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An Analysis of the Quality of

the financial institutions in ThailandPresent at the Bank of Thailand,

29 May 2015

The views expressed in this presentation are the views of the author and do not necessarily reflect the views or policies of the Asian Development Bank Institute (ADBI), the Asian Development Bank (ADB), its Board of Directors, or the governments they represent. ADBI does not guarantee the accuracy of the data included in this paper and accepts no responsibility for any consequences of their use. Terminology used may not necessarily be consistent with ADB official terms.

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Background of the financial institutions in Thailand

• Cause of 97 crisis:

FX overvaluation, weakness in the financial system

• Measures after crisis:

1. Restore stability to the financial system

(e.g. closure, recap, debt restructure, consolidation)

2. Dramatic internal reforms to realign with new risk based supervisory

framework

• Key improvement of financial landscape over the decade:

1. Financial Sector Master plan I (2005-2008) and II (2010-2014)

(promote competency driven, modification of prudential guideline, improve

financial service & competition, universal banking, improve financial access)

2. Reform to improve surveillance procedure for specialized financial institutions

(SFIs) in 2015

Deposit taking institutions in Thailand and supervision structure

Supervision Type of deposit taking

institutions4/

Scope Objective Deposit insuranc

e premium

Stability NPL Market share

Supervised by Bank of Thailand1/

1.Commercial bank1.1 local1.2 subsidiaries1.3 retail banks1.4 foreign bank branches

-Commercial banking business-Capital market, FX, derivative (for 1.1 and 1.2 only)

Profit max. Pay 0.47% of deposit base

Good Low Large

2. Finance companies

-Accept deposit and grant credit only

Good Low Small

3. Credit foncier companies

-Accept deposit and grant mortgage loan, purchase immovable property

Good Low Small

Supervised by MOF (examined by BOT) 2/

4. Specialized Financial institutions (SFI)

Support financial access +Profit max.

No contribution3/.

Good but subject to Government intervention

High for I-bank and SME bank

Medium, Growing rapidly

Note: 1/ Non deposit taking institutions under BOT supervision are foreign financial institution representative office, asset management companies, non-bank (credit card company, personal loan company), e-payment. 2/ Non deposit taking institutions under MOF supervision are Thai asset management company, national credit bureau.

BOT will supervise this group in early 2016.3/ Under the new Act for specialized financial institution development fund (on 20 Mar 2015), SFI will need to contribute the deposit insurance premiumto the SFI fund to reduce an unfair competition. The MOF is considering the method of collection and the premium rate.4/ Other types of deposit taking institutions are savings cooperative and credit union, supervised by Ministry of Agriculture and Cooperatives, with thescope of managing funds contributed by members and grant loan to members who need credits. The objective is to provide financial service among

members. 3

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The Thai financial market is mainly bank based.

Bank of Thailand; 15.3

Commercial bank; 40.8

SFIs; 12.3

Saving cooperative and credit union; 4.9

Money market mutual fund; 0.8

Non-depository corporation; 25.9

% of total assets of financial institutions, end 2013

The commercial bank and the specialized government credit institution (SFIs) are the two most important depository institutions for Thailand.

Source: Bank of Thailand

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Details of reform to improve surveillance procedure for specialized financial institutions (SFIs)

• The State Enterprises Policy Commission (super board) allowed the Bank of Thailand (in October 2014) to take over the supervision and inspection of specialized financial institutions (SFIs) beginning in early 2016.

• MOF keeps its role in setting SFI policy and direction, and appointing executive (that must meet BOT criteria).

• Specialized Banks includes:

- Deposit taking institution:

1. Government Savings Bank (GSB)

2. Government Housing Banks (GHB)

3. Bank for Agriculture and Agricultural Cooperatives (BAAC)

4. Islamic Bank of Thailand (IBANK)

- Non-deposit taking institution:

5. Export-Import Bank of Thailand (EXIM bank)

5. Small and Medium Enterprise Development Bank of Thailand (SME bank)

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Problem of SFIs

• The objective of organizing the SFIs: To play a key role in providing financial services to sectors not adequately served by commercial banks - such as small and medium enterprises (SMEs), agricultural and rural enterprises - and also contributed to the government's social and development policies.• Comments from public:The regulatory framework is weak, occasionally subjected to government intervention, the major role is not fully achieved.• High NPL ratio for SME bank (36.24%of total loan),

and IBANK

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Are they ready for the new regulation under the BOT?

• “…Regulatory standards for SFIs in terms of capital adequacy ratio and loan loss provision

reserves could be looser than for commercial banks because SFIs are required to run business

that comply with government schemes…”, FPO director general-Krisada Chinavicharana, 9 Feb

2015

• “…Government saving bank should not be affected by the measure, as it complies with the rule

and are examined by BOT regularly…”, Director-Mr. Tachapol Kanjanakul, GSB, 1-3 Jan 2015

• “… BOT has examined the Bank for Agriculture and Agricultural Cooperatives twice a year

using the same standard as the commercial bank, the bank stability remain intact, the liquidity

management is better than the requirement, credit quality is good, loan growth increase

steadily, NPL is under control. The measure helps enhance efficiency in the monitoring system

and shore up credibility..”, BAAC president- Luck Vajananawat, 31 Jan 2015

• “…SFIs are development banks, applying universal regulatory standard (like commercial bank)

could conflict with their mission. The new regulation under he BOT should be deferred until the

economy improve and get approval from stakeholders…”, SME Bank chairwoman- Salinee

Wangtal, 24 Mar 2015.

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Research Question?

• Questions:

1. How is the financial condition of depository taking institutions in

Thailand? What indicator should we use?

2. Does the difference in business model and supervision

associate with the difference in the financial condition?

3. Can we infer the risk from the financial condition?

• Data: annual data (2006-2013) from Bankscope.

• 26 observations: 2 finance companies, 4 deposit taking SFIs, 3

foreign bank branch, 2 subsidiaries, and 15 local commercial

bank

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Research Outline and Methodology

1. Assess the financial condition of the deposit

taking institutions (banks) in Thailand and identify

key financial ratios (using PCA)

2. Classify banks according to their financial

condition (using Cluster analysis)

3. Associate the risk aspect to the financial profile &

peer group assessment (using regression)

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Key financial ratios

Profitability and earning

Liquidity

Capital adequacy (solvency)Asset quality/ risk provision

Operational Efficiency

-Return on average equity (ROAE)-Net interest margin (NIM)

-liquid asset to deposit and borrowing ratio (LADBR)-Asset to net loan ratio (ATNL)

income to cost ratio (ICR)

gross loan to loan loss reserve ratio (LLOSR) equity to asset ratio (ETA)

Note: this method is similar to CAMELS approach which was developed by bank regulators in USA to measure financial condition of financial institutions. (ie. Capital adequacy, Asset quality, Management, Earnings (profitability), Liquidity and funding, sensitivity to market risk (loses arising from changes in market prices)

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Principal component analysis

Aspects Variables

Principal component

1 2 3

Profitability

ROAE 0.12 0.35 0.64

NIM -0.44 0.39 -0.08

Liquidity

LADBR 0.51 0.07 -0.06

ATNL 0.44 0.34 -0.42

Efficiency ICR 0.18 0.43 0.48

Asset Quality LLOSR -0.04 0.62 -0.41Capital

adequacy ETA 0.55 -0.20 0.00

Principal component 1:

Tradeoff between higher capital adequacy + liquidity

and lower profitability

Principal component 2:

Asset quality and efficiency

Principal component 3:

Tradeoff between higher profitability + efficiency,

and lower liquidity and asset qualityNote: data is period average (2006-2013),consisting of 26 deposit taking institutions

Financial conditions of 26 banksComponent loading plot Score plot

pink dot represent= finance companyorange dot=specialized government credit institutionbrown dot = subsidiariesyellow dot=local commercial bankgreen dot= foreign bank branch

- Specialized government credit institutions (SFIs) have relatively higher dispersion of component values. (1. IBANK is weak, 2. BAAC have strong financial condition, 3.financial condition of GSB and GHB is quite close to local commercial bank)

- Foreign bank branch and subsidiary have strong capital adequacy and liquidity- Financial condition among the local commercial bank is quite similarThe cluster analysis in the next section will help discriminating the group of financial institutions according to their financial condition. 12

More components

13

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Research Outline and Methodology

1. Assess the financial condition of the deposit

taking institutions (banks) in Thailand and identify

key financial ratios (using PCA)

2. Classify banks according to their financial

condition (using Cluster analysis)

3. Associate the risk aspect to the financial profile &

peer group assessment (using regression)

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Custer analysis

- Principal Components 1-3 are used to classify groups financial institutions (banks)

- This helps us identify the banks that have similar financial conditions

- We assume that there is no prior knowledge about which banks belong to which type or group.

- The grouping will be defined through a cluster analysis of the data

- This allows us to maximize the similarity of banks within each cluster, while also maximizing the dissimilarity between groups that are initially unknown

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Identifying group of financial institutions

Dendogram from hierarchical (average linkage) cluster analysis

- The four largest banks have very similar financial condition- Financial condition of the two SFIs (GHB and GSB) are quite close to the four

largest bank

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9

8

7

6

5

4

3

2

1

ROAE NIM LADBR ATNL ICR

LLOSR ETA

bbl kbank scb ktb bay

gsb lhb thnb tiscob

The cluster analysis yields 9 groups of banks

boc rhb sumitb mizuhob

bkfirs agrico stcb

islbot

kiatnb

megab iacboc

Profitability: ROAE, NIMLiquidity: LADBR, ATNLEfficiency: ICR

Asset quality: LLOSRCapital adequacy: ETA

Financial ratios, 2006-2013 Group of bank

The difference in bank business model and regulatory framework does not necessary implies difference in thefinancial conditions

ghb

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Research Outline and Methodology

1. Assess the financial condition of the deposit

taking institutions (banks) in Thailand and identify

key financial ratios (using PCA)

2. Classify banks according to their financial

condition (using Cluster analysis)

3. Associate the risk aspect to the financial profile &

peer group assessment (using regression)

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Can financial ratio infer to risk?

• There are 2 main types of risk:

- Systemic risk- general risk such as economic slowdown

- Specific risk- balance sheet weakness/ mismanagement

• Financially weak and risky institutions are generally the first

group that suffer in the stressed condition and crisis (as

seen in recent crisis)

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Link between financial condition and risk

• The strong key financial conditions are protection against risk

Profitability & earning

Liquidity

Capital adequacy&solvency

Asset quality & risk provision

Operational Efficiency

RISK

- Funding- Business- Regulatory- Reputation- Asset composition and quality

Financial conditions

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Associating the risk aspect to our analysis of the financial profile.

• The two major indicators that define the risk of the financial institutions are

the non-performing loan to gross loan (NPL) and the z-score (ZSCORE).

• Instead of performing regression of the risk variable on the financial ratios

directly, the first three principal components of these financial ratios are

used as regressors, which helps:

1. solving muticollinearity problem (financial ratios can be collinear with each

other)

2. the dimension reduction property of the PCA helps lowering the effective

number of parameter characterizing the financial conditions.

• We are assessing whether each of the three principal components are an

important determinant of the financial institution’s risk.

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2 main indicators to identify risk

• ZSCORE measures the financial institution’s overall risk taking, which covers credit risk, liquidity risk and market risk that can occur from non-lending activities. It captures the distance to distress or the probability of default. The larger value suggests the lower overall risk and is more stable.

• NPL is an alternative measure of risk which is more specific to the institutions that participate in the lending activities. It is calculated as NPL/Total loan. It reflects the financial stability of the financial institutions.

𝑍𝑆𝐶𝑂𝑅𝐸=𝛼0+𝛼1 𝑃𝐶𝐴1+𝛼2𝑃𝐶𝐴2+𝛼3𝑃𝐶𝐴3

𝑁𝑃𝐿=𝛽0+𝛽1 𝑃𝐶𝐴1+𝛽2 𝑃𝐶𝐴2+𝛽3𝑃𝐶𝐴3

𝑍𝑆𝐶𝑂𝑅𝐸=(𝑁𝑒𝑡 𝑖𝑛𝑐𝑜𝑚𝑒+𝐸𝑞𝑢𝑖𝑡𝑦𝑐𝑎𝑝𝑖𝑡𝑎𝑙)/𝑎𝑠𝑠𝑒𝑡

𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛𝑜𝑓𝑅𝑂𝐴

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There is significant statistical relationship between financial condition and the risk

 Variables Ln(Z-score) NPL/gross loan

Component 1 0.48(4.17)*** -1.08(-1.39)Component 2 0.23(1.80)* -1.06(-1.02)Component 3 0.64(4.08)*** -3.49(-3.19)***

Constant3.46(20.74)*** 4.72(4.16)***

Observations 26 25Adjusted R-square 0.58 0.33

Note: t-statistics in parentheses *p<0.1, ** p<0.05, *** p<0.001

OLS regression for each indicator of risk

• The regression results confirm significant relationship between financial condition

and risk.

• The stronger the financial condition (profitability, liquidity, solvency, credit

quality, efficiency), the lower overall risk and the more stability measured by Z-

Score

• The stronger the financial condition, the lower the risk (measured by NPL ratio)

of the banks that participate in the lending activities

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The peer group assessment

Variables ln(ZSCORE)ln(NPL to gross

loan)ln(ROAE) 0.03(10.95) *** -0.03(-0.35)ln(LADBR) 0.00(-0.19) -0.12(-1.22)ln(ATNL) 0.04(2.51) *** 0.40(0.81)ln(NIM) 0.01(1.52) 0.49(2.27) **ln(ICR) 0.03(3.19)* ** -0.62(-2.31) **ln(LLOSR) 0.01(1.59) -0.84(-5.93) ***ln(ETA) 0.98(123.63) *** 0.37(1.83)*Dumg1 -0.43(-0.76) -1.48(-2.97)***dumg2 -0.53(-0.85) -0.45(-0.94)dumg3 -2.84(-2.86) *** 1.40(2.34)**dumg4 -1.24(-2.20) ** 0.36(1.05)dumg5 -1.40(-1.41) -0.24(-0.41)dumg6 -2.92(-2.95) *** -0.23(-0.37)dumg8 -0.11(-0.15) 0.09(0.20)dumg9 -0.12(-0.12) 1.35(2.15)**_cons 1.72(5.79) *** -1.62(-0.63)Obs. 173 160Overall R2 0.64 0.71

Note: Data is annually observed from 2006-2013. Dummy for the group is held constant over the period.

Main findings:

1. The sign of the coefficient for the

financial ratio is correct.

2. Group 7 is employed as base group.

After controlling for the financial ratios,

the base group is relatively more stable

than the other groups.

where group 7 consists of the big 5

commercial banks and government

housing bank, and other 3 new

commercial banks.

Panel regression for Zscore and NPL ratio using random effect estimation.

bbl kbank scb ktb bay

gsb lhb thnb tiscob

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Conclusion

• This paper investigates the effects of bank financial performance on

the risk-taking.

• The balance sheet items of the 26 financial institutions are carefully

examined. Five main aspects that commonly explain their financial

position are explored, such as profitability, liquidity performance,

asset credit quality, efficiency and capital adequacy.

• The research also identifies the group of these financial institutions

according to their balance sheet characteristics.

• The implications on the financial risk aspects are analyzed. We found

that the strong financial position significantly associate with the

higher stability, longer distance to distress and lower risk.

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Suggestion for future work

• Due to the limitation of the data, an analysis cannot well capture 2 aspects

1. An analysis cannot capture the risk adjusted financial condition (i.e. data on the risk weighted asset, risk weighted equity in Bankscope is not completed).2. An analysis of the risk of the financial institutions can be more comprehensive with the data on concentration risk (risk from type of customers), foreign exchange exposure, maturity mismatch of asset and liability, etc.