the

opportunity to mitigate greenhouse gases, which have,

for a long time been considered as the main cause of

global warming. The carbon market, which was

created by the Kyoto Protocol in 1997, provides a rare

opportunity for financial institutions to become

involved in financing business activities that can

mitigate the emission of greenhouse gases (GHG).

Under the terms of the carbon market, a country

that exceeds its quota for GHG emissions can pay

compensation by contributing to the GHG emission

mitigation project in its own country or abroad. A

carbon transaction is defined as a contract purchase

where the first party compensates the second for

conducting mitigating activities for GHG emissions.

Payment can be in cash, equity, debt, convertible debt,

warrant or in the form of technological conversion.

The European Union Emissions Trading Scheme (EU

ETS) is the largest capitalized carbon market that

represents developed countries which are actively

involved in the carbon market to finance GHG emission

mitigation in European countries as well as developing

countries.

Due to the limited or negligible exposure of

Indonesia to the carbon market, the carbon market

share in the Indonesian financial market is also almost

null, thus its impact on financial system stability can

58


be ignored. However, the carbon market has the

potential to fund environmental projects in Indonesia.

Furthermore, as Indonesia has the potential to

contribute extensively in mitigating the greenhouse

effect, carbon market exposure is likely to increase. The

international carbon market expanded its capitalization

to an amount of US$30 billion in 2006; triple the

amount in 2005. It is time to consider efforts to

encourage carbon trading in the Indonesian financial

market as one source of financing for environmental

projects

References

Asia Cleantech, ≈Avoided deforestation credits head

for the voluntary carbon markets∆, 7 January 2008.

New Energy Finance, ≈Clean energy investment breaks

the $100bn barrier in 2007∆, Press Release 2

January 2008.

The World Bank, ≈Environment at a Glance -

Indonesia∆, 2004.

The World Bank, ≈State and Trends of the Carbon

Market 2007∆, May 2007.

United Nations Framework Convention on Climate

Change (UNFCCC) website (http://unfccc.int).

59

Chapter 4 Financial Infrastructure

Chapter 4Financial Infrastructure

60



61


4.1. PAYMENT SYSTEM

4.1.1. Payment System Performance

The Indonesian payment system performed robustly

and did not exhibit any potential risk potential and has

fully supported financial system stability. In the second

semester of 2007, nearly all (around 96.51%) of the total

value of inter-bank payment transactions was performed

through the Bank Indonesia Real Time Gross Settlement

system (BI-RTGS). Meanwhile, transactions processed

through clearing totaled just 3.49%, with the remainder

through credit cards and account-based cards (ATM,

ATM+Debit and Debit cards).

Compared to the previous semester, the value of

payment transactions through the BI-RTGS system in the

reporting semester declined by 10.42% (from Rp22.09

thousand trillion to Rp20.01 thousand trillion), despite a

surge in volume by 15.34% (from 3.87 million transactions

to 4.57 million transactions). The decline in payment

transaction value was due to infrequent intervention in

monetary management. Meanwhile, the swell in payment

transaction volume was attributable to increased economic

activities in the community for special occasions such as

religious celebrations, year-end bookkeeping and New Year

festivities. Moreover, the rise in payment transaction volume

owed to higher transaction activities in the foreign exchange

market to fulfill foreign currency demand from the corporate

sector, as well as increasing transaction activities in the capital

market during the reporting semester.

Indonesian financial infrastructure continued to support the preservation of

financial system stability. Despite increases in volume and settlement value,

the payment system functioned without fault, successfully mitigating

settlement risk and operational risk. Meanwhile, the Credit Information Bureau

played a more significant role in the provision of credit information to business

players. In addition, financial infrastructure was strengthened by the more

encompassing function of the Financial System Stability Forum (FSSF).

Graph 4.1Payment System Transaction Activities in

Semester II 2007

0.0002%

96.5101%

0.0045%3.4852%

Credit CardAccount Based Card (ATM, ATM+debet & debet)

RTGSClearing

Financial InfrastructureChapter 4

62


As a continuation of activities in the previous semester,

the implementation of Bank Indonesia»s National Clearing

System (SKNBI) through Local Clearing Providers (LCP)

proceeded as planned. Consequently, by the end of

semester II 2007 41 LCP had implemented SKNBI.

Meanwhile, the value of credit clearing transactions in the

reporting semester totaled Rp195.49 trillion with a

transaction volume of 19.62 million transactions. Conversely,

the value of debit clearing transactions amounted to

Rp529.23 trillion with a transaction volume of 20.28 million

transactions. Contrasted against semester I 2007 both credit

and debit clearing increased in value and volume. The rise

in value and volume of credit clearing was 12.91% and

8.22% respectively, whilst debit clearing expanded in value

and volume by 11.47% and 2.11% respectively.

In the reporting semester, Bank Indonesia

approved seven payment card providers in the form of

credit cards, debit cards, ATM cards and pre-paid card.

Despite the increasing number of cards issued, actual usage

of credit cards, debit cards and ATM cards has slowed when

compared to the previous semester. The total number of

cards issued in the reporting semester was 44.35 million

cards, representing a jump of 8.74% over the previous

semester. Meanwhile, the transaction value attributable

to payment cards totaled Rp0.98 thousand trillion; a decline

of 12.51% compared to the previous semester, with a

transaction volume of 657.26 million; down 23.12%. The

decline in payment card transaction value and volume was

principally due to a contraction in the volume and value

of account-based card transactions in the form of ATM

cards and ATM+debit cards, which dominated (around

95.97%) payment card transactions.Transaction Transaction Transaction Transaction Value Volume

Value Volume Value Volume

(thousand (thousand

trillions) (millions) trillions) (millions)

Table 4.1Settlement Value and Volume Development in

BI-RTGS System

GrowthSemester I-2007 Semester II-2007

Rp22.09 3.87 Rp20.01 4.57 (10.42%) 15.34%

4.1.2. Payment System Policy and Risk

Mitigation

In the operation of the payment system, Bank

Indonesia must confront risk as the regulator and operator

of the payment system as well as one of its users. To

mitigate the inherent risk potential, Bank Indonesia

undertakes the following measures:

a.a.a.a.a. Intensification of BI-RTGS Adherence to CoreIntensification of BI-RTGS Adherence to CoreIntensification of BI-RTGS Adherence to CoreIntensification of BI-RTGS Adherence to CoreIntensification of BI-RTGS Adherence to Core

Principles for Systemically Important Payment SystemsPrinciples for Systemically Important Payment SystemsPrinciples for Systemically Important Payment SystemsPrinciples for Systemically Important Payment SystemsPrinciples for Systemically Important Payment Systems

(CP SIPS)(CP SIPS)(CP SIPS)(CP SIPS)(CP SIPS)

Core Principles for Systemically Important Payment

Systems (CP SIPS) is an international standard issued

by the Bank for International Settlements (BIS),

through the Committee on Payment and Settlement

Systems (CPSS). Fulfillment of this international

standard will bolster risk mitigation.

Furthermore, by adhering to the CP SIPS, regulations

concerning the BI-RTGS system become more

transparent, including publishing the charges that

apply to Bank Indonesia when using the system.

Other than transparency, regulations applicable to the

Credit card 9.15 67.22 39.96

Debit card (ATM

and ATM+Debit) 35.20 990.04 941.64

TotalTotalTotalTotalTotal 44.3544.3544.3544.3544.35 657.26657.26657.26657.26657.26 981.20981.20981.20981.20981.20

Table 4.2Payment Card Transactions

Total Transaction TransactionCards Type Cards Volume Value

(in millions) (in millions) (in trillions)

63


BI-RTGS system also consider the efficiency of system

participants, providing freedom to choose their

participation in the BI-RTGS system. In terms of the

application, innovative new safety features are being

implemented to ensure the safety of the administrator

(Bank Indonesia) and participants. In addition, Bank

Indonesia will also issue regulations regarding

customer protection for users of the payment system,

amongst others including protecting the credit and

debit accounts of customers as well as providing

interest and compensation.

b.b.b.b.b. Payment System OversightPayment System OversightPayment System OversightPayment System OversightPayment System Oversight

Effective oversight will mitigate risk in the payment

system. As part of the efforts to maintain a quick,

safe and reliable BI-RTGS system, Bank Indonesia has

been conducting onsite and offsite surveillance of

participants. Onsite surveillance is performed through

direct site visits to participants» production locations

to confirm participant compliance to applicable BI-

RTGS system regulations. Conversely, offsite

surveillance is performed by analyzing submitted

reports consisting of internal audit reports and security

audit reports.

c.c.c.c.c. Business Continuity Plan for the Payment SystemBusiness Continuity Plan for the Payment SystemBusiness Continuity Plan for the Payment SystemBusiness Continuity Plan for the Payment SystemBusiness Continuity Plan for the Payment System

To maintain the BI-RTGS system, Bank Indonesia

conducts periodic trials using several scenarios to

prepare and train operational personnel so they are

always prepared for any eventuality. The trials also

measure the preparedness of the administrator»s

backup system. To maintain the BI-RTGS system in

terms of the participants, Bank Indonesia provides

opportunities for participants to test their connection

to the administrator in order to ensure the readiness

of the backup system. Should the backup system fail,

Bank Indonesia also has a Guest Bank facility, which

can be utilized by participants to settle outstanding

transactions in the BI-RTGS system.

d.d.d.d.d. Security Upgrades for Payment Cards Security Upgrades for Payment Cards Security Upgrades for Payment Cards Security Upgrades for Payment Cards Security Upgrades for Payment Cards (APMK(APMK(APMK(APMK(APMK)))))

The licensing process for payment cards can be used

to enhance the safety of payment cards before they

become too widely used by the public. Bank

Indonesia applies prudential principles in the licensing

process of APMK issuances such as by analyzing

requests by candidate providers of payment cards.

Improving safety can be implemented from the

technological side by implementing chip technology

in ATM cards and debit cards. Meanwhile, to minimize

risks to customers, Bank Indonesia conducts direct

oversight on APMK providers and indirect oversight

by analyzing periodic APMK performance reports

submitted to Bank Indonesia.

4.2. CREDIT INFORMATION BUREAU

Another important step taken to strengthen

Indonesian financial sector infrastructure is the establishment

of the Credit Information Bureau (BIK) at Bank Indonesia.

The establishment of BIK is one program contained within

the Indonesian Banking Architecture (IBA), particularly the

fifth pillar which is to complete the existing infrastructure in

order to support a healthy banking industry.

In general, BIK is mandated with assisting banks and

other financial institutions to smooth the process of fund

allocation and the application of risk management through

the provision of reliable information on debtor quality.

Complete and transparent information on debtors is vital

to avoid asymmetric information in credit extension to

minimize credit risk.

The provision of debtor information has actually long

been performed by Bank Indonesia. It was initially known

64


as the Credit Information System which then became the

Fund Allocation Information System and since 2005 has

been known as the Debtor Information System (DIS). DIS

is a system to manage and provide information on

individual debtors.

Since the promulgation of BI Regulation (PBI) No.7/

8/PBI/2005 dated 24 January 2005 on DIS, the debtor

information report submitted to Bank Indonesia must be

published online on a website created by Bank Indonesia.

The first application of web-based DIS was version 504;

currently version 510 is being used. Improvement and

development of the DIS application will help expedite

online and real-time DIS implementation. DIS coverage

includes the following:

online to Bank Indonesia monthly through the web-

based DIS application.

Those whom submit their debtor reports according

to prevailing regulations have the right to obtain

Individual Debtor Information (IDI) online and in real

time. Information covered by IDI includes debtor

identity, debtor owner/manager, facilities received by

the debtor from the reporting bank, outstanding debt

or facilities, collateral and credit quality.

Penalties on those whom fail to submit reports or

corrections are imposed according to prevailing

regulations or as per existing agreements.

The differences in regulations between the current

DIS application and the old system are as follows:

Eligible to submit reports Commercial Banks Commercial Banks, Rural Bank, PKKSB,and LKNB

IDI On line but not in real time On line and in real time

Reported Ceiling Rp50 million or more Value of all provided facilities

Debtor Identification Number (DIN) No unique number Each debtor receives a unique DIN

Audit No special DIS audit Special DIS audit

Report Submission Through switching - PT Aplikanusa Lintasarta Direct to BI server (Head Office)

Communication Network Dial up via VSAT Dial up via BI extranet

Table 4.3Comparisons of DIS Regulations

Description Old DIS Regulation Current DIS Regulation

Those reporting on DIS include Commercial Banks,

Rural Banks, Sharia Banks, Non-bank Credit Card

Providers (LPKKSB) and Non-bank Financial

Institutions. For Commercial Banks and Rural Banks

with assets totaling Rp10 billion or more as well as

LPKKSB, reporting is mandatory. Oppositely, for other

financial institutions and Rural Banks with assets of

less than Rp10 billion, reporting is on a voluntary basis.

Debtor reports include all fund provision facilities

recorded on the books from Rp1 and above.

Debtor information reports have to be submitted

For credit providers, BIK and DIS are particularly

beneficial in terms of assisting a time-efficient analysis and

decision-making process for credit extension. In addition,

with comprehensive and accurate information, credit risk

can be minimized. Meanwhile, to the receivers of credit,

BIK and DIS will speed up credit approval times. Furthermore,

new customers have wider access to credit providers as their

credit performance information can be accessed by potential

creditors through DIS. Another benefit is that debtors can

check the accuracy of their credit history by submitting a

written request to Bank Indonesia with proof of identity.

65


4.3. FINANCIAL SYSTEM RISK MITIGATION

4.3.1. Financial System Stability Forum

The Financial System Stability Forum (FSSF) has

increasingly underpinned its pivotal role as a venue of

coordination among authorities responsible for safeguarding

financial stability in Indonesia. During the second semester

of 2007 FSSF delivered several major initiatives to bolster

the domestic financial system and hosted a regular

information exchange on issues surrounding financial system

developments both globally and domestically. As reported

in the previous Financial Stability Review (FSR No. 9), FSSF

consists of the Steering Forum, Executive Forum and

Working Groups, which function as follows:

To support decision-making to prevent systemic crisis

emanating from problem banks;

To coordinate and exchange information in order to

harmonize legislation and regulations for banks, non-

bank financial institutions and the capital market;

To prepare a Macro Early Warning System for the

financial sector and to mitigate institutional problems

in the financial system with systemic potential based

on the information gathered by the early warning

systems of respective supervisory institutions;

To coordinate and synchronize the drafting of

Indonesia Financial System Architecture (IFSA).

To coordinate preparation of the Financial Sector

Assessment Program (FSAP).

To support the implementation of the functions

mentioned, working groups have been formed at the

Organizing Forum level since the second half of 2007.

These include IFSA and FSAP Preparation, Subprime

Mortgage Crisis, Crisis Management Protocol, and

Government Bond Repo working groups.

The FSSF regularly holds meetings to discuss the latest

developments in the Indonesian financial sector. In the

meetings, required anticipatory steps are discussed to

prevent unprecedented shocks. Moreover, to encourage

information exchange, each month Bank Indonesia

disseminates the latest information to FSSF regarding

banking industry performance and the assessment results

of overall financial system stability.

4.3.2. Crisis Management Protocol

Meanwhile, in association with Crisis Management

Protocol (CMP), several milestones have been completed

including setting CMP coverage. The objective will be to

minimize the impact of financial distress. At present, a

comprehensive CMP is being developed and will be

followed by a legal framework, as well as an organization

and coordination mechanism, infrastructure preparation,

data and information sharing, indicators and scenario

setting, communication program and crisis simulation.

66



67

Article I - Property Industry Survey: Observing Potential Pressure on Repayment Ability

Ar t ic le

68



69


Article I

Property Industry Survey:Observing Potential Pressure on Repayment Ability

Wimboh Santoso5, Noer Azam Achsani6, Herawanto7

The goal of this survey is to build an economic model to be applied as an early warning system for the

negative effects of property and real estate industry growth on financial system stability and also to investigate

the financing behavior of real estate and property industry players. Utilizing data from 1996 √ August 2006, the

results demonstrate that the EWS model built in this study can comprehensively explain the behavior of GDP

construction, property credit and property NPL, especially on over 3, 6 and 12-month prediction periods.

5 Director, Financial System Stability Bureau, Directorate of Banking Research and Regula-tion, Bank Indonesia, [email protected]

6 Researcher, Institute for Research and Community Empowerment of Bogor AgriculturalInstitute (IPB), [email protected]

7 Senior Researcher, Financial System Stability Bureau, Directorate of Banking Researchand Regulation, Bank Indonesia, [email protected]

I. INTRODUCTION

The property industry constitutes one of the

preeminent drivers of economic growth in any country. In

most developing countries, the property industry plays a

strategic role as it involves both upstream and downstream

industries. Rapid property industry growth is swiftly

transmitted to other industrial segments such as cement,

reinforced concrete, bricks, log/wood/timber, consultants

and real-estate agents. However, the implications of

property industry growth are not only limited to the

industries mentioned. Property industry growth spreads

quickly to the financial services sector because property

companies require investment funds to begin construction,

which are primarily sourced from banks/financial

institutions. On the other hand, house buyers who require

funds to finance their property purchase also seek financing

from banks/financial institutions. At this point the financial

system becomes entwined with the property industry.

Growth in the real estate and property industry in

Indonesia over the past three years has shown significant

progress following the market crash due to the 1997

Economic Crisis. Such expansion in the real estate and

property industry can be seen as an indicator of improving

domestic economic conditions. That is because growth

in this industry is tightly correlated to labor as well as the

various support industries (such as cement, bricks, tiles,

70


early warning system can future property industry growth

be predicted.

Stage two involves a survey to study the financing

behavior of business players in the real estate and property

industry (developers, banks and buyers) and to investigate

the expectations of industry players regarding the future

prospects of the industry. The survey will be used to clarify

the economic model built in the initial stage.

2. EARLY WARNING SYSTEM FOR THE REAL

ESTATE AND PROPERTY INDUSTRY IN INDONESIA

Shocks (either from internal or external sources) will

trigger fluctuations in the economy. In the long run, such

fluctuations form the business cycle of a fluctuating

economy that is highly likely to reoccur in the future. If

such a cycle can be well understood then future economic

behavior should be known long in advance of its

occurrence. As a result, early warning systems and

economic cycle forecasts become vital for the government

and business players alike.

In the construction of an Early Warning System (EWS)

model for the real estate and property industry in Indonesia

and to analyze the effects of the industry on

macroeconomic variables and financial stability, five criteria

are used, namely: Accurate, Anticipative, Comprehensive,

Flexible, and Kiwari (up to date). To achieve the goals set,

the model is constructed using Business Cycle Analysis.

This method was established by the National Bureau of

Economic Research (NBER) and is currently used in many

developed countries, especially OECD countries. In

Indonesia and other developing countries, this method is

rarely used due to data limitations.

In business cycle analysis there are three types of

composite index and 1 reference series. Each composite

index is a combination of a few variables. The three indices

are leading, coincident and lagging indices. The Reference

Series is a variable that illustrates the aggregate economic

paint, steel, timber/wood/logs), transportation, and other

related sectors. Literature Studies in numerous countries

(such as Nathakumaran et al (1996), Key et al (1994),

Wood and Williams (1992), Newell and Higgins (1996),

Krystalogianni et al (2004) and Everhart and Duva-

Hernandez (2001)) also show that the real estate and

property industry is a key indicator of economic

robustness.

The performance of the real estate and property

industry can also be considered as a signal to the financial

sector, particularly the banking sector. Experience in the

past has shown that pressure on the real estate and

property industry can trigger a crisis, as evident from the

US savings and loans crisis at the end of 1980s, the Swedish

and Japanese financial crises in the early 1990s and the

US subprime mortgage crisis which persists to this day.

This is in line with research conducted by Koehler (2001),

Carson (2001), Van den Bergh (2001) and Zhu (2003).

Observing the close correlation between the role of

the real estate and property industry on the economy as a

whole and financial system stability in particular, it is

imperative to continually review the behavior of the

property sector. In this context this research aims to:

(i) Construct an economic model that can be used as

an early warning system for the negative impacts of

real estate and property sector growth on financial

system stability,

(ii) Investigate the financing behavior of business players

in the real estate and property industry (developers,

banks and buyers),

(iii) Explore the expectations of business players in the

real estate and property industry as well as the

industry»s future prospects.

To achieve the goals of this study, the research is

split in two stages. Stage one includes constructing a model

that can be used as an Early Warning System (EWS) for

real estate and property industry growth. Only with a sound

71


conditions to be reviewed, which in this case are indicators

of the real estate and property sector. The leading index

moves ahead of the coincident and reference series. The

coincident index moves in correlation with the reference

series. And the lagging index moves behind (lag) the

coincident and reference series.

The leading index is the focus of attention because

it can provide an early warning system regarding the

direction of aggregate economic movement. The

coincident index can illustrate the current economic

situation and the lagging index confirms the movements

of the previous two indices.

This study uses three alternative reference series closely

related to the real estate and property industry, namely:

Alternative 1: banking indicators including property

credit and property NPL;

Alternative 2: Value-added construction measured

against the GDP of the construction sector; and

Alternative 3: Absorption level measured by the level

of occupancy/sales or rental/sale price index (for

commercial property) and the selling price index or

level of sales (for residential property).

An alternative to the third reference series is not used

due to the change in price definition in 2002. As a result,

the available series is very short and fails to qualify. Of the

two available alternatives, an early warning system is then

developed to detect the behavior of reference series in

the upcoming prediction period of 3, 6 and 12 months.

EWS development in the 3 periods is not merely based on

the accuracy of analysis results, but it also considers room

for the policy-maker, especially in the process of

formulating and determining policy.

Using data from 1996 √ August 2006, study results

show that the EWS model developed could

comprehensively explain the behavior of construction GDP,

property credit and property NPL in all prediction periods

(3, 6 and 12 months). To summarize, the analysis results

of the business cycle can be presented as follows:

Property NPLProperty NPLProperty NPLProperty NPLProperty NPL: The results show a declining trend of

property NPL in the upcoming 3 and 6-month periods (end

of 2006 √ March 2007). This is in line with NPL data (out

of sample); however in the upcoming 12 months (August

2007), NPL indicated a rise. This is also in line with abundant

press coverage in various media that also show a similar

trend.

The primary variable used to formulate the leading

index of property NPL is electricity consumption and the

consumer price index (for the upcoming 3-month period),

and 1-month SBI (for the upcoming 6 and 12-month

periods). Electricity consumption has a negative correlation,

which implies that high electricity consumption will be

followed by lower property NPL. In contrast, the consumer

price index and 1-month SBI correlate positively, which

indicates that high consumer prices and 1-month SBI will

trigger a surge in NPL in the following 6 and 12 months.

Property CreditProperty CreditProperty CreditProperty CreditProperty Credit: The model shows that property credit

in the subsequent 3, 6 and 12-month periods (November

2006 √ August 2007) is projected to experience growth.

This is consistent with the latest property credit data and

the prevailing expectations of business players in the

property sector.

A more thorough analysis shows that the primary

variables of the leading index for property credit are: the

inventory of rented offices, inventory of luxury hotels and

the apartment occupancy level. The inventory of rented

apartments and the occupancy level of rented apartments

positively correlate to property credit. Therefore, higher

levels of these indicators will be followed by a rising trend

in credit. In contrast, the inventory of luxury hotels

negatively correlates to property credit, so that a low

inventory of luxury hotels would indicate a rise in property

credit in the subsequent period.

GDP of the Construction SectorGDP of the Construction SectorGDP of the Construction SectorGDP of the Construction SectorGDP of the Construction Sector: Similar to the

previous two models, the early warning system for

72


construction GDP also convincingly projected GDP

movements for the subsequent 3, 6 and 12-month periods.

The model indicates GDP growth in the upcoming 3, 6

and 12-month periods (November 2006 √ August 2007).

Unfortunately, these results are still awaiting confirmation

from actual GDP data, which has yet to be published.

However, the results do match prevailing opinion of the

business players and property experts.

Further analysis reveals that the key variables for EWS

of construction GDP are the 1-month SBI rate, retail

occupancy level, and real investment approval for hotels.

The 1-month SBI rate negatively correlates to construction

GDP, therefore, a low 1-month SBI rate will be followed

by high economic activity in the property sector. On the

contrary, a high retail occupancy level and high real

investment approval for hotels will precipitate intense

activity in the property sector.

To study the effect of the property sector on the

economy in general and also financial system stability, the

variable of property NPL will be analyzed both as a leading

indicator and with regards to coincident and lagging

indicators. Property NPL itself is the primary component that

makes up the leading index for property credit with a

negative correlation. This translates to the backward-looking

tendency of banks; therefore, high NPL tends to be followed

by low property credit. The coincident index shows that

NPL movement correlates to other economic indicators such

as electricity consumption, exports, real exchange rate, sales

level of industrial areas as well as the occupancy level and

inventory of rented apartments. Property NPL behavior is

followed by property credit, M1 and net foreign assets.

3. FINANCING BEHAVIOR AND THE

EXPECTATIONS OF PROPERTY INDUSTRY

PLAYERS

In order to understand financing behavior and the

expectations of property industry players, a survey is

conducted to identify future financing behavior and player

expectations, which comprise of developers, banks and

buyers. The survey is performed in 10 cities in Indonesia:

Jakarta, Bogor, Depok, Tangerang, Bekasi, Yogyakarta,

Medan, Palembang, Makasar and Balikpapan. Sample

Location Selection is conducted through Shift-share

Analysis (SSA) and Location Quotient (LQ).

SSA is an analysis method to measure whether a

sector in a certain region outperforms the average of other

regions or the national average. LQ is used to identify the

basis sectors in a region. A sector is categorized as a basis

sector if its LQ coefficient > 1. On the contrary, if the LQ

coefficient < 1 then it is not a basis sector. A region is

selected as a sample if in that region, the property sector

(construction) is the basis sector that supports the local

economy and outperforms other regions nationally.

Survey results for developers, buyers and banks are

as follows:

Developers:Developers:Developers:Developers:Developers: For small and subsidized housing

developers, the pre-selling method is preferable to post-

selling. With pre-selling, the developer has assured buyers

as well as supplementary capital. In contrast, despite having

to indent for 2-6 months, buyers are also satisfied as the

house selling price can be cheaper which suits their

financial situation. The larger the house to be purchased,

the more favorable the post-selling method becomes. In

addition, the tendency to use self-financing is bigger.

Graph A1.1Residential Property Selling Method

0

10

20

30

40

50

60

70

64

36

57

43

52

48

51

49

%

Pre selling Post selling

Small typesubsidi

Small typenon subsidi

Middle type Big type

73


be tightly related to credit application are interest rates,

income level and down payments.

Graph A1.2Commercial Property Selling Method

0

10

20

30

40

50

60

70

Apartemen Perkantoran Pertokoan

37

63

42

58 54

46

Pre Selling Post Selling

%

From a source of financing viewpoint, the largest

portion used by developers originates from self financing.

This is related to cost of clearing and preparing the land

until it is ready for construction that has to be borne by

the developers themselves. Other funds come for down

payments, bank loans and non-bank loans. The factors

that significantly affect the developers» decision to seek a

bank loan are: the interest rate, property prices, building

material prices, occupancy levels and property demand.

Graph A1.3Source of Financing

0,00

10,00

20,00

30,00

40,00

50,00

60,00

70,00

1 2 3 4 5 6 7

1. Modal sendiri 2. Uang muka penjualan 3. Pinjaman Bank 4. Pinjaman lembaga non Bank

Graph A1.4Residential Property Financing

Self FundingSelf Funding and Bank

BankSelf Funding and Non BankNon BankSelf Funding, Bank and Non Bank

38.3

46.9

8.64.9 0.6 0.6

Buyers:Buyers:Buyers:Buyers:Buyers: One of the interesting findings of this study

is that the majority of residential buyers (about 40%)

purchase property using self financing due to several

reasons: (i) do not wish to be burdened by debt; (ii)

complicated bank procedures; and (iii) have sufficient

funds. The larger the property to be purchased, the more

substantial the portion of self financing used; however,

bank funds still dominate overall. The factors believed to

Graph A1.5Commercial Property Financing

Self FundingSelf Funding and Bank

BankingSelf Funding and Non Bank

Non Bank Fund

75%

15%

4%5% 1%

Many commercial property buyers (apartments and

shops) use self financing since their purchasing power is,

on average, relatively strong. Meanwhile, most property

is sold through post-selling. With this method of selling,

buyers are assured of a specific location as well as building

style and quality.

Graph A1.6Commercial Property Selling Method

0

20

40

60

80

Apartemen Perkantoran Pertokoan

Pre Selling Post Selling

37

63

21

79

24

76

%

74


Banks: Banks: Banks: Banks: Banks: Factors influencing the amount of property

credit include: (i) property industry prospects; (ii) level of

property market absorption/demand; and (iii) macro,

security and political stability. Factors that affect the level

of property NPL include: (i) interest rate level; (ii) level of

public income; (iii) level of property absorption/demand;

and (iv) inflation.

In general, banks, buyers and developers have

acknowledged that conditions in the property sector in

Indonesia in 2007 are better than in 1999. In 1999, the

property sector was expanding after plummeting to its

nadir during the crisis. And in 2007 the sector continues

to strengthen. In addition, respondents have stated that

the lending rate for property credit is still too high, and

its ideal rate would be in the range of 8 √ 12%.

Respondents also opined that monthly installments,

reaching 30% of income, are still far too high. Around

10% would be a more acceptable percentage for monthly

installments.

4. CONCLUSION

An Early Warning System (EWS) for the real estate

and property industry was compiled using three reference

series: Property Credit, Property NPL and Construction

Sector GDP. The EWS built on those three reference series

could project up to the next 12 months with a high level

of accuracy. The results of business cycle analysis were

congruent with real conditions in the field as confirmed in

various media (national and international), as well as

findings from various surveys.

Interviews with market players showed that the

property industry is currently expanding, but the media

have reported a substantial number of empty commercial

properties, which has the potential to increase property

NPL. On the other hand, interview results with banks and

market players indicated that NPL and the interest rate

need to be carefully considered in the property business.

Therefore, monitoring credit risk exposure (especially in

the property sector) is vital in order to mitigate risk that

may be triggered by property NPL.

In order to develop a future Early Warning System

that supports financial system stability, it is necessary to

expand and complete the data as well as actively monitor

EWS related indicators, not only in the property sector,

but also for other sectors. This matter has been addressed

by developed countries that recently improved 19 types

of leading indicators to monitor future economic and

financial movements.

75


Akerlof, George. 1970. The Market for Lemons: Quality,

Uncertainty and the Market Mechanism. Quarterly

journal of Economics 84: 488-500.

Bernanke, Ben S. and Alan S. Blinder. 1988. Credit, Money,

And Aggregate Demand. National Bureau Of

Economic Research. Working Paper No. 2534.

Bussiere, M and Marcel F. 2002. Towards a New Early

Warning System of

Financial Crises. Working Paper European Central Bank

no. 145.

Greef , I.J.M. de and R.T.A. de Haas. 2000. Housing Prices,

Bank Lending, and Monetary Policy. Paper presented

at the Financial Structure, and Behaviour and

Monetary Policy inthe EMU Conference, October 5-

6, 2000, Groningen.

Kiyotaki, N and Moore J. 1997. Credits Cycles. Journal of

Political Economy, Vol. 105, pages 211-248

Krytalogianni, A., G. Matysiak, dan S. Tsolacos. 2004.

Forecasting UK Commercial Real Estate Cycle Phases

With Leading Indicators: A Probit approach. Applied

Economics.

Nanthakumaran, N., B. O»Roarty, and A. Orr. 1997. The

Impact of Economic Indicators on Industrial Property

Market Performance. Center for Property Research.

University of Aberdeen. UK.

References

Samuelson, P.A. 1976. Optimality of Sluggish Predictors

under Ergodic Probabilities. International Economic

Review 17:1-7.

Sims, C. 1980. Macroeconomics and Reality. Econometrica,

Vol. 48 page 1-48.

Siregar, Doli. 2002. Dasar-Dasar Penilaian Properti.

Stiglitz, J. E. 1992. Capital Markets and Economics

Fluctuations in Capital Economies. European

Economics Review. Vol. 36, pages 269-306.

Sugema, Iman. 2000. Indonesia»s Deep Economic Crisis:

The Role of the Banking Sector in It»s Origin and

Propagation, PhD thesis, The Australian National

University.

Whitley, J and Richard W. 2003. A Quantitative Framework

for Commercial Property and its Relationship to the

Analysis of Financial Stability of the Corporate Sector.

Bank of England Working Paper no. 207.

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Indicators of Business Cycle in Malaysia and the

Philippines. ERD Working Paper No. 32

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77

Article II - Household Balance Sheet Survey : Significant Indicators in Financial System Stability Surveillance

Article II

Household Balance Sheet Survey8 :Significant Indicators in Financial System Stability Surveillance

Wimboh Santoso9, Bagus Santoso10

A household survey was conducted to establish the structure of the general public»s household balance

sheet. The household balance sheet is an important indicator in terms of financial system stability surveillance. By

establishing the structure of the household balance sheet, it is expected that analyzing a household»s ability to

obtain bank credit and calculating the probability of default of the household sector can be measured more

accurately. Subsequently, a survey using the random sampling technique was undertaken of respondents in all

municipalities/cities in six locations: West Sumatera, West Java, Bodetabek, Central Java, D.I. Yogyakarta and

East Java. Survey results indicate that on average, households are capable of fulfilling their commitment to the

banks and non-bank financial institutions as reflected by the ratio of total liabilities to core income, the ratio of

bank liabilities to core income and the ratio of non-bank liabilities to core income, which were 19.98%, 14.42%,

and 5.56% respectively.

8 Summarized from survey results conducted through collaboration between the Direc-torate of Banking Research and Regulation and Bagus Santoso and Setiyono (GadjahMada University), Viverita (University of Indonesia), FX. Sugiyanto (Diponegoro Univer-sity), Niki Lukviarman (Andalas University), Maryunani (Brawijaya University) and NuryEffendi (Padjadjaran University)

9 Director of the Financial System Stability Bureau, Directorate of Banking Research andRegulation, Bank Indonesia, email address: [email protected]

10 Lecturer, Faculty of Economics, Gadjah Mada University, email address:[email protected]

I. BACKGROUND

As one of the units in an economic system,

households play an important role in the financial system.

In a financial system households can function as Investors/

Debtors (surplus units) as well as Creditors (deficit units)

as illustrated in Diagram 1. Therefore, pressure on the

household balance sheet has a potential to affect financial

system performance and vice versa. If this is not well

anticipated, risks may disrupt the financial system as a

whole. In this context, surveillance on the household sector

is crucial to measure and monitor potential risk.

In order to support household sector surveillance,

data availability is a prerequisite, particularly Household

Balance Sheet data which is currently incomplete. By

establishing the household balance sheet, it is expected

that risk analysis for the household sector can be performed

more precisely.

78


To establish the balance sheet, primary data is used

in the form of a field survey based on the random sampling

technique. Survey implementation covers the following

factors:

1. Survey respondents are households located in six

survey regions. A household is defined as a person or

a group of persons living within one physical building/

census for which their food and other living necessities

are jointly funded (Central Bureau of Statistics).

2. The choice and determination of the number of

research respondents in each municipality/city is

proportional to the number of residents in the

municipality/city. The proportion of respondents in

each municipality/city to the number of respondents

in a province is equal to the ratio of the number of

residents in each municipality/city to the number of

residents in the province. Moreover, the number of

respondents in each sub-district to the total

respondents in a municipality/city is equal to the ratio

of residents in each sub-district to total residents in

the municipality/city. The sample region was chosen

as it is a representative region that corresponds to

the survey methodology. In addition, the choice of

region was also determined by access availability to

the particular region.

3. Sampling is based on district/village.

III.2. Data

Data regarding the number of residents required to

estimate the total number of respondents, as well as the

names of the sub-district and village of the survey location

are obtained from the Provincial BPS Office, the

corresponding Municipal/City BPS Office and the regional

governments» websites. The residential data used is from

2004. The number of respondents in each province is 500,

therefore, the total number of respondents for the six

locations is 3,000.

II. OBJECTIVES

The objectives of the survey are as follows:

- To establish the structure of the public household

balance sheet in all municipalities/cities in six

locations to be used as the basis of analyzing a

household»s ability to obtain bank credit as well as

calculating the probability of default in the

household sector.

- To reinforce Bank Indonesia»s surveillance activities on

the household sector in Indonesia, especially in

relation to financial system stability.

III. METHODOLOGY AND DATA

III.1. Methodology

This survey is a quantitative study. The interview

process with respondents is performed face-to-face.

Through this survey a household balance sheet is created

in six locations: West Sumatera, West Java, Bodetabek,

Central Java, DIY, and East Java. Creating the household

balance sheet in this region represents an initial step in

Indonesia»s household balance sheet development

program. In its implementation, the choice of study

method to conduct the survey is at the discretion of the

surveyor through prior discussions with the host.

Graph A1.1Financial System Stability Analysis Framework

Household

Corporate

Macroeconomic

Financial Condition

Probabilityof Default

Probabilityof Default

Bank

Non BankFinancial

Institution

MoneyMarket

FinancialSystem

Infrastructure

Financial Performance

International and Domestic :- Economic Factor- Non Economic Factor

CapitalProfitability

CapitalProfitability

JSI, YieldCurve, InterbankMoney Market

FinancialSystemStability

- Intermediation- Transmission Mechanism

GrowthDomesticProduct

Inflation

Inflation Target

MonetaryStability

79


Jatim Snow Ball Purposive Sampling: 5 besarkontributor PDRB Jatim

DIY Secara umum tidak ada -penyesuaian, kec. untukdaerah-daerah yangterkena dampak gempa

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Bodetabek Snow Ball -Sumbar Pertimbangan anggaran Pertimbangan anggaran

Table A2.2Adjustments Made

Wilayah Kotamadya

Sumbar Padang, Bukittinggi Solok, Agam, Padang Pariaman

Jabar Bandung Bandung, Indramayu,

Karawang, Garut

Bodetabek Tangerang, Bogor, Tangerang, Bogor, Bekasi

Bekasi, Depok

Jateng Semarang, Surakarta, Kudus

Pekalongan, Magelang

DIY Yogyakarta Bantul, Kulonprogo

Sleman, Gunung Kidul

Jatim Malang, Pasuruan Malang, Pasuruan, Batu

Table A2.1Survey Region

Wilayah Kotamadya Kabupaten

1 Gaji & Tunjangan 1 Pangan2 Penghasilan usaha Netto 2 Pakaian3 Penerimaan Pensiun 3 Sewa rumah dan tanah4 Beasiswa/Ikatan Dinas 4 Peralatan rumah tangga

tahan lama5 Ganti Rugi Asuransi 5 Transportasi6 Hasil Menang Undian 6 Kendaraan, dan bahan

bakar7 Pendapatan Bunga 7 Listrik, air, dan

Piutang dan Bunga telekomunikasiTabungan

8 Hasil Netto Penjualan 8 PendidikanTanah

9 Hasil Netto Penjualan 9 KesehatanEmas

10 Hasil Netto Penjualan 10 Rekreasi dan PerhiasanKendaraan

11 Bantuan Pemerintah 11 Aneka barang dan jasaNon-Beasiswa

12 Bantuan Lembaga Non- 12 Pembayaran pokokPemerintah Non-Beasiswa pinjaman

13 Penerimaan Lainnya 13 Pembayaran bungacicilan.

Table A2.4Income and Expenditure

No Elemen Pendapatan No Elemen Pengeluaran

IV. ANALYSIS RESULTS

IV.1. Balance Sheet Analysis

In accordance with the survey»s objectives, the

structure of the Household Balance Sheet is formulated at

both the provincial and municipal levels from the data

available. Elements of the balance sheet procured from

the questionnaire are then grouped into ≈Assets∆ or

≈Liabilities and Equities∆ as follows:

Table A2.3Assets and Liabilities

From the questionnaire, elements of household

income and expenditure are compiled as follows:

1 Kas 1 Utang Bank2 Tabungan 2 Utang Koperasi3 Deposito 3 Utang Pegadaian4 Giro 4 Utang Toko/Dealer5 Tabungan Asuransi 5 Uang Warung6 Tabungan Koperasi 6 Utang Pemilik Rumah/

Tanah7 Tabungan Kantor Pos 7 Utang Saudara8 Piutang 8 Utang Majikan9 Saham 9 Utang Arisan/Teman10 Obligasi 10 Utang Pelepas Uang11 Reksadana 11 Utang Lainnya12 Dana Pensiun13 Bapertarum14 Penyertaan modal usaha15 Ternak16 Emas17 Kendaraan18 Rumah19 Bangunan20 Tanah21 Harta Lainnya

No Elemen Aktiva No Elemen Pasiva

80


Prior to the elements being arranged into a Balance

Sheet, they are classified based on a prediction of their

usefulness. Since the Household Balance Sheet data will

be used to maintain Financial System Stability, the assets

are grouped according to their liquidity, whereas liabilities

are grouped according to their source of funds, namely

Banks and Non-bank Financial Institutions (NBFI).

From the survey results and based on element

grouping contained in the financial report, the structure

of the household balance sheet is calculated. This

household balance sheet structure is calculated per resident

(total balance sheet elements divided by the number of

samples per location), and presented as follows:

1. West Sumatera

Aktiva Lancar

Investasi

Aktiva Tetap

Total AktivaUtang BankUtang LKNBUtang Lain-lain

Total UtangKekayaan BersihPendapatan

Total Pendapatan

Konsumsi

Total Cicilan + Bunga

Pembayaran BungaPendapatan Bersih

Table A2.5Definition of Variables

Variabel Definisi

Kas + Tabungan + Deposito + Giro +Tabungan Asuransi + Tabungan Koperasi +Tabungan Kantor Pos + Piutang +Saham + Obligasi + ReksadanaDana Pensiun+Bapertarum+Penyertaanmodal usaha+TernakEmas + Kendaraan + Rumah + Bangunan +Tanah + Harta LainnyaAktiva Lancar + Aktiva Tetap + InvestasiUtang BankUtang Koperasi + Utang PegadaianUtang Toko/Dealer+Uang Warung+UtangPemilik Rumah/Tanah+Utang Saudara+UtangMajikan+Utang Arisan/Teman+UtangPelepas Uang+Utang LainnyaUtang Bank + Utang LKNB + Utang Lain-lainTotal Aset - Total UtangGaji & Tunjangan + Penghasilan usaha Netto+ Penerimaan PensiunGaji dan Tunjangan + Pendapatan UsahaNetto + Penerimaan Pensiun + Beasiswa/Ikatan Dinas + Ganti Rugi Asuransi + HasilMenang Undian + Pendapatan BungaPiutang dan Bunga Tabungan + Hasil NettoPenjualan Tanah + Hasil Netto PenjualanEmas dan Perhiasan + Hasil Netto PenjualanKendaraan + Bantuan Pemerintah Non-Beasiswa + Bantuan Lembaga Non-Pemerintah Non-Beasiswa + PenerimaanLainnyaPangan+Pakaian+Sewa rumah dantanah+Peralatan rumah tangga tahanlama+Transportasi, kendaraan, dan bahanbakar+Listrik, air, dantelekomunikasi + Pendidikan + Kesehatan +Rekreasi + Aneka barang dan jasaPembayaran pokok pinjaman + Pembayaranbunga cicilanPembayaran bunga cicilanPendapatan √ Konsumsi

Average Asset ( Rp ) Average Liabilities ( Rp )

Current Assets :Current Assets :Current Assets :Current Assets :Current Assets : Household Debt: BanksHousehold Debt: BanksHousehold Debt: BanksHousehold Debt: BanksHousehold Debt: Banks 4,758,8784,758,8784,758,8784,758,8784,758,878

Cash 2,172,157 Household Debt: Non BanksHousehold Debt: Non BanksHousehold Debt: Non BanksHousehold Debt: Non BanksHousehold Debt: Non Banks 899,858899,858899,858899,858899,858

Saving, Deposit and 14,107,812 Household Debt: Store/ 518,548

Checking Acc Dealer

Insurance, Cooperatives, 2,827,600 Household Debt: Kiosk 2,400

Post Office

Account receivable 5,905,440 Household Debt: Landlord 0

Stock, Bond, Mutual Fund 912,000 Household Debt: Relatives 81,200

Total Current AssetTotal Current AssetTotal Current AssetTotal Current AssetTotal Current Asset 25,925,01025,925,01025,925,01025,925,01025,925,010 Household Debt: Employer 800

InvestmentInvestmentInvestmentInvestmentInvestment 12,235,80412,235,80412,235,80412,235,80412,235,804 Household Debt: ROSCA/ 17,720

Friends

Fixed Assets :Fixed Assets :Fixed Assets :Fixed Assets :Fixed Assets : Household Debt: Money 4,000

Lender

Gold and Jewelry 6,440,278 Household Debt: Others 175,832

Vehicle 34,756,541 Total Others DebtTotal Others DebtTotal Others DebtTotal Others DebtTotal Others Debt 1,847,5811,847,5811,847,5811,847,5811,847,581

House and buildings 221,637,302 Total DebtTotal DebtTotal DebtTotal DebtTotal Debt 7,506,3187,506,3187,506,3187,506,3187,506,318

Land 50,354,506

Total Fixed AssetTotal Fixed AssetTotal Fixed AssetTotal Fixed AssetTotal Fixed Asset 313,188,627313,188,627313,188,627313,188,627313,188,627 Net WorthNet WorthNet WorthNet WorthNet Worth 346,874,202346,874,202346,874,202346,874,202346,874,202

Other AssetsOther AssetsOther AssetsOther AssetsOther Assets 3,031,0803,031,0803,031,0803,031,0803,031,080

Total AssetsTotal AssetsTotal AssetsTotal AssetsTotal Assets 354,380,520354,380,520354,380,520354,380,520354,380,520 Total Liabilities and EquityTotal Liabilities and EquityTotal Liabilities and EquityTotal Liabilities and EquityTotal Liabilities and Equity 354,380,520354,380,520354,380,520354,380,520354,380,520

The household balance sheet for residents of West

Sumatera is dominated by fixed assets with a share

of 88.38%. In terms of liquid assets, the largest

component is savings, term deposits and checking

accounts, which together make up 54.42% of total

liquid assets. Regarding liabilities the largest

component is net worth, namely 97.88% of total

liabilities. Concerning debt, households in West

Sumatera rely on the banking sector with a share of

63.40% of total debt. Meanwhile, the shares of debt

to non-bank financial institutions and other debts are

11.99% and 24.61%, respectively.

2. West Java

From the household balance sheet structure for

residents in West Java, fixed assets (particularly houses

81


Based on the household balance sheet structure for

Bodetabek, fixed assets (mainly houses and buildings)

are the largest component of total assets, constituting

88.31%. Liquid assets, investments and other assets

have shares of 8.04%, 3.11% and 0.54% respectively.

Relating to liquid assets, the largest components are

savings, term deposits and checking accounts with a

combined share of 66.95% of total liquid assets. As

regards liabilities, the largest component is capital (net

worth) with a 95.87% share of total liabilities. Aside

from private capital, households in Bodetabek rely

heavily on banks for their funding, accounting for

45.28% of total debt. The shares of debt to non-

bank financial institutions and other debts are

15.91% and 38.81% respectively.

4. D.I. Yogyakarta


Current Assets :Current Assets :Current Assets :Current Assets :Current Assets : Household Debt, BanksHousehold Debt, BanksHousehold Debt, BanksHousehold Debt, BanksHousehold Debt, Banks 8,748,3778,748,3778,748,3778,748,3778,748,377

Cash 1,152,812 Household Debt : NonHousehold Debt : NonHousehold Debt : NonHousehold Debt : NonHousehold Debt : Non 261,153261,153261,153261,153261,153

BanksBanksBanksBanksBanks

Saving, Deposit and 24,814,429 Household Debt : Store/ 1,276,500

Checking Acc Dealer

Insurance, Cooperatives, 2,400,146 Household Debt : Kiosk 200

Post Office

Account receivable 2,912,344 Household Debt : Landlord 38,400

Stock, Bond, Mutual Fund 5,040,000 Household Debt : Relatives 160,680

Total Current AssetTotal Current AssetTotal Current AssetTotal Current AssetTotal Current Asset 36,319,73236,319,73236,319,73236,319,73236,319,732 Household Debt : Employer 0

InvestmentInvestmentInvestmentInvestmentInvestment 6,625,1706,625,1706,625,1706,625,1706,625,170 Household Debt : ROSCA/ 12,000

Friends

Fixed Assets :Fixed Assets :Fixed Assets :Fixed Assets :Fixed Assets : Household Debt : Money 396

Lender

Gold and Jewelry 3,044,710 Household Debt : Others 126,200



Land 46,670,200




and buildings) are again the largest component of

total assets, with a share of 87%. Liquid assets,

investments and other assets have shares of 10%,

2% and 1% respectively. With respect to liquid assets,

the largest components are savings, term deposits

and checking accounts that together make up 68%

of total liquid assets. Meanwhile, referring to liabilities,

the largest component is net worth, with a share of

97% of total liabilities. Besides, the majority of

households in West Java still rely on banks for their

funding, which makes up 82% of total debt.

3. Bodetabek


Current Assets :Current Assets :Current Assets :Current Assets :Current Assets : Household Debt: BanksHousehold Debt: BanksHousehold Debt: BanksHousehold Debt: BanksHousehold Debt: Banks 5,436,3805,436,3805,436,3805,436,3805,436,380

Cash 918,553 Household Debt : NonHousehold Debt : NonHousehold Debt : NonHousehold Debt : NonHousehold Debt : Non 1,910,0741,910,0741,910,0741,910,0741,910,074



Checking Acc Dealer

Insurance, Cooperatives, 915,243 Household Debt : Kiosk 395

Post Office

Account receivable 5,558,247 Household Debt : Landlord 0

Stock, Bond, Mutual Fund 328,063 Household Debt : Relatives 470,593

Total Current AssetTotal Current AssetTotal Current AssetTotal Current AssetTotal Current Asset 23,357,73723,357,73723,357,73723,357,73723,357,737 Household Debt : Employer 31,621


Friends


Fixed Assets :Fixed Assets :Fixed Assets :Fixed Assets :Fixed Assets : Household Debt : Money 10,119

Lender

Gold and Jewelry 2,779,087 Household Debt : Others 2,084,163



Land 40,703,755





Current Assets :Current Assets :Current Assets :Current Assets :Current Assets : Household Debt : BanksHousehold Debt : BanksHousehold Debt : BanksHousehold Debt : BanksHousehold Debt : Banks 14,172,83314,172,83314,172,83314,172,83314,172,833

Cash 2,089,595 Household Debt : NonHousehold Debt : NonHousehold Debt : NonHousehold Debt : NonHousehold Debt : Non 1,506,0231,506,0231,506,0231,506,0231,506,023



Checking Acc Dealer

Insurance, Cooperatives, 2,597,860 Household Debt : Kiosk 6,250

Post Office

Account receivable 5,905,440 Household Debt : Landlord 22,639


Total Current AssetTotal Current AssetTotal Current AssetTotal Current AssetTotal Current Asset 24,520,98124,520,98124,520,98124,520,98124,520,981 Household Debt : Employer 11,905


Friends

Fixed Assets :Fixed Assets :Fixed Assets :Fixed Assets :Fixed Assets : Household Debt : Money 20,635

Lender




82


Based on the household balance sheet structure for

residents in Central Java, fixed assets (mainly houses

and buildings) are the largest component of total

assets, with a share of 94.28%. Liquid assets,

investments and other assets represent 5.08%,

0.41% and 0.23% respectively. In terms of liquid

assets, the largest components are savings, term

deposits and checking accounts with a share of 50%

of total liquid assets. Meanwhile, referring to liabilities,

nearly all household necessities are funded by private

capital (net worth) with a share of 98.11% of total

liabilities. Apart from private capital, households in

Central Java depend on banks for their funding,

amounting to 76.67 % of total debt. The shares of

debt to non-bank financial institutions and other

debts are 8.63% and 14.70% respectively.

6. East Java

From the household balance sheet structure for D.I.

Yogyakarta, fixed assets (mainly houses and buildings)

are again the largest component of total assets, with

an 89.42% share. Liquid assets, investments and

other assets account for 5.25%, 2.19% and 3.13%

respectively. With regards to liquid assets, the largest

components are savings, term deposits and checking

accounts totaling 56.19% of total liquid assets.

Meanwhile, concerning liabilities, the largest

component is capital (net worth) with a 96.24% share

of total liabilities. In addition to private capital,

households in D.I. Yogyakarta depend on banks for

their funding needs, making up 80.87% of total debt.

The shares of debt to non-bank financial institutions

and other debts are 8.59% and 10.54% respectively.

5. Central Java


Current Assets :Current Assets :Current Assets :Current Assets :Current Assets : Household Debt : BanksHousehold Debt : BanksHousehold Debt : BanksHousehold Debt : BanksHousehold Debt : Banks 5.386.9465.386.9465.386.9465.386.9465.386.946

Cash 2.343.074 Household Debt : NonHousehold Debt : NonHousehold Debt : NonHousehold Debt : NonHousehold Debt : Non 634.727634.727634.727634.727634.727


Saving, Deposit and 13.704.406 Household Debt : Store/ 1.308.552

Checking Acc Dealer

Insurance, Cooperatives, 1.458.087 Household Debt : Kiosk 0

Post Office

Account receivable 4.218.410 Household Debt : Landlord 0

Stock, Bond, Mutual Fund 1.940.200 Household Debt : Relatives 212.000

Total Current AssetTotal Current AssetTotal Current AssetTotal Current AssetTotal Current Asset 23.664.17723.664.17723.664.17723.664.17723.664.177 Household Debt : Employer 7.900

InvestmentInvestmentInvestmentInvestmentInvestment 5.805.5385.805.5385.805.5385.805.5385.805.538 Household Debt : ROSCA/ 58.286

Friends


Lender

Gold and Jewelry 4.126.520 Household Debt : Others 148.527

Vehicle 34.236.390 Total Others DebtTotal Others DebtTotal Others DebtTotal Others DebtTotal Others Debt 1.735.9651.735.9651.735.9651.735.9651.735.965

House and buildings 219.749.584 Total DebtTotal DebtTotal DebtTotal DebtTotal Debt 7.757.6377.757.6377.757.6377.757.6377.757.637

Land 78.583.960

Total Fixed AssetTotal Fixed AssetTotal Fixed AssetTotal Fixed AssetTotal Fixed Asset 336.696.454336.696.454336.696.454336.696.454336.696.454 Net WorthNet WorthNet WorthNet WorthNet Worth 361.758.772361.758.772361.758.772361.758.772361.758.772

Other AssetsOther AssetsOther AssetsOther AssetsOther Assets 3.350.2403.350.2403.350.2403.350.2403.350.240

Total AssetsTotal AssetsTotal AssetsTotal AssetsTotal Assets 369.516.409369.516.409369.516.409369.516.409369.516.409 Total Liabilities and EquityTotal Liabilities and EquityTotal Liabilities and EquityTotal Liabilities and EquityTotal Liabilities and Equity 369.516.409369.516.409369.516.409369.516.409369.516.409


Land 121,388,179





Current Assets :Current Assets :Current Assets :Current Assets :Current Assets : Household Debt : BanksHousehold Debt : BanksHousehold Debt : BanksHousehold Debt : BanksHousehold Debt : Banks 4,776,3124,776,3124,776,3124,776,3124,776,312

Cash 1,245,918 Household Debt : NonHousehold Debt : NonHousehold Debt : NonHousehold Debt : NonHousehold Debt : Non 537,350537,350537,350537,350537,350


Saving, Deposit and 8,311,627 Household Debt : Store/ 804,410

Checking Acc Dealer

Insurance, Cooperatives, 2,451,280 Household Debt : Kiosk 292

Post Office

Account receivable 3,840,979 Household Debt : Landlord 0


Total Current AssetTotal Current AssetTotal Current AssetTotal Current AssetTotal Current Asset 16,742,00416,742,00416,742,00416,742,00416,742,004 Household Debt : Employer 1200


Friends


Lender


Vehicle 28,022,390 Total Others DebtTotal Others DebtTotal Others DebtTotal Others DebtTotal Others Debt 915,772915,772915,772915,772915,772


Land 40,048,548


Other AssetsOther AssetsOther AssetsOther AssetsOther Assets 758,020758,020758,020758,020758,020


Taken from the household balance sheet structure

for East Java, fixed asset (mainly houses and buildings)

dominate total assets, with a share of 91.12%. Liquid

assets, investments and other assets make up 6.40%,

83


1.57% and 0.91% respectively. As regards liquid

assets, the largest components are savings, term

deposits and checking accounts with a share of

57.91% of total liquid assets. Concerning liabilities,

nearly all household necessities are self funded (net

worth) with a 97.90% share of total liabilities. In

addition to private capital, households in Central Java

rely on banks for their funding, representing 69.44%

of total debt. The shares of debt to non-bank financial

institution and other debts are 8.18% and 22.38%

respectively.

IV.2. Ratio Analysis

West Sumatera 2.12 28.95 18.36 2.40

West Java 2.84 29.25 24.09 3.26

Bodetabek 4.13 51.40 23.27 4.68

Central Java 1.89 37.21 28.53 2.01

DIY 3.76 71.48 57.80 4.20

East Java 2.10 32.78 22.76 2.30

LocationR a t i o

Total Liabilities/Total Asset Total Liabilities/Current Asset Total Bank Liabilities/Current Asset Total Bank Liabilities/Fixed Asset(%) (%) (%) (%)

• Total Liabilities/Total Asset Ratio Analysis

This ratio shows the ability of total assets to cover

household liabilities. If this ratio is less than 1 (= 100%)

then the household»s liabilities are smaller than its total

assets. Put another way, the household can still apply

for a larger loan. Based on the survey it can be seen

that all households in the survey area could apply for a

larger loan. Households in Bodetabek have the highest

ratio, whereas those in Central Java have the lowest.

Total Bank Liabilities/Current Asset Ratio Analysis

This ratio reveals the ability of liquid assets to cover

household liabilities. Should this ratio be less than 1

(= 100%) then the household»s liabilities are smaller

than its liquid assets. This means that the household

can still apply for a larger loan. The survey results

show that all households in the survey area could still

apply for another loan. Households in D.I. Yogyakarta

have the highest ratio, whereas those in West

Sumatera have the lowest.

Total Bank Liabilities/Fixed Asset Ratio Analysis

This ratio demonstrates the ability of fixed assets to

cover household liabilities. If this ratio is less than 1 (=

100%) then the household»s liabilities are smaller than

its assets. Therefore, the household can still apply for

a larger loan. From the survey it can be seen that all

households in the survey area could still apply for a

larger loan. Households in Bodetabek have the highest

ratio, whereas those in Central Java have the lowest.

Total Liabilities/Core Income Ratio Analysis

This ratio shows the ability of a household»s primary

income to cover its liabilities. Survey results indicate

that all households in the survey area could apply for

a loan.

Bank Liabilities/Core Income Ratio Analysis

This ratio denotes the ability of household»s primary

income to cover its liabilities to the bank. Survey results

show that households in D.I. Yogyakarta and Central

Java have a greater ratio than households in other

areas.

Non-Bank Liabilities/Core Income Ratio Analysis

This ratio demonstrates the ability of a household»s

income to cover its liabilities to non-bank financial

institutions (such as cooperatives or other

84


microfinance institutions as well as pawnshops).

Survey results evidence that households in West Java

have the highest income ability to cover non-bank

liabilities compared to households in other areas.

Meanwhile, households in Bodetabek have the lowest

ability to cover non-bank liabilities in terms of income

compared to households in other areas.

Interest Payment/Core Income Ratio Analysis

This ratio reveals the proportion of household»s

primary income used to repay interest on a loan. The

survey shows that among households in all sample

locations, households in West Java have the smallest

proportion of interest repayment liability. In other

words, households in West Java have the best income

ability to cover the interest on loans. Meanwhile, with

the largest proportion of loan interest repayment

liabilities, households in DIY have the lowest income

ability to cover such liabilities.

(Total Installment + Interest Payment) / Total Income

Ratio Analysis

This ratio indicates the proportion of a household»s

primary income used to pay the initial loan and its

interest. Survey results show that among households

in all survey locations, those in West Java have the

smallest proportion of loan installment repayment

liabilities (4.816%). In other words, households in

West Java have the best income ability to cover loan

installments. Meanwhile, households in Bodetabek

have the largest proportion of loan installment

repayment liabilities, with a ratio of 22.485%.

Consequently, households in Bodetabek have the

lowest income ability to cover loan installments.

(Total Installment + Interest Payment) / Current Asset

Ratio Analysis

This ratio shows the ability of liquid assets to cover

loan installments (principal and interest). Survey

results show that among households in all survey

locations, households in West Java have the smallest

loan installment repayment liabilities (9.950%).

Therefore, households in West Java have the best

income ability to cover loan installments. Meanwhile,

the largest proportion of loan installment repayment

West Sumatera 5.53 13.95 -

West Java 4.82 9.95 3.14

Bodetabek 22.49 82.25 1.40

Central Java 10.89 20.17 -

DIY 12.58 35.11 1.64

East Java 10.92 26.76 11.46

LocationR a t i o

(Total Installment + Interest Payment)/ (Total Installment + Interest Payment)/ Collateral / Agreed Bank LoanTotal Income (%) Current Asset (%)

West Sumatera 13.02 8.25 4.76 1.73

West Java 18.59 15.31 3.28 0.38

Bodetabek 15.54 7.03 8.50 1.90

Central Java 25.33 19.42 5.91 1.44

DIY 31.47 25.45 6.02 10.08

East Java 15.94 11.07 4.87 2.66

LocationR a t i o

Total Liabilities/Core Income Bank Liabilities/Core Income Total Non-Bank Liabilities/Core Income Interest Payment/Core Income(%) (%) (%) (%)

85


liabilities belongs to households in Bodetabek with

a ratio of 82.253%. As a result, households in

Bodetabek have the lowest income ability to cover

loan installments.

Collateral/Agreed Bank Loan Ratio Analysis

This ratio reveals the amount of credit approved

compared to the collateral value. Should this ratio be

less than 1 then the approved loan is higher than the

collateral value. The limit for this ratio is 1.25.

Exceeding the limit shows that such a province has

the potential to apply for a larger loan. Survey results

confirm that households in West Java, Bodetabek,

D.I. Yogyakarta and East Java have the potential to

apply for larger loans compared to their current ones.

VI. CONCLUSION

The Household Balance Sheet Survey was conducted

in six locations, namely West Sumatera, West Java,

Bodetabek, Central Java, D.I. Yogyakarta and East Java.

The survey successfully composed a household balance

sheet as of November 2007 at both the provincial and

municipal levels. The Household Balance Sheet structure

in DIY comprises of current assets, investments and fixed

assets on the assets side and bank debt, non-bank financial

institution debt, other debts and net worth on the liabilities

side (liabilities and equities). From its composition, the

assets» side of the household balance sheet is dominated

by fixed assets (particularly assets in the form of houses

and buildings), whereas on the liabilities side, debt is

dominated by bank debt, which makes up 69.67% on

average of total debt.

Generally, households throughout the survey location

have the potential to apply for larger loans. This is

evidenced by the ratio of total liabilities/total assets, total

liabilities/current assets, total bank liabilities/current assets,

and total bank liabilities/fixed asset. Survey results also

confirm that based on primary income, all households in

the survey location are able to meet their liabilities to both

banks and non-bank financial institutions. This is reflected

by the ratio of total liabilities/core income, bank liabilities/

core income and non-bank liabilities/core income.

Meanwhile, referring to total income and liquid assets,

households in the six survey locations are able to meet

their repayments of the principal loan and its interest. This

is demonstrated by the ratio of (total installment + interest

payment) / current asset.

86


Penelitian dan Pengembangan Ekonomi Universitas Gadjah

Mada, 2007. Laporan Akhir Household Balance Sheet

Survey Daerah Istimewa Yogyakarta 2007

Pusat Kajian Dinamika Sistem Pembangunan Universitas

Brawijaya, 2007. Laporan Akhir Survei Neraca Rumah

Tangga Propinsi Jawa Timur 2007

Center for Banking Research Universitas Andalas, 2007.

Laporan Pelaksanaan Survey Neraca Rumah Tangga

2007 di Sumatera Barat

Laboratorium Studi Kebijakan Ekonomi Universitas

Diponegoro, 2007. Laporan Akhir Survei Household

Balance Sheet Wilayah Jawa Tengah Tahun 2007

Laboratorium Penelitian, Pengabdian Pada Masyarakat dan

Pengkajian Ekonomi Universitas Padjajaran, 2007.

Laporan Akhir Survei Household Balance Sheet

References

Laboratorium Studi Manajemen Universitas Indonesia,

2007. Survey Neraca Rumah Tangga Bank Indonesia:

Analisis Temuan

Lee, Kevin and Paul Mizen (2005), ≈Household Credit and

Probability Forecast of Financial Distress in the United

Kingdom∆

Rinaldi, Laura and Alicia Sanchis Arellano (2006),

≈Household Debt Sustainability: What Explains

Household Non Performing Loan? An Empirical

Analysis, Working Paper no.570, European Central

Bank, January 2006.

87

Glossary

Glossary

88

Glossary


89

Glossary

Bank Indonesia Real Time Gross Settlement (BI-RTGS):Bank Indonesia Real Time Gross Settlement (BI-RTGS):Bank Indonesia Real Time Gross Settlement (BI-RTGS):Bank Indonesia Real Time Gross Settlement (BI-RTGS):Bank Indonesia Real Time Gross Settlement (BI-RTGS):

Electronic transaction settlement in real time where

accounts are debited and credited multiple times per day.

Business continuity management:Business continuity management:Business continuity management:Business continuity management:Business continuity management: Risk management to

ensure critical functions during disruptions as well as having

an effective recovery process.

Capital Adequacy Ratio (CAR): Capital Adequacy Ratio (CAR): Capital Adequacy Ratio (CAR): Capital Adequacy Ratio (CAR): Capital Adequacy Ratio (CAR): The ratio of a bank»s total

regulatory capital to its risk-weighted assets.

Credit risk: Credit risk: Credit risk: Credit risk: Credit risk: the risk of loss due to a debtor»s possibility of

default, or non-payment of a loan.

Crisis Management Protocol (CMP):Crisis Management Protocol (CMP):Crisis Management Protocol (CMP):Crisis Management Protocol (CMP):Crisis Management Protocol (CMP): A framework that

details the measures, roles and responsibilities of the

relevant authorities in handling a crisis to minimize the

resultant economic losses.

Exchange Traded Fund (ETF):Exchange Traded Fund (ETF):Exchange Traded Fund (ETF):Exchange Traded Fund (ETF):Exchange Traded Fund (ETF): A type of mutual fund with

characteristics similar to open-end companies where the

unit is traded like a stock on an ecchange. ETF consist of a

combination of open-end and closed-end funds.

Failure to settle: Failure to settle: Failure to settle: Failure to settle: Failure to settle: a mechanism which obliges participants

of the clearing system to provide a pre-fund to anticipate

liabilities emerging at the end of the day.

Financial Deepening: Financial Deepening: Financial Deepening: Financial Deepening: Financial Deepening: the development of the financial

sector; the increased provision of financial services with a

wider choice of services geared to all levels of society.

Financial Sector Assessment Program: Financial Sector Assessment Program: Financial Sector Assessment Program: Financial Sector Assessment Program: Financial Sector Assessment Program: a joint program by

the IMF and World Bank to assess the resilience of a

country»s financial system and its adherence to international

standards.

Financial Safety Net: Financial Safety Net: Financial Safety Net: Financial Safety Net: Financial Safety Net: framework to strengthen financial

system stability through four key elements: i) bank

regulation and supervision; ii) lender of last resort; iii)

deposit insurance; and iv) crisis management.

Financial system stability: Financial system stability: Financial system stability: Financial system stability: Financial system stability: refers to a state in which a

financial system, consisting of financial institutions and

markets, functions properly. In addition, the participants,

such as firms and individuals, have confidence in the

system.Ω

Flight to safety: Flight to safety: Flight to safety: Flight to safety: Flight to safety: switching funds from banks considered

less safe to safer banks.

Four-eyes principle: Four-eyes principle: Four-eyes principle: Four-eyes principle: Four-eyes principle: credit approval considering business

prospects and risk management.

Lender of last resort: Lender of last resort: Lender of last resort: Lender of last resort: Lender of last resort: the function of a central bank in

extending credit to banks to overcome liquidity problems

caused by a mismatch in funds and to prevent systemic

crisis.

Liquidity Risk:Liquidity Risk:Liquidity Risk:Liquidity Risk:Liquidity Risk: risk that an institution will not be able to

execute a transaction at the prevailing market price because

there is, temporarily, no appetite for the deal on the other

side of the market.

Mark to market: Mark to market: Mark to market: Mark to market: Mark to market: Evaluating the price or value of a security,

portfolio, or account on a daily basis, to calculate profits

and losses or to confirm that margin requirements are being

met.

Market risk: Market risk: Market risk: Market risk: Market risk: the risk that the value of an investment will

decrease due to the movements in market factors.

Glossary

90

Glossary

Non-performing loans (NPL): Non-performing loans (NPL): Non-performing loans (NPL): Non-performing loans (NPL): Non-performing loans (NPL): a loan that is in default or

close to being in default categorised as sub-standard (SS),

doubtful (D) and loss (L)

Operational risk: Operational risk: Operational risk: Operational risk: Operational risk: the risk of loss resulting from inadequate

or failed internal processes, people and systems, or from

external events.

Profit taking: Profit taking: Profit taking: Profit taking: Profit taking: the selling of assets or securities by investors

at a high price to receive profit.

Redemption:Redemption:Redemption:Redemption:Redemption: selling of a bond before maturity.

Regulatory capital: Regulatory capital: Regulatory capital: Regulatory capital: Regulatory capital: the minimum capital required applied

to banks set by the regulator.

Risk-control system: Risk-control system: Risk-control system: Risk-control system: Risk-control system: is a system to control risk implemented

through bank policy and procedure in line with sound risk

management principles.

Risk-free assets: Risk-free assets: Risk-free assets: Risk-free assets: Risk-free assets: an asset whose future return is known

with certainty. However, such assets remain subject to

inflation risk.

Risk mitigation: Risk mitigation: Risk mitigation: Risk mitigation: Risk mitigation: efforts to reduce the possibility and effects

of risk.

Restructuring: Restructuring: Restructuring: Restructuring: Restructuring: the act of improving loan conditions by

applying several options: i) adjusting the covenants to

provide additional financing; ii) converting all or partial

interest as new loans; iii) converting all or part of the loan

as equity for the bank in the company with or without

rescheduling or reconditioning.

Subprime mortgage: Subprime mortgage: Subprime mortgage: Subprime mortgage: Subprime mortgage: a type of mortgage made out to

borrowers with low credits ratings. As a result interest on

subprime mortgagesΩis often charged at a higher rate than

a conventional mortgage in order to compensate for

carrying more risk.

Sudden reversal: Sudden reversal: Sudden reversal: Sudden reversal: Sudden reversal: sudden capital outflows.

Systemically Important Payment Systems: Systemically Important Payment Systems: Systemically Important Payment Systems: Systemically Important Payment Systems: Systemically Important Payment Systems: are those that,

in terms of the size or nature of the payments processed

via them, represent a channel in which shocks could

threaten the stability of the entire financial system.

Stress testing: Stress testing: Stress testing: Stress testing: Stress testing: is a simulation technique used on asset

and liability portfolios to determine their sensitivities to

different financial situations. Stress-testing is a useful

method of determining how a portfolio will fare during a

period of financial crisis.

Undisbursed Loans: Undisbursed Loans: Undisbursed Loans: Undisbursed Loans: Undisbursed Loans: are loans that have been agreed but

are yet to be withdrawn.

Volatility: Volatility: Volatility: Volatility: Volatility: is the relative rate at which the price of a security

moves up and down. Volatility is found by calculating the

annualized standard deviation of daily change in price. If

the prices of securities move up and down rapidly over

short time periods, it has high volatility. If the price almost

never changes, it has low volatility.

Yield:Yield:Yield:Yield:Yield: The rate of income generated from a stock in the

form of dividends, or the effective rate of interest paid on

a bond, calculated by the coupon rate divided by the bond»s

market price. Furthermore, for any investment, yield is the

annual rate of return expressed as a percentage.

DIRECTOR

Halim Alamsyah Wimboh Santoso

COORDINATOR & EDITOR

Agusman

WRITER

Ardiansyah, Linda Maulidina, Ratih A. Sekaryuni, Pipih Dewi Purusitawati, Wini Purwanti,

Endang Kurnia Saputra, Ita Rulina, Ricky Satria, Fernando R. B, Noviati, Cicilia A. Harun,

Sagita Rachmanira, Reska Prasetya, Elis Deriantino, Primitiva Febriarti, Hero Wonida,

Mestika Widantri, Heny S.

COMPILATOR, LAYOUT & PRODUCTION

Ita Rulina Ricky Satria Primitiva Febriarti

CONTRIBUTOR

Directorate of Bank Supervision 1



Directorate of Sharia Banking

Directorate of Credit, Rural Bank Supervision and SMEs

Directorate of Banking Investigation and Mediation

Directorate of Bank Licensing and Banking Information

Directorate of Accounting and Payment System

Directorate of Economic Research and Monetary Policy

Directorate of Monetary Management

Directorate of Reserve Management

DATA SUPPORT

Suharso I Made Yogi Tita Hapsari

Financial Stability ReviewNo. 10, March 2008

Bank Indonesia, Financial Stability Review No.10, March 2008

Documents

Transcript of Bank Indonesia, Financial Stability Review No.10, March 2008