Factors determining net interest margins of the commercial banks in vietnam

List of Abbreviations ABBank An Binh Commercial Joint Stock Bank Agribank Vietnam Bank for Agriculture and Rural Development Baovietbank Bao Viet Joint Stock Commercial Bank BIDV Bank of

- i -

FACTORS DETERMINING NET INTEREST MARGINS

OF THE COMMERCIAL BANKS IN VIETNAM

In Partial Fulfillment of the Requirements of the Degree of

MASTER OF BUSINESS ADMINISTRATION

THESIS

FACTORS DETERMINING NET INTEREST MARGINS

IN THE COMMERCIAL BANKS IN VIETNAM

In Partial Fulfillment of the Requirements of the Degree of

MASTER OF BUSINESS ADMINISTRATION

In Finance

by

Ms Do Thi Thanh Huyen ID: MBA03015 International University - Vietnam National University HCMC

- iii -

Acknowledge

To complete this thesis, I have been benefited from the following people:

I would like to express my appreciation and say thank my supervisor, Dr Nguyen

Kim Thu for her careful guidance and support me to complete this thesis

I also would like to thank all lecturers for teaching me, giving me interesting

knowledge and all office staffs for their support me during two years at International

University

Plagiarism Statements

I would like to declare that, apart from the acknowledged references, this thesis either does not use language, ideas, or other original material from anyone; or has not been previously submitted to any other educational and research programs or institutions I fully understand that any writings in this thesis contradicted to the above statement will automatically lead to the rejection from the MBA program at the International University – Vietnam National University Hochiminh City

Table of Contents

Acknowledge i

Plagiarism Statements ii

Copyright Statement iii

Table of Contents iv

List of Abbreviations vi

List of Tables vii

List of Figures viii

Abstract ix

CHAPTER 1 INTRODUCTION 1

1 Background .1

2 Research objectives 2

3 Research method 2

4 Scope and limitation of the study 2

5 Research structure 3

CHAPTER 2 4

OVERVIEW OF VIETNAMESE BANKING SYSTEM 4

1 Growth of Vietnamese banking system 4

2 Vietnamese commercial banks performance:……… 6

CHAPTER 3 .9

LITERATURE REVIEW 9

1 Previous international studies 9

2 Previous researches in Vietnam 13

CHAPTER 4 14

DATA AND METHODOLOGY 14

1 Sampling design 14

2 Data collection methods 14

3 Variables 14

4 Framework: 17

CHAPTER 5……… 18

FINDINGS 18

1 Descriptive statistics………18

2 Empirical results 19

- v -

CONCLUSIONS 25

1 Summary of the thesis 25

2 Limitations 25

3 Main implications 26

4 Suggestion for future research 26

REFERENCES 28

List of Abbreviations

ABBank An Binh Commercial Joint Stock Bank

Agribank Vietnam Bank for Agriculture and Rural Development Baovietbank Bao Viet Joint Stock Commercial Bank

BIDV Bank of Investment and Development of Vietnam

Eximbank Export and Import Joint Stock Commercial Bank

JSCBs Joint-stock commercial banks

Sacombank Saigon Thuong Tin Commercial Joint Stock Bank

Southern Bank Southern Bank

VCBS Vietcombank Securities Co., LTD

VIB Vietnam International Joint Stock Bank

Vietcombank Joint Stock Commercial Bank for Foreign Trade of Vietnam VietinBank Vietnam Bank for Industry and Trade

- vii -

List of Tables

Table 1 Descriptive statistics of all variables of entire sample 19

Table 2 Descriptive statistics of all variables of SOCBs 19

Table 3 Descriptive statistics of all variables of JSCBs 19

Table 4 Correlation of independent variables 20

Table 5 Redundant Fixed Effect Tests………21

Table 6 Hausman Test result………21

Table 7 Fixed effect model ………22

List of Figures

Figure 1 Number of commercial banks in Vietnam from 2006 to 2012 4

Figure 2 Total assets of SOCBs and JSCBs from 2008 to 2011 5

Figure 3 Interest rate stipulated by SBV from 2/2008 to 12/2011 6

Figure 4 Bad debt ratios of Vietnamese banking system from 2007 to June 2012 7

Figure 5 The percentage of bad debt according to bank types at 31/3/2012 8

- ix -

Abstract

This study investigates the factors determining the net interest margins of 33 Vietnamese commercial banks during the period 2008-2011 Based on the literature reviews, market power, managerial risk aversion, interest rate risk, credit risk, management quality and implied payment are the independent variables in the model Fixed effects model will be chosen to run regression of panel data The empirical analysis points out that managerial risk aversion, credit risk, management quality and implied payment are statistically significant in explaining bank’s net interest margins Among four significant variables said above, only management quality has negative relationship with net interest margins Additional, there is no evidence to conclude that both market power and interest rate risk are significant to net interest margins

Keywords: net interest margins, Vietnamese commercial banks

CHAPTER 1 INTRODUCTION

1 Background

Becoming the fiftieth member of the World Trade Organization is the Vietnam’s remarkable economic event in 2007 The Vietnamese economy has accessed to the global market and has gained many achievements The public data released by World Bank showed that Vietnam GDP growth rate rose from 8.23% in

2006 to a peak 8.46% in 2007 and the inflation rate was only 8.30% in this same year Enterprises have many opportunities not only to develop their domestic market but also to expand into international market However, five years later, the economy was falling down so fast and there has been no signal for complete recovery In 2011, GDP growth rate stood at 5.89%, lower than 6.78% in 2010, and 6.31% in 2008 The inflation rate soared to 23.12% in 2008, much higher than previous year and was recorded at 18.67% in 2011 Unstable macroeconomic environment makes the business of enterprises in general and banking system in particular become more difficult than ever before Thus, Vietnamese commercial banks not only find the way

to survive, to face to the competition pressures from the foreign financial institutions,

to meet many international standard regulations; but also take an important role in saving enterprises and economic recovery

Bank acts as “an intermediary between the demanders and suppliers of funds.” (Ho and Saunders, 1981, p.583) In recent years, Vietnamese commercial banks seem

to perform this function inefficiently Companies who are in tremendous need of capital must suffer high lending interest rates Although the State Bank of Vietnam (SBV) imposed a ceiling deposit interest rate in the hope of dragging down lending interest rates, the access to banking loans remains harsh for companies In the mean time, the interest rate spreads (i.e., the difference between lending interest rates and deposit interest rates) brings huge profits to commercial banks This is the largest component of a bank’s net interest income and leads to the ratio net interest margins (NIM), which measures the return on bank’s earning assets, is high Accordingly, commercial banks have been criticized to have maintained high net interest margin and no difficulty sharing with companies Despite net interest margins being one of

the major determinants of bank profits, little is known of the determinants of

Vietnamese trading bank interest margins Why Vietnamese commercial banks need

to maintain high NIM or which variables have strong impact on NIM become the interesting questions for all those who care about bank sector in Vietnam Therefore,

in this context, the study will help to explain the queries above It is likely that the

NIM reflects the costs such as the implied interest payments that the banks have to

offer to its customers Those non-interest expenses must be accounted for in the net

interest margins Besides, the high credit risk also partly contributes to the high net interest margin, as credit risk premium increases in the current economic downturn Consequently, the principal objective of this research is to empirically test the model

of bank interest margin determination in the context of Vietnamese banking system Based on the findings of the research, the SBV would be able to have effective solutions (instead of the administrative measures) to reduce the lending rates

4 Scope and limitation of the study

This study is limited to 33 Vietnamese commercial banks Foreign commercial banks and foreign bank branches are beyond the scope of this study

This study is also limited to the period from 2008 to 2011 From the analysis mentioned above, this is the period of time in which there have been numerous fluctuations in the operations of the Vietnamese banking system and of the whole

- 3 -

economy This is also the period in which banking operation and the interest rate policy of the SBV received special attention from businesses

5 Research structure

This research includes five chapters and conclusions

Chapter 1 gives the background and justifies the reasons of conducting this study Chapter 2 provides an overview of the banking system in Vietnam, and then review key theories and empirical studies related to the model development of net interest margins in chapter 3 Chapter 4 discusses the model used in this research and explains the relationship between dependent and independent variables Chapter 5 discusses the results of the regression Finally, the conclusion will summary all results mentioned in chapter 5, also the implications, limitations and suggestion for future researches

CHAPTER 2

OVERVIEW OF VIETNAMESE BANKING SYSTEM

This chapter will look around the operation of Vietnamese banking system in recent years The achievements banks get, as well as the problems they are facing to will be considered herein These characteristics of Vietnamese banking system help

in understanding and explaining for later analysis in the next chapters

1 Growth of Vietnamese banking system

Though the Vietnamese banking system is quite young compared with others

in the world, it has been growing very fast The number of commercial banks increases dramatically, rising from 8 banks in 1991 to 85 banks in 2007 and 98 banks

in 2012 Although VCB, Vietinbank, MHB were equitized, SBV still sort them into group State-owned commercial banks (SOCBs) Therefore, of those 98 banks, there are 50 branches of foreign banks, 5 foreign banks, 4 joint-venture banks, 34 joint-stock commercial banks (JSCBs), and 5 SOCBs In the period of 2006-2012, the Vietnamese banking system has increasingly attracted foreign attention The number

of foreign banks in Vietnam has increased by 77 percent in this period (see Figure 1)

Figure 1 Number of commercial banks in Vietnam from 2006 to 2012

State-owned commercial banks

Source: website of SBV (www.sbv.gov.vn), BVSC (www.bvsc.com.vn), and VCBS (www.vcbs.com.vn)

In addition, commercial banks in Vietnam have grown in both total assets and equity As of the end of 2012, website of SBV updated figures about the total assets

of the commercial banking system as VND 5,085,850 billion, up by 3.84% compared

to VND 4,897,774 billion at the end of 2011 (Source: The report of the National Financial Supervisory Commission 2012) However, there exist differences among two major banking groups in the growth rates of total assets While SOCBs are gradually losing their leader position, JSCBs have an enormous increase in asset growth rate For instance, the asset growth rate of ACB, HDB, and Eximbank in

2011 were 37.91%, 98.91% and 40.01% respectively, while this rate of the two SOCBs - Agribank and BIDV- are 4.68% and 10.78%, respectively (Source: author’s calculation)

Figure 2 Total assets of SOCBs and JSCBs from 2008 to 2011 (unit: billion)

(Source: Financial reports of 5 SOCBs and 31 JSCBs from 2008 to 2011)

In terms of equity capital, to satisfy the requirement of the SBV on

commercial banks’ minimum chartered capital of VND 3,000 billion, stated in

Decree 141/2006/ND-CP in 2010, chartered capital of most banks except BaoViet Bank and PG Bank, reached VND 3,000 billion at the end of 2011 Some SOCBs have the equity capital far above the required level, such as BIDV with capital of 28,251 billion VND, Agribank with capital of 21,103 billion VND and Vietinbank with capital of 20,230 billion VND By raising the chartered capital, banks will

enhance their competitiveness and maintain the Capital Adequacy Ratio (CAR) of 9

percent regulated by the Decree 13/2010/TT-NHNN

2 Vietnamese commercial banks performance:

With some remarkable changes as said above, Vietnamese banking sector

was expected to develop strongly or at least to be stable However, recently,

commercial banks have to face with problems related to interest rate race and bad

debts To curb high inflation rates, the SBV implemented the tight monetary policy

in 2008 with a series of solutions Firstly, VND base deposit rate was applied, from

12% to 14% per year at the first half year of 2008 Next, other tools of monetary

policy were used simultaneously, such as higher reserve requirement and the

issuance of VND 20,300 billion of compulsory SBV bills to withdraw money out of

circulation Facing with increasing difficulty in capital mobilization, banks rushed to

raise interest rates and provided promotion to encourage deposits from individuals

and organizations Some small-sized banks adjusted their VND mobilizing interest

rates up to 18% to 19% per annum Large-sized banks also push their rates to high

point to keep customer’s feet Besides that, being controlled maximum 150% of the

base interest rate, or within a cap of 18% per annum, banks add more extra fees into

VND lending interest rate to cover the high mobilizing interest rate Therefore, both

real mobilizing interest rate and lending interest rate increased very high From 2009

until now, SBV continuously enacts many decrees to stop the interest rate race and

keep it stable

Figure 3 Interest rate stipulated by SBV from 2/2008 to 12/2011

(Source: SBV’s website http:// www.sbv.gov.vn)

- 7 -

With regard to bad debts, this is really the urgent problems of Vietnamese banking sector Before 2008, Vietnam’s credit growth was too hot This growth was later reduced by the SBV’s tight monetary policy However, in 2010, although the global economy has not recovered completely from the 2008 financial crisis, it had to suffer from the consequences of the debt crisis in the Euro zone in the second quarter

of 2010 Enterprises in Vietnam were also deeply influenced by the crisis, and numerous enterprises had to do bankrupt or stop their operation As a result, banks find it extremely hard to collect their loans made in previous periods The high lending interest rate made it harder for companies to repay their debt Consequently,

banks’ bad debts are growing According to Chief Inspector of the State Bank of Vietnam, Mr.Nguyen Huu Nghia’s statement dated 12/7/2012, the bad debts which

was calculated by SBV was 8.6% of total outstanding loans, much higher than 4.47% reported by the credit institutions

Figure 4 Bad debt ratios of Vietnamese banking system from 2007 to June 2012

(Source: Report of Vietnamese banking sector Q2.2012, Vietcombank Securities

Company – VCBS)

It is the fact that the percentage of bad debts in the state-owned banks is much more than the others They occupied 50% of bad debt ratio of whole credit market The next positions were commercial joint stock banks (27.8%), foreign banks (17.5%) and the remains belonged to other financial institutions (4.2%) Most of state-owned banks serve many customers who are state-owned corporations with inefficient operations It could be seen as one of the reason explaining why the state-owned banks stood on top on bad debts ratio

Figure 5 The percentage of bad debt according to bank types at 31/3/2012

(Source: VnEconomy’s website www.vneconomy.com)

Others

- 9 -

CHAPTER 3

LITERATURE REVIEW

1 Previous international studies:

Determining the bank’s net interest margins is the attractive subject and researched in many countries Ho and Saunders (1981) are considered as the pioneers

in this subject In their research, they viewed banks as the dealers in the credit market, providing the services to depositors and loaners Because the mismatching in maturity of the deposits and bank loans, banks must face to two kinds of risks: reinvestment risk and refinancing risk when a change in the short-term rate of interest and a bank’s unmatched portfolio of the deposits and loans, it will face to interest rate risk For instance, having a long-term deposit, but no new loan demand, bank will invest funds temporarily in money market In this case, it will get trouble in reinvestment risk if short-term rate fall Or having a new loan demand but no inflow

of deposit, bank has to borrow funds from money market Refinancing risk happens

as short-term rate raise Hence, banks will determine the optimal interest spread in order to cover the uncertainty in transactions and interest rate risk Based on this reasoning, the study by Ho and Saunders (1981) defined the pure spread (s) as a

function below

=Where measures the elasticity of demand and supply in the markets in which the bank operates Bank faces relatively inelastic demand and supply (high )

it may be able to exercise monopoly power, and earn a producer's rent by demanding a greater spread than it could get if banking markets were competitive The second term in the model implies that, other things equal, the greater the degree

of risk aversion (measured by R), the larger the size of transactions (measured by Q), and the greater the variance of interest rates (measured by ), the larger bank margins are

The quarterly data from 1976 to 1979 of over 100 US commercial banks, and cross-section regression were used in this study Although not explicitly considered

in above equation, the research conducted an empirical study on the determinants of actual bank margins (M), which comprise a pure spread (s) due to underlying

transaction uncertainty, plus mark-up for implicit interest expense (IR), the

opportunity cost of required reserves (OR), and default premiums on loans (DP) It

was found that the pure spread and the implied interest expense were statistically significant, which implied that the main determinants of the size of actual bank margins were transactions uncertainty and markups to cover implicit payments to depositors Then, they tested whether these estimated spreads depend on interest rate volatility and market structure or not

Later studies on bank net interest margins have added more independent variables to the model of Ho and Saunders The next article done by R.W.McShane and I.G.Sharpe (1985) continued to contribute new discoveries on NIM and its determinants In the case of Australian trading banks, the authors assumed the uncertainty coming from the instantaneous short-term money market rate, wider than that from the deposit and loan rates as stated in theory of Ho and Saunders (1981) In addition, the factors chosen in this approach were the bank’s power in the loan and deposit markets, interest rate volatility, and risk aversion, uncertainty of the instantaneous money market risk-free interest rate and average size of transactions After running regression with the sample of 22 banks, from 1962 to 1982, they found that there existed a stable non-linear relationship between NIM and those above-mentioned factors Moreover, upon the hypothesis of differences between business and personal sectors, they found that in the Australian context, the more personal business sector, the greater market power and the higher margins are

Angbazo (1997) developed his model from the previous papers by adding some risk factors He concentrated on building a function in which NIM was a function of those risks and bank specific variables His sample consisted 286 US commercial banks with assets equal or over USD 1 billion from 1989 to 1993 and was estimated by generalized least squares (GLS) The regression’s results showed the relationship between NIM and determinants by entire sample and by each bank group While the default risk proxy was significantly positive, the interest rate risk was negative and significant to NIM Three other proxies including capital base, management quality, and non-interest bearing assets were significantly positive For result tested by each bank group, the author realized that the sensitivity of above variables on NIM of each group was different For instance, money-center and local banks’ NIM has relationship with defaults risk, but regional and super-regional banks

Another research of Australian banks was provided by Barry William (2007), who investigated the NIM of 22 domestic banks and 21 foreign subsidiary banks operating from 1989 to 2001 Not only testing the application of the Ho and Saunders (1981) model with the core variables- managerial aversion and interest rate risk, he also considered the extended models like Angbazo (1997) and Joaquin Maudos and Juan Fernandez de Guevara (2004) such as operating cost, liquidity, management quality, credit risk, interaction between interest rate risk and credit risk, bank operation size, implied payment, implied taxes and control variables, in order to have

a framework for Australian banking sector After running descriptive statistics, he found that the foreign banks had lower NIM, lower level of retail, but higher levels

of average capital than domestic Australian banks Four major banks called the Big Four banks have the lower operating cost, higher management quality, while the others were very active in their retail banking Consistent to Ho and Saunders (1981), regression presented that interest rate volatility and management risk aversion related positively on NIM While McShane and Sharpe proposed NIM and market, power to

be positive, William found this relationship was negative in case of whole sample, but positive consistently in case of NIM of big four banks in Australia Continuously, the higher management quality was, the lower NIM was However, variable liquidity, implied taxes was found to have no relationship, and credit risk was negative significantly to NIM

Anthony Q.Q.Aboagye, S.K.Aknoena, T.O.Antwi-Asare and A.F.Gockel (2008) explained the bank’s optimal spread between lending rate and deposits rate in Ghana Like other authors, their research relied on Ho and Saunders (1981) framework and the model of Joaquin Maudos and Juan Fernandez de Guevara (2004) The determinants here included the bank specific (the competitive structure of markets, average operating costs, extent of risk aversion, volatility of money market rates, riskiness of a bank’s loan portfolio, covariance of interaction between interest rate risk and credit risk and the average size of credit and deposit operations), industry characteristics (banking industries structure, the Lerner index, the concentration, opportunity cost of non-earning bank reserves) and macroeconomic variables (expected inflation and money supply) The quarterly data of 17 Ghanaian banks was collected Their finding were: the decrease in market power, bank concentration, bank total assists, bank equity, inflation and bank staff expenses, capital expenditure and administrative expenses over total assets would decrease NIM, while the bank liquidity, central bank lending rate, bank management efficiency would increase NIM

Ahmet Ugur and Hakan Erkus (2010) investigate the net interest margins of both domestic and foreign banks in Turkey Firstly, they run regression to find the effect of bank specific factors on the bank spreads, including NIM, bank size, risk aversion, loan quality, liquidity risk, bank market share, operating costs, personnel expenses, and management quality Then, the constant term in the first model called

“pure spread” would become the dependent variable in the second regression In this regression, the independent variables were volatility of interest rates, the ratio of budget deficit to GDP, GDP growth rate, inflation rate and two crisis dummy variables to capture the effect of the financial crisis in Turkey in two years The authors run the descriptive statistics and the panel data random effect model They found that the foreign bank had higher internet margin due to their higher operating costs However, they also had higher personnel expenses and management quality, while their market shares were smaller than domestic banks While NIM and market share had a negative sign, the bank size, operating costs, and risk adverse affect positively on NIM The liquidity ratio was not significant factor in the model For the second model, Ahmet Ugur and Hkan Erkus (2010) realized that only inflation rate significantly affected on the pure spread