Credit risk management case study of BIDV

This is the main reason that drove this study to describe credit risk management in BIDV, to know why non-performing loan ratio in BIDV has been sharply reduced from 38.3% in 2004 to 2.8

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECNOMICS HOCHIMINH CITY

K -

BÙI NGUYÊN NGỌC

CREDIT RISK MANAGEMENT:

CASE STUDY OF BIDV

MASTES’S THESIS

In Banking Ology code: 60.31.12 Supervisor: Dr Nguyễn Văn Phúc

Ho Chi Minh City – 2010

Finally, I want to express my sincere thanks to every member of my family for their encouragement and support during the time I devoted to this dissertation

Page i

ABSTRACT

Credit risk is one of the most popular risks in banks due to their intermediary functions: lending and borrowing An excessive level of credit risk may destroy not only banks’ profitability but also the stability of global banking system Therefore, it

is necessary for banks to develop an effective credit risk management strategy not only to protect themselves but also to prevent banking crises

In case of BIDV, BIDV is one of four State Banks established when Viet Nam banking system is at a very early stage of development For a long time, BIDV was controlled in allocating loans by government Therefore, credit risk management has been the main challenge facing the board of BIDV managers With the best try of this board, since 2008, BIDV has controlled credit risk that comply with international standard (non-performing-loan ratio was less than 3%) This is the main reason that drove this study to describe credit risk management in BIDV, to know why non-performing loan ratio in BIDV has been sharply reduced from 38.3%

in 2004 to 2.82% in 2009

Both secondary data and primary data are needed for this study Collected data is analyzed by Statistical Package for Social Studies version 16.0 (SPSS) Cronbach alpha is used to measure coefficient of reliability and t-test technique is used to test the hypotheses about the four factors influence reduction of non-performing-loan ratio in BIDV These techniques and tools help collected data transform into information that will answer the researcher’s questions

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LIST OF FIGURES

Figure 1.1: Structure of chapter 1 2

Figure 1.2: Field of research problem 4

Figure 1.3: Method of secondary data 7

Figure 1.4: Population and sampling 8

Figure 1.5: Quota sampling method 9

Figure 1.6: Structure of the study 12

Figure 3.1: BIDV Organization Chart 40

Figure 3.2: BIDV’s non-performing loans 45

Figure 3.3: BIDV’s loan structure by collateral 46

Figure 3.4: BIDV’s loan structure by economic sector 47

Figure 4.1: Respondents’ position 57

Figure 4.2: Respondents’ working years in BIDV 58

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LIST OF TABLES

Table 2.1: Level of specific provision 20

Table 2.2: Example of a loan rating system and bond rating mapping 23

Table 2.3: Strategies for reducing and scoping with portfolio credit risk 26

Table 3.1: BIDV’s key performance indicators 41

Table 3.2: BIDV’s credit indicators 43

Table 3.3: Loan classification in BIDV 49

Table 3.4: Summarize four factors influencing NPL ratio in BIDV 52

Table 4.1: Four variables with different aspects 58

Table 4.2: Level of agreement in survey questionnaire 59

Table 4.3: The overall score of Cronbach’s alpha 60

Table 4.4: The t-test result 61

Table 4.5: Summary of hypotheses testing results 64

LIST OF APPENDICES Appendix A 74

Appendix B 75

Appendix C 79

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TABLE OF CONTENTS

Acknowledgment i

Abstract ii

List of figures iii

List of tables iv

List of appendices iv

Table of contents v

Chapter 1: Introduction 1

1.1 Introduction 1

1.2 Rationale of the study 2

1.3 Statement of the problem and the scope of the study 3

1.4 Research questions and objectives 4

1.5 Methodology 5

1.5.1 Research design 5

1.5.2 Data collection 6

1.5.3 Data analysis 10

1.6 Significance of the study 12

1.7 Structure of the study 12

Chapter 2: Literature review 14

2.1 Introduction 14

2.2 Basic functions of banks 14

2.3 Lending business 15

2.3.1 The board of directors’ written loan policy 15

2.3.2 Lending procedure 16

2.4 Credit risk in banks 17

2.4.1 Credit risk 17

2.4.2 Loan classification 19

2.4.3 Loan loss provision 20

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2.4.4 Non-performing loan 21

2.5 Credit risk measurement 21

2.5.1 Traditional approaches 21

2.5.2 Modern approaches 24

2.6 External factors that affect the level of credit risk 27

2.6.1 Financial deregulation 28

2.6.2 Supervision and re-regulation 28

2.6.3 Competition 29

2.6.4 The recent financial crisis 30

2.7 Internal factors that affect the level of credit risk 30

2.7.1 Credit information 30

2.7.2 Technology 32

2.7.3 Credit staffs 33

2.7.4 Loan policy 34

2.8 Summary 35

Chapter 3: Case study of BIDV 37

3.1 Introduction 37

3.2 Overview of BIDV 37

3.2.1 Introduction 37

3.2.2Organization structure 37

3.2.3 BIDV business performance 41

3.3 Lending business 43

3.3.1 Overview 43

3.3.2 Non-performing loans and loan loss provision 44

3.3.3 Loan structure 45

3.4 Internal factors that influence non-performing-loan ratio in BIDV 47

3.4.1 Credit information 47

3.4.2 Technology 48

3.4.3 Credit staff 50

3.4.4 Loan policy 51

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Page vii

3.4.5 Suggesting hypotheses 52

3.5 Summary 55

Chapter 4: Data analysis and findings 56

4.1 Introduction 56

4.2 Data collection results 56

4.3 Data analysis 57

4.3.1 Descriptive statistic 57

4.3.2 Measures of reliability 58

4.3.3 Statistical hypotheses testing (t-test) 60

4.4 Comparison and discussion of findings 62

4.4.1 Credit information 62

4.4.2 Technology 62

4.4.3 Credit staffs 63

4.4.4 Loan policy 63

4.5 Result of hypotheses testing 64

4.6 Summary 64

Chapter 5: Recommendation and Conclusion 66

5.1 Introduction 66

5.2 Reviewing research questions 66

5.3 Recommendation for BIDV 66

5.3.1 Credit information 66

5.3.2 Technology 67

5.3.3 Credit staffs 67

5.3.4 Loan policy 68

5.4 Recommendation for other banks 68

5.5 Limitation of the research 69

5.6 Summarizing and concluding the dissertation 69

References 70

Section 1.4 which includes two subsections 1.4.1 and 1.4.2 defines the research questions and research objectives Subsection 1.4.1 addresses the research questions that will be respectively answered in chapters of the study Subsection 1.4.2 presents research objectives that the study covers in the process of solving the research problem defined

Section 1.5 discusses the aspects of research methodology such as selecting from alternative types of research, research design and research techniques Section 1.6 points out the significance and scope of the study, and finally section 1.7 describes overall structure of the thesis

Section 3: Statement of the problem and

scope of the study

Section 1: IntroductionSection 2: Rationale of the study

Section 4: Research questions and objectives

Section 5: Methodology

Section 7: Structure of the study Section 6: Significance of the study

Figure 1.1: Structure of chapter 1

1.2 Rationale of the study:

In today’s world, in order to meet customers’ requirements, there is a need for banks

to diversify their business including other activities such as payments, leasing, and investments besides the two traditional functions of lending and borrowing However, lending still plays an important role in banks because banks’ revenue primarily comes from lending revenue which contributes over a half of bank total operating (about 70% in case of BIDV)

The traditional way that banks make their profit is to take risk in exchange for an acceptable return to not only cover the cost of funding but also maintain their profitability Thus, the main business of banks is not, as everyone might assume, taking deposits and making loans but minimizing the risk in collecting interest and principle from the loans which is known as managing credit risk (Burton & Lombra 2006)

Credit risk is usually associated with banks because of their intermediary function which is channeling funds from people who have fund surplus to those who have fund deficit for their investment opportunities (Mishkin & Eakins 2006) Historically, financial crises are usually derived from the failure of banks to manage credit risk from poor quality loans or high probability of customers’ default (Yarbrough & Yarbrough 2006)

In case of BIDV, BIDV is one of four State Banks established when Viet Nam banking system is at a very early stage of development For a long time, BIDV was controlled in allocating loans by government Therefore, credit risk management has been the main challenge facing the board of BIDV managers With the best try of this board, since 2008, BIDV has controlled credit risk that comply with international standard (non-performing-loan ratio was less than 3%) This is the main reason that drove this study to describe BIDV credit risk management, to know why non-performing loan ratio in BIDV has been rapidly reduced from 38.3% in

2004 to 2.82% in 2009

1.3 Statement of the problem and scope of the study

This study conducts with particular emphasis on why non-performing-loan ratio in BIDV has been rapidly reduced from 38.3% in 2004 to 2.82% in 2009

Stemming from the reason mentioned in the rationale part, this research will focus two main parts: First is credit risk management background; second is case study of BIDV credit risk management The first part provides some background knowledge about credit risk, credit risk measurements, management and the factors that influence credit risk The second part analyses BIDV’s case in reducing non-performing-loan ratio This part presents three main subparts including overview of BIDV; analysis credit activities, application of credit risk management theory to its credit activity practice; consideration of four factors including credit information, technology, credit staff and loan policy during the period 2004-2009, and suggesting hypotheses These analysis and consideration help the researcher realize that credit risk management is one of significant achievements of BIDV because at the end of

2009, BIDV has controlled credit risk under international standard

loan ratio was less than 3%) Maybe there are many reasons leading the success of BIDV In scope of this study, four factors including credit information, technology, credit staff, and loan policy will be examined as the main positive factors that influence credit risk management of BIDV

The four factors will be presented throughout this study Firstly, this study reviews literature related to the four factors and credit risk management theory Secondly, by analyzing BIDV’s credit business practice, this paper shows how the four main factors influence BIDV on reducing non-performing-loan ratio Finally, findings from the survey by questionnaires confirm the above relationships

Credit staffs

NPL ratio in BIDV

Technology

Loan policy

Credit

information

Figure 1.2: Fields of the research problem

1.4 Research Questions and Research Objectives:

1.4.1 Research Questions

Research questions involve the research translation of “problem” into the need for inquiry (Zikmund, 1997, p.88) The research problem defined above leads to the

following research questions:

• What are factors that influence non-performing-loan ratio in BIDV?

• How has BIDV applied credit risk management theory to practice?

1.4.2 Research Objectives

This study is conducted with the purpose of:

• To know the main factors leading to BIDV success in reducing non-performing loan ratio,

• To consider whether BIDV applies theory to manage its credit risk or not

1.4.3 Research hypotheses

Aiming to confirm the influence of four factors including credit information, technology, credit staffs and loan policy on reducing non-performing-loan ratio in BIDV, the researcher assumes hypotheses as follows:

H1: Credit information variable influences non-performing-loan ratio in BIDV

H2: Technology variable influences non-performing-loan ratio in BIDV

H3: Credit staffs variable influences non-performing-loan ratio in BIDV

H4: Loan policy variable influences non-performing-loan ratio in BIDV

1.5 Methodology

The research methodology includes research design, data collection and data analysis

1.5.1 Research design: provide a road map of the whole research,

The researcher undertakes both qualitative and quantitative approach to this study since both numerical data (BIDV’s performance indicators, BIDV’s business lending indicators, level of agreement about factors that influence non-performing-loan ratio, ) and non-numerical data (respondents’ background, position and their suggestion to help BIDV continuously reduce non-performing-loan ratio, ) are needed to answer the research questions

According to G.Zikmund (1997), there are four basic design techniques: survey, experiment, secondary data and observation This research utilizes both survey and secondary data methods Based on the objectives of the research, survey method helps the researcher collect primary data in order to indentify of four factors influencing non-performing-loan ratio in BIDV while secondary data methods is necessary for the researcher to understand credit risk background and describe BIDV’s situation in managing credit risk or reducing non-performing-loan ratio

Since this study applies perception survey which investigates the feeling of respondents about the research problem, the findings are influenced by subjective judgment of respondents However, the researcher also utilizes secondary technique for the purpose of exploring evidences to confirm the research problem

1.5.2 Data collection

This section will describe the way in which data including both primary and secondary data from a variety source of information was collected Secondary data was collected from available sources such as books, previous researches, BIDV’s annual reports, financial journals and magazines while primary data was obtained through surveys and interviews conducted by the author

1.5.2.1 Secondary data

There are many advantages by using secondary data in conducting a research First,

it is economical in the way that collecting available data is almost always less expensive than collecting firsthand data through a study In addition, collecting secondary data help researcher save a huge amount of time spending analyzing and interpreting the data collected Second, in some cases, secondary data is the only source that researcher can collect from the previous periods Finally, unlike primary data, secondary data is generally permanent and available in a form that is easily checked and collected by others (Zikmund, 1997)

There are many types of secondary data such as documentary secondary data, multiple source secondary data and survey based secondary data (Saunders, Lewis

& Thornhill 2007) However, this study focuses only on the documentary secondary data source which includes BIDV internal materials (like BIDV regulations and annual reports which collected from the internet and intranet website of BIDV) and other written materials (such as previous researches, books, journals, newspapers and magazines) These kinds of secondary data are important raw data sources for this study

For this study, the information from written materials like previous researches, books, financial magazines, journals were used to build up literature review while BIDV s annual reports and regulations which collected

Chapter 1: Introduction Page 7

from the official internet and intranet websites of BIDV were used to provide a clear picture about credit risk management of BIDV

Figure 1.3: Method of secondary data collection

Based on the above advantages of secondary data, the researcher decided to use

secondary data as one of the sources of information in order to conduct this study

work relevant to lending business

It would be impracticable for this study to collect all data available from the entire population of all BIDV credit staffs because of the limited time and financial sources Thus, this research will be conducted with a sample size of 100 BIDV credit staffs including 20 managers/vice managers, 30 credit department leaders and

Chapter 1: Introduction Page 8

Figure 1.4: Population, sample and sampling methods

Source: Adapted from G.Zikmund (1997) The quota sampling technique is used in this study because of its advantages in term

of time, finance and convenience Three steps of the technique are described as below:

• First, the whole population of BIDV credit staffs is divided into three significant classes: managers/vice managers, credit department leaders and credit officers This classification is based on the researcher judgment that the higher position the credit staffs are in, the more reasonable feeling they have

• Secondly, each class is determined the desired proportion Managers/vice managers group occupies 20% of the sample, credit leaders group occupies 30% of the sample and 50% of the sample is credit officers group The determination is based on the researcher judgment mentioned in the first step Since this is a perception survey, the findings are influenced by subjective judgment of respondents Therefore, a half of selected sample are credit staffs with high positions Thanks to the advantage of being a member of BIDV, it

is quite easy for the researcher to communicate with managers/vice managers and credit department leaders about the research problem

30 credit dept leaders

20 managers

Chapter 1: Introduction Page 9

In this study, number of credit officers occupies only 50% of sample while it

is 90% in Chau’s (2009) This is the main reason leads the researcher retest

the four hypotheses conducted by Chau (2009)

• Finally, quota sample (100 respondents) is fixed The sample of this study is about 100 respondents (over 5 times of observed variables) including 20 managers/vice managers, 30 credit department leaders and 50 credit officers This number was decided after considering some previous researches For example, see Tho & Trang (2008, p.35) or Trong & Ngoc (2008, p31)

To obtain the desired sample size, a total of 150 self-administered questionnaires were distributed to the respondents by the researcher Of these, 100 questionnaires were returned making effective response rate 67%

Figure 1.5 Quota sampling method

Source: Adapted from Adapted from G.Zikmund (1997) This study utilizes two techniques to obtain primary data: interview (telephone interview and face to face interview) and self administered questionnaire Interview method is used to gather response of manager group while self administered

Population

(BIDV credit staffs)

Credit officers

Managers/Vice managers

20 staffs

50 staffs

Credit department leaders

30 staffs

questionnaire is used to collect response of credit department leader group and credit officer groups

Before conducting survey, the researcher carries out depth-interview and pretest in order to increase quality of data collection

Depth-interview

Beside reviewing different aspects of four factors including credit information, technology, credit staff and loan policy via books, previous researches, the researcher will also carry out an depth interview in order to draw other practical aspects of the four factors such as: credit information selecting and systemizing, credit staff competence and technology matching, frequency of facility maintenance, important role of board of directors The objects of this interview are one manager and three credit department leaders

Pretest

A list of questions used for getting information from respondents (Appendix A) was created In order to improve the response rate, the researcher implemented a pilot test to refine the questions and make sure that respondents have no problems in understanding or answering those questions

This pilot test was conducted through a group of 10 people including one professor and four classmates from UEH, one manager and 4 BIDV credit officers The feedback from these people who have practical experience and academic knowledge helped the researcher to improve the questions in order to get the highest response

rate from respondents

1.5.3 Data analysis

The process of analysis begins after the data have been collected (G.Zikmund, 1997, p.507) Data collected must be analyzed in order to create meaningful findings for the study Data analysis plays an important role in analyzing the data If the collected data is not properly analyzed, the result may be invalid SPSS software version 16.0 was used for data analysis because of its many powerful statistical features The main objectives of the data analysis are to test the quality of the data collected and the hypotheses studied (Sekaran, 2003)

• Firstly, collected data must be recorded by using numerical codes By doing so, the researcher can input the data quickly into the system using the numeric keypad on the keyboard with very few errors

• Second, once the collected data is input and coded, the researcher can then enter them into the computer manually

• Finally, when the data has been already recorded and entered, the researcher can proceed to the data analysis phase

Data analysis technique

The study uses descriptive statistics to summarize the background information of respondents’ in the survey questionnaires The detail about the frequency and percentage of respondents’ working years, positions and backgrounds will be

showed in this section

Reliability measures were used to test the meaning of the different variable combinations The four hypotheses in this study are the assumptions about the effects of four variables to the effectiveness of credit risk management strategy Therefore, the survey questionnaire consists of 19 questions related to these four variables However, as it was difficult to test these hypotheses based on separate individual aspects, the researcher decided to combine different aspects of each variable into one Therefore, it was necessary for the researcher to test the meaning

of this combination process Cronbach’s alpha is a commonly used number to test the reliability of the combination of different individual variables The value of Cronbach’s alpha varies between 1 (perfect internal reliability) and 0 (no internal reliability) According to Bryman and Bell (2003), the value of 0.80 is an acceptable level of internal reliability However, many writers accept a slightly lower figure like Vogt (2007) argued that an alpha of 0.70 or higher is often considered satisfactory for most studies

An application of hypothesis testing is used to quantify respondents’ perception of research problem on a five-point scale, where 1 indicates strongly disagree and 5 indicates strongly agree The scale is assumed to be an interval scale T-test technique is used to estimate confidence intervals for the mean

The later chapter, chapter four: “Data analysis and findings” will discuss about analysis technique in detail

1.6 Significance of the study

This study helps readers realize the crucial importance of credit risk management and know the main factors that influence the reduction of non-performing-loan ratio

in BIDV

1.7 Structure of the study

Chapter 3: Case study of BIDV

Chapter 1: IntroductionChapter 2: Literature Review

Chapter 4: Data analysis and findings

Chapter 5: Recommendations and conclusions

Figure 1.6: Structure of the study This main purpose of the study is to understand the impact of credit information, technology, loan policy and credit staffs on reduction of non-performing-loan ratio

in BIDV Beside this chapter one currently discussed, the study also consists of the

following five chapters:

Chapter 2: Literature Review: This chapter will provide general theories related to

credit risk management Furthermore, the researcher’s insights on these theories will also be discussed

Chapter 3: Case study of BIDV: This chapter provides an overview of bank for

investment and development of Vietnam (BIDV) and BIDV’s credit risk management is the main part of this chapter

Chapter 4: Data analysis and findings: analyzing the collected data in order to get

results to test the hypotheses and answer the research questions in chapter one

Chapter 1: Introduction Page 13

Chapter 5: Recommendation and conclusion: based on these analysis and

findings from chapter five, some suggestions or recommendations about the credit risk management strategies that BIDV can adopt to manage credit risk will be given

2.2 Basic functions of banks:

In general term, a bank is an organization that engages in the business of banking -

it accepts deposits and makes loans Banks perform three basic functions: (1) They provide a leading role in the payment system; (2) They intermediate between depositors and borrowers by offering deposit and loan products; and (3) They provide a variety of financial services, encompassing fiduciary services, investment banking (underwriting original issues of stocks and bonds), and off-balance sheet risk taking (E.Gup & W.Kolari 2005)

Traditionally, the main activity of banks is to mobilize funds from those with surplus money to lend to those with shortage of money In other words, banks play

an intermediary role between suppliers of funds (depositors) and the users of funds

(borrowers) (Ritter, Silber & Udell 2000)

2.3 Lending business

2.3.1 The board of directors written loan policy

According to Benton E.Gup & James W.Kolari (Commercial banking, 2005, 251), a bank’s board of directors has the ultimate responsibility for all of the loans made by the bank Because the board delegates the task of making loans to others, it must have a written loan policy that establishes the guidelines and principles for the banks’ credit risk strategies and polices The credit risk strategy must recognize the goals of credit quality, earnings, and growth-that is the risk/reward tradeoff

p250-Loan policies vary widely from bank to bank The loan policy for a small bank that lends primarily to local customers is going to differ from the policy of a large bank that specializes in lending to business concerns In either case, the policy would state that the bank is in the business of making sound and profitable loans Therefore, the loan policy must make it clear that an important part of lending process is that all loans should have a repayment plan at the time the loan is made Other parts of the loan policy deal with:

• Loan authority: Who has the authority to make loans; the lending limits relative

to capital, deposits, or assets; the lending approval process

• Loan portfolio: the types of loans the bank wants to make, such as consumer loans, loan to start up businesses, loans to large businesses, farm loans, international loans, and so on The policy should also put limits on the concentration of particular types of loans

• Geography limits of the bank’s trade area where it may grant loans The overwhelming majority (97 percent) of small and medium-sized business use financial institutions within 30 miles of their principal office

• Policies for determining interest rates, fees, and contractual terms of the loans

• Limits and guidelines for off-balance sheet exposures from loan commitments, letters of credit, securitized loans, and derivative products (swaps, options, and futures, etc.)

• A loan review process to evaluate lending procedures and the quality of the loan portfolio

2.3.2 Lending procedure:

Lending procedure is the process that banks loans are provided to borrowers through proper evaluation of customers’ financial condition and credit worthiness (Rose & Hudgins 2008) According to Hempel and Simonson (1999), although different banks employ different methods to make their final lending decision, they normally follow the standard lending procedure described in the following basis steps:

Step 1: Receiving application: Customers including individuals and corporations

apply for a loan from banks by filling out a loan application

Step 2: Evaluating application: Bank credit officers evaluate the loan application

Evaluating loan request or by interviewing customers in order to investigate their characters and borrowing purpose Furthermore, the banks can collect customers’ information or credit history from the banks’ database when customers have existing relationship with the banks Other banks and credit information agencies are also other sources for banks to gather customers’ credit information

Step 3: Lending decision: Refusing application or Granting credit

Refusing application: If credit officers realize that the customer is ineligible for

receiving the bank loan, they may reject the loan application Credit officers will then issue a formal announcement on the loan application status to the customers within a certain period of time

Granting credit: If the loan application satisfies the requirements from the banks

then a loan agreement may be issued and signed between customers and authorized bank officer Other activities must be taken into account when the agreement is signed such as checking and collecting the property or other asset types considered

as collateral for the loans

Step 4: Monitor loan: After granting credit, credit officers must monitor customers

in order to ensure that customers use the loan accordingly with the purpose stated on the loan agreement In addition, as credit officers can quickly assess customers’ financial condition or their ability to pay the loan back by a proper monitoring process, banks managers and credit officers who are aware of the importance of this process can effectively help preventing their banks from credit losses

Step 5: Collecting loan: The duty of credit officers has not finished upon granting

the loan to customers Their last and important mission is to collect debt and liquidate credit agreement However, one of four things can happen to an outstanding loan: (1) It can be repaid on schedule; (2) It can be renew and extend; (3) The bank can sell the loan to another investor; (4) The loan can go into default and the bank may sustain losses The first three are desirable outcomes The last is the worst-case scenario for the bank

Before loans are granted, banks must evaluate the creditworthiness of the prospective borrowers (step 2) The borrower’s character, financial condition, and ability to repay the loan from future income or the sale of assets are of primary importance When the banks decide to grant a loan, all of the terms of the loan (credit facility, amount to be borrowed, the term of loan, method and timing of repayment, interest rate and fee, collateral if required, covenants or promises by the borrower to take or not to take certain actions during the term of the loan) are put into a contract called a loan agreement After the loan is granted, the bank must monitor the loan to assure repayment The best outcome is that the loan is repaid in full The worst outcome is that it is charge of as a loss

2.4 Credit risk in banks

2.4.1 Credit risk

Banking is the management of risk Banks accept risk in order to earn profits They balance alternative strategies in terms of their risk/return characteristics with the goal of maximizing shareholder wealth

According to Jane E.Hughes and Scott B.MacDonald (2002, p.297), a banker’s job

is to manage risk, not avoid it Banks face a variety of risks in their operations such

as: credit risk, market risk, liquidity risk, interest rate risk, operation risk, etc However, credit risk seems to be the most popular risk that most modern banks face due to their main business functions: lending and borrowing

Benton E.Gup et al (2005, p247) defined credit risk as: “The credit risk of banks is the risk of repayment, i.e., the possibility that an obligor will fail to perform as agreed Credit risk applies to loans, derivatives, foreign exchange transactions, the investment portfolio, and other financial activities

Based on the scope of this study, the above definition of credit risk is narrowed to

include only the lending activity of banks Credit risk is the risk that borrowers

may default on their loans, causing losses to the lender Therefore, if borrowers

pay back the promised amount of principal and interest of the loan at the specified time then the banks will bear no credit risk Otherwise, if borrowers settle a part of principal or interest to the bank, no matter how their willingness or capacity to repay the loan, then the banks will face credit risk, which means there is high probability that the banks will lose their money from the customers

Credit risk management plays an important role in preventing not only the banks’ lending business but also banks’ operations from failure (Madura 2006) Furthermore, because of their crucial role in the economy and society, banks are too important to fail The failure of any bank can cause highly negative effects to the household, the corporation sectors and the whole economy (Yarbrough &

Yarbrough 2006)

First, the problem of one bank may spread to others in the same country and around the world (e.g the recent subprime mortgage crisis in the U.S.) This is due to the nature of banking business in which banks tend to be so closely related to each other when doing business When funds stop flowing into one bank, other banks in the financial system that have placements or other credit positions with the failed bank will see themselves short of funds in-flow Again, banks who are behind these

“other banks” above-mentioned will face the same problem too This domino effect will eventually cause the whole banking system to collapse as it did during the recent financial crisis (Yehning, Hasan & Iftekhar 2008)

Chapter 2: Literature Review Page 19

Second, in market-oriented economies, banks channel fund from savers to those who have investment opportunities In order words, the role of banks is to improve the fluency of the flow of fund in the economy

Therefore, the more effectively banks can operate, the more fluency the flow of fund can be or the more opportunities that profitability projects get funding The problem

of one or few banks may become the problem of the whole banking system, the global economy and society If this is the case, savers will lose their savings and interest earning opportunities while entrepreneurs will lose their investment opportunities This will affect the development of the economy and the welfare of the society as fewer jobs are created Thus, credit risk management is not only important to one single bank but also to the whole banking system and the economy

2.4.2 Loan classification

The governor of the State Bank of Vietnam (SBV) promulgated a decision1 on loan classifications and provisioning for bad debts of credit institutions in 2005 Based on overdue indicator of debts, according to the article sixth of this regulation, a loan portfolio is classified into five groups as follows:

- Group 1 (standard debts): includes undue debt, whose principal and interest are

assessed by credit institutions to be fully recoverable when they become due Debts under this category are not subject to provisioning (0% rate of provisioning);

- Group 2 (debts to which attention shall be paid): includes debts overdue for less

than 90 days and rescheduled debts that are now no longer due according to rescheduled terms This group shall be provisioned at the rate of 5%;

- Group 3 (sub-standard): includes debts overdue between 90 and 180 days and

rescheduled debts overdue for less than 90 days according to the rescheduled terms This group shall be provisioned at the rate of 20%;

- Group 4 (doubtful debts): includes debts overdue for between 181 and 360 days

and rescheduled debts that are overdue for between 90 and 180 days

1Decision 493/2005/QD-NHNN dated 22 April 2005

according to the rescheduled terms This group is subject to a provisioning rate of 50%;

- Group 5 (debts with potentially irrecoverable principal): includes debts

overdue for more than 360 days, debts frozen pending the government’s handling, and rescheduled debts that are now overdue for more than 180 days according to the rescheduled terms This group shall be provisioned at 100% With respect to debt frozen by the government, specific provisions shall be set up according to the financial capability of the credit institution

In addition, according to the article seventh of the decision, credit institutions are allowed to classify loans based on their credit rating system when their risk provision policy was approved by SBV In this case, a loan portfolio is also classified into five groups

2.4.3 Loan loss provision

According to Greuning et al (2009), loan classification provides a basis for determining an adequate level of provision for possible loan loss In the decision number 493/2005/QD-NHNN, state bank of Vietnam regulates that loan loss provision contains general provision and specific provision:

Loan loss provision = general provision + specific provision

General provision is equal 0.75% multiply by total loan value groups from group 1

to group 4:

General provision = 0.75% x loan value of groups (1 + 2 + 3 + 4)

Level of specific provision is determined correlative to each group as below:

Loan group Level of specific provision

Total outstanding loansNPL ratio shows credit quality of a credit institution: high NPL ratio shows low credit quality

2.5 Credit risk measurement

2.5.1 Traditional approaches:

Adapted from Anthony Saunders (2002, p.9), it is hard to differentiate between the traditional approach and the new approaches since many of the better ideas of traditional models are used in the new models

The traditional approach is comprised of four classes of models

2.5.1.1 Expert Systems

In the expert system, the credit decision is left in the hands of the branch lending officer His expertise, judgment, and weighting of certain factors are the most important determinants in the decision to grant loans The loan officer can examine

as many points as possible but must include the five “Cs” these are: character, capital, capacity, collateral and cycle (economic conditions):

1 Character: A measure of the reputation of the firm, its willingness to

repay, and its repayment history In particular, it has been established empirically that the age of a firm is a good proxy for its repayment reputation

2 Capital: The equity contribution of owners and its ratio to debt (leverage)

These are viewed as good predictors of bankruptcy probability High leverage suggests a greater probability of bankruptcy

3 Capacity: The ability to repay, which reflects the volatility of the

borrower’s earnings If repayments on debt contracts follow a constant stream over time, but earnings are volatile (or have a high standard

deviation), there may be periods when the firm’s capacity to repay debt claims is constrained

4 Collateral: In the event of default, a banker has claims on the collateral

pledged by the borrower The greater the priority of this claim and the greater the market value of the underlying collateral, the lower the exposure risk of the loan

5 Cycle (or Economic) Conditions: The state of the business cycle; an

important element in determining credit risk exposure, especially for dependent industries For example, durable goods sectors tend to be more cycle-dependent than nondurable goods sectors Similarly, industries that have exposure to international competitive conditions tend to be cycle-sensitive Taylor (1998), in an analysis of Dun and Bradstreet bankruptcy data by industry (both mean and standard deviation), finds some quite dramatic differences in U.S industry failure rates during the business cycle

cycle-In addition to the 5 Cs, an expert may also take into consideration the level of interest rate

2.5.1.2 Artificial Neural Networks:

Due to the time consuming nature and error-prone nature of the computerized expertise system, many systems use induction to infer the human expert’s decision process The artificial neural networks have been proposed as solutions to the problems of the expert system This system simulates the human learning process It learns the nature of the relationship between inputs and outputs by repeatedly sampling input/output information

2.5.1.3 Internal Rating at Banks:

An internal rating system helps financial institutions manage and control credit risks they incur through lending and other operations by grouping and managing the creditworthiness of borrowers and the quality of credit transactions Financial institutions use internal rating system for originating and monitoring loans (Bank of Japan, August 2005)

Over the years, banks have subdivided the pass/performing rating category, for example at each time, there is always a probability that some pass or performing loans will go into default, and that reserves should be held against such loans Banks have developed internal rating systems for loans on a 1 to 9 or 1 to 10 scale

Bond Rating Score Risk Level

Table 2.2: Example of a loan rating system and bond rating mapping

Source: Adapted from Saunders A & Allen L, 2002

2.5.1.4 Credit Scoring Systems:

Adapted from Benton and James (2005, p.217-218), credit scoring is the use of statistical, operational research, and data mining models to determine the credit risk

of prospective borrowers The credit score is a number that is calculated by a credit bureau or another company, such as the Fair Isaac Corporation’s FICO score that is used in making credit decisions and for other purposes

The advantages of using credit scoring model are that they reduce the cost of evaluating credit and increase the speed, consistency, and accuracy of credit decisions

Credit scores are based on the past financial performance of groups of borrowers similar to the one being scored In general, a high credit score signals low credit risk Each lender has its own cut-off points depending on the risks it is willing to take Thus, a lender may use a rating system such as:

• FICO scores of 720 and above: Excellent credit

• 680-719: Good credit

• 620-679: Conditional credit

• 585-619: High risk credit

• 584 and below: Very-high-risk-credit

2.5.2 Modern approaches

2.5.2.1 Value At Risk (VAR):

Adapted from Anthony Saunders (2002), VAR is a technique used to estimate the probability of portfolio losses based on the statistical analysis of historical price trends and volatilities

By assuming financial institutions care about the odds of a really big loss on loans,

VAR answers the question, "What is my worst case scenario?" or "How much

could I lose in a really bad month?"

To be more specific, a VAR statistic has three components: a time period, a confidence level and a loss amount (or loss percentage) Keep these three let’s take note of this as we give some examples of variations of the questions that VAR answers:

• What is the most I can - with a 95% or 99% level of confidence - expect to lose in default on loan repayment over the next month?

• What is the maximum percentage I can - with 95% or 99% confidence - expect to lose over the next year?

2.5.2.2 Portfolio Approach

Since the 1980s, banks have successfully applied modern portfolio theory (MPT) to market risk Many banks are now using earnings at risk (EAR) and value at risk (VAR) models to manage their interest rate and market risk exposures Unfortunately, however, even though credit risk remains the largest risk facing most banks, the practical of MPT to credit risk has lagged (William Margrabe, 2007) Banks recognize how credit concentrations can adversely impact financial performance

As a result, a number of sophisticated institutions are actively pursuing quantitative approaches to credit risk measurement, while data problems remain an obstacle This industry is also making significant progress toward developing tools that measure credit risk in a portfolio context They are also using credit derivatives to transfer risk efficiently while preserving customer relationships The combination of these two developments has precipitated vastly accelerated progress in managing credit risk in a portfolio context over the past several years

2.5.2.2.1 Asset-by-asset Approach:

Traditionally, banks have taken an asset-by-asset approach to credit risk management While each bank’s method varies, in general this approach involves periodically evaluating the credit quality of loans and other credit exposures, applying a credit risk rating, and aggregating the results of this analysis to identify a portfolio’s expected losses The foundation of the asset-by-asset approach is a sound loan review and internal credit risk rating system A loan review and credit risk rating system enable management to identify changes in individual credits, or portfolio trends in a timely manner Based on the results of its problem loan identification, loan review, and credit risk rating system management can make necessary modifications to portfolio strategies or increase the supervision of credits

Banks increasingly attempt to address the inability of the asset-by-asset approach to measure unexpected losses sufficiently by pursuing a portfolio approach One weakness with the asset-by-asset approach is that it has difficulty identifying and measuring concentration Concentration risk refers to additional portfolio risk resulting from increased exposure to a borrower, or to a group of correlated

borrowers The below table summarizes strategies for reducing and coping with

portfolio credit risk

Technique Advantages Disadvantages Implication Geographic

Diversification

External shocks (climate, price, natural disasters, etc.) are not likely to affect the entire portfolio if there is spatial

diversification

If the country is small or the Institution is capital constrained, it may not be able to apply this principle

Loan Size

Limits

(Rationing)

Prevents the institution from being vulnerable to nonperformance on a few large loans

Can be carried to the extreme where loan size does not fit the business needs of the client and results in suboptimal use and lower positive impact by client

Client could become dissatisfied

Protects asset quality in the short run but creates client retention

problems in the long run Inimical to relationship

banking

Over

Collateralization

Assures the institution that enough liquidation value will exist for foreclosed assets

Excludes poor, low-income clients who are the vast majority of the market

Not a recommended

technique if goal

is to better serve the low- and moderate income clients

Credit

Insurance

Bank makes clients purchase credit insurance In event of default, bank collects from insurer

Databases and credit bureaus may not exist to permit insurer to engage in this line of business

in cost-effective manner

Portfolio

Securitization

Lender bundles and sells loans to a third party

Transfers default risk and improves liquidity so that it

can continue to lend

Allows lender to develop expertise in analyzing

creditworthiness in one sector or niche

Requires well documented loans and long time series of performance data

to permit ratings and reliable construction of financial

projections

Requires a well developed

secondary market, standardized underwriting practices, and existence of rating companies

Table 2.3: Strategies for reducing and coping with portfolio credit risk

Source: Adapted from Bank performance and credit risk management, Master

degree project of Takang Felix Achon, University of Skovde, Sweden

2.6 External factors that influence NPL ratio

Due to their unique business, banks always maintain certain level of credit risk in their operations in order to exchange for high profit at the end However, the current high level of credit risk in banks leads to the fragility of the global banking system This fact is further explained by the trend of deregulation, supervision and re-regulation, high competition in the banking system and the recent financial crisis The following sections will discuss the relationship between these trends and the level of credit risk in banks

2.6.1 Financial deregulation

Financial deregulation is defined by Casu, Girardone and Molyneuz (2006, p.37) as:

“The remove of controls and rules that in the past have protected financial institutions, especially banks” In the past, banks are strictly regulated by the

governments in order to ensure the stability of the country banking system Furthermore, governments tend to protect their domestic banks from competition, especially from foreign banks by setting complicated barriers and requirements However, at this time the operation of banks has expanded outside their domestic market because of the globalization trend Therefore, the control of government may harm their banks rather than protect them in such a high competitive banking industry Thus, financial deregulation is an inevitable trend in the modern banking system

The benefits from the financial deregulation come along with a variety of challenges derived from this kind of trend The loosening of banking control from governments leads to the fact that banks have more freedom in running their business However, this also means that banks must take responsibility for their business without hoping for protection from the governments As a result, modern banks are threatened by the high level of risk because they misused their freedom to extend their credit to high risk business

2.6.2 Supervision and re-regulation

Re-regulation is defined as: The process of implementing new rules, restrictions

and controls in response to market participants efforts circumvent existing regulations (Casu, Girardone and Molyneuz, 2006, p.38)

It is clearly stated in the above section that, the consequence of deregulation process

is the increasing level of credit risk in the current banking system Therefore, according to Hubbard (2008), countries’ governments around the world try to regulate the financial markets and institutions with the purpose of:

• Ensuring that all participants in the financial system have the opportunities to access to timely and accurate information in order to make their financial decisions

• Maintaining the stability and safety of the overall banking sector by preventing the failures of banks

Recently, a project named “Financial reform: a framework for financial stability” was launched by the group of thirty (G30) financial experts from the public, private sectors and academic in July 2008 By examining the global financial crisis, the project emphasized the importance of the supervisory systems, the role of central banks in managing risk especially credit risk in order to ensure the stability of global banking system (Williams 2009)

2.6.3 Competition

Before the deregulation process, in most countries, governments highly regulate and control the banking industry and protect domestic banks from competition especially from foreign banks The main objective was to ensure the stability of banking system and prevent banking crises (Lange et al 2007)

There are many opposite opinions about the role of competition in improving the stability of the banking system Smith (1984), Keeley (1990 and Repullo (2004) (in Schaeck et al 2009) and Benton E.Gup et al (2005) argued that high level of competition lead banks to involve in more riskier business while other theoretical studies done by Caminal and Matutes (2002) or Mishkin (1999) (in Schaeck et al 2009) stated that uncompetitive banking industry or concentrated banking system are more likely to encourage risk taking behavior by bank managers because bank managers believe that they will be bailed out by the government in case of failures Although the above opinions are reasonable, the first argument is proved to be more convincing with the supportive evidences from reality, especially from the recent

financial crisis There is no doubt that the increasing competition leads to a high

level of risk especially credit risk in banking industry Banks are now losing their

powers in lending business to the commercial paper market and securitization This fact threatens the profitability and the position of banks in the financial services industry and banks are forced to involve in other potential risky business: subprime mortgage loan and credit card to maintain their profit Thus, the lending business of banks is becoming more complicated for banks to monitor and control Banks are

facing challenges in monitoring these new activities due to the lack of expertise and resources (Mishkin 2007) As a result, this will cause the level of credit risk to become higher in modern banks and the current financial crisis is a result of this fact

2.6.4 The recent financial crisis

The recent financial crisis which started from the U.S has a great impact on the global financial system in specific and the world economy in general The collapse

of the housing market, the slowdown of the global economy, the difficulties of global financial system and the rising of unemployment rate are effects of this financial crisis which caused by the high level of credit risk in banks This fact encouraged financial experts and related parties around the world to think more seriously about risk management, especially credit risk management in banking industry (Brown & Davis 2008)

2.7 Internal factors that influence NPL ratio

Chau (2009) suggested the model for credit risk management strategy for Vietnam banks The model highlighted the importance of four main factors that have great impacts on credit risk management: accurate and timely credit information, skilled and moral banks staff, intensive investment on technology and innovation, well-defined and well communicated loan policy

2.7.1 Credit information

Credit information that banks collect for making lending decisions is in terms of borrower’s characteristics, loan purposes, the primary and secondary sources of loan repayment (Sinkey 1998)

This kind of information is crucial in the bank lending practices because it can help banks to determine the loan applicant’s willingness and capacity to implement the repayment obligation Therefore, credit information is one of the most important factors that can help banks reduce the level of credit risk by granting loan to the right customers Based on the importance of credit information, banks must have access to timely and accurate credit information because it is extremely difficult for banks to make lending decisions without such information Out-of-date and

inaccurate credit information may result in impairing of banks’ assets and profitability due to wrong lending decision (Thomas 2006)

In “Commercial banking” (2005), Benton E.Gup and James W.Kolari mentioned about the role of asymmetric information in credit risk management The inequality

of information between the bank and the borrower is called asymmetric information Simply stated, asymmetric information means that the borrowers have more information about themselves than is available to the banks and banks tend to attract the higher-risk borrowers (adverse selection) The asymmetric information also gives rise to a moral hazard problem after loan is made Moral hazard is the risk that the borrower, who now has loan, might use the funds to engage in higher-risk activities in expectation of earning higher returns The higher-risk activities increase the probability of default on the loan

Chau (2009) found the importance of credit information with four aspects including: the impact of credit information, source of credit information, credit information sharing and credit information checking in enhancing Vietnamese banks’ capacity

to manage credit risk

According to Hempel and Simonson (1999), banks should have reliable sources of credit information in order to improve the quality of credit and credit risk management capacity There are three fundamental sources that banks can collect credit information from: customers, internal bank sources and external sources available through institutions outside the bank However, there are some problems that may occur when collecting information from these sources:

First, there is a conflict interest between banks and borrowers in lending practices Obviously, borrowers will always have a better knowledge about their financial situation than banks do In some cases, borrowers tend to conceal their financial situation in order to get the loans from banks Thus, banks may be at risk if they make the wrong judgments based solely on this source of information

The second source that banks can collect credit information is the bank’s database if borrowers already have a relationship with the banks However, banks need to spend huge amounts of money to upgrade the technology system in order to be able to

store and analyze its internal information Furthermore, because this information is provided by borrowers so banks must carefully investigate the accuracy and timeliness of information

Third, banks can collect information from a third party outside the banks such as suppliers, credit rating agencies or other banks This can provide another reference source of information that can help banks make a right lending decision However, banks may again face the same dilemma as a result of the inaccurate third-party information

2.7.2 Technology

The development of technology is changing the way banks do their business, especially the lending business Banks now employ technology as an instrument in storing, transmitting and analyzing credit information to come out with the lending decisions Most consumer loan decisions are made today with the assistance of statistical techniques that can more accurately predict the probability of customers’ default With the support of technology, the credit analysis process now is becoming quicker and easier than before (Ritter, Silber & Udell 2000)

It is understandable to state that, the banking industry is information technology intensive because of its unique products and services which are related to the huge amount of customers’ money and confidential data Therefore many billions of dollars are spent annually by financial institutions worldwide in supporting information technology needs such as computer systems, and/or technological infrastructure to improve their competitive advantages (Seymann 1998)

Technology facilitates elimination of manual processes and allows information to be managed in an efficient and effective way Technology can help banks to lower their operating costs by increasing the productivity and accuracy of banks staff Therefore, it will result in higher profit for the banks Furthermore, technology is also considered a risk management tool for banks based on its functions in collecting, storing, processing and transmitting customers’ data (such as age, job, size of family or income) The above functions of technology can help banks to