Impact of credit risk on the financial performance of vietnamese banks

This study therefore investigates the impact of credit risk with focus on non-performing loans on the financial performance of commercial banks in Vietnam.. The analysis focuses on key c

Dissertation submitted in partial fulfillment of the

Requirement for the MSc in Finance

FINANCE AND INVESTMENT

Supervisor: Ph.D Pham Thu Thuy

DISSERTATION CONFIRMATION PAGE

Student’s name: DO TRUNG NGHIA

Student number: 23081362

Supervisor’s name: PHAM THU THUY

I, Pham Thu Thuy, hereby confirm that I have supervised the research and preparation of

the student’s dissertation I have reviewed the content, structure, and methodology used in the Dissertation and found it to be of satisfactory quality

I am confident that the Dissertation meets the requirements set forth by the University of the West of England and is ready for examination

Signature of Student and date Signature of Supervisor and date

Do Trung Nghia Date: 08 Sep 2024

Pham Thu Thuy Date: 08 Sep 2024

ACKNOWLEDGEMENTS

I wish to extend my deepest gratitude to Ph.D Pham Thu Thuy, my esteemed lecturer and research supervisor, whose steadfast commitment to academic excellence and tireless pursuit of knowledge have been pivotal to the completion of this Master’s thesis Ph.D Pham Thu Thuy’s profound expertise, insightful guidance, and uncompromising scholarly standards have consistently challenged and inspired me to push the boundaries of my research Ph.D Pham Thu Thuy, your mentorship has been invaluable, and for that, I am truly grateful

I would also like to express my sincere appreciation to the employees from the various banks who participated in this research Their generous contributions of time, insights, and perspectives have enriched the depth and quality of this study in immeasurable ways Without their cooperation and openness, this project would not have been possible

My heartfelt thanks also go to the faculty and staff of the Banking Academy Their unwavering support and the provision of a conducive academic environment have been fundamental to the success of my research The resources, intellectual community, and dedication to fostering a culture of academic inquiry at the Academy have inspired me throughout this journey

Additionally, I am deeply indebted to my teachers and friends, whose constant encouragement and understanding have provided me with the emotional and moral strength to persevere through the most challenging phases of this research Your support has been my foundation, and I am forever grateful for your kindness and belief in me

Finally, to all those—individuals and institutions alike—who have, in their own way, contributed

to the successful completion of this research, I extend my sincerest thanks This achievement is as much a testament to your support as it is to my efforts

Master of Science in Finance & Investment

Banking Academy

Hanoi, 08 Sep 2024

Research: Impact of credit risk on the financial performance of Vietnamese banks

Abtracts: The financial performance of banks across the globe is of utmost importance to its shareholders, managers, investors, regulators, and the general public This study therefore investigates the impact of credit risk with focus on non-performing loans on the financial performance of commercial banks in Vietnam Return on asset and Return on equity are used as measures of financial performance Internal bank factors such as the age and size of the bank are also considered Macroeconomic factors such as gross domestic product, inflation are included in the analysis Panel data spanning the period 2011 to 2023 on 26 commercial banks in Vietnam a is used for the analysis The results from the random effect estimation technique show that non-performing loans have a negative impact on both measures of financial performance studies have virtually ignored in the analysis of credit risk and financial performance nexus Model FEM - REM with Generalized Least Squares (GLS) techniques The analysis focuses on key credit risk metrics, including the Capital Adequacy Ratio (CAR), Non-Performing Loan Ratio (NPLs), Cost Efficiency Ratio (CER), Liquidity Ratio (LR), and Loan-to-Deposit Ratio (LDR) The analysis reveals mixed effects of various variables on financial performance metrics Non-Performing Loans (NPLs) negatively impact both Return on Equity (ROE) and Return on Assets (ROA), though the effects on ROA are statistically insignificant The Capital Adequacy Ratio (CAR) and Average Lending Rate (ALR) positively and significantly influence both ROE and ROA, indicating that higher capital and lending rates enhance profitability The Cost Efficiency Ratio (CER) significantly negatively affects ROE but has an insignificant impact on ROA, suggesting that cost inefficiency notably erodes equity returns The Liquidity Rate (LR) positively impacts both ROE and ROA, underscoring the importance of liquidity management Loan Loss Provisions (LLP) negatively affect ROE and marginally impact ROA, reflecting the strain of higher provisions

on profitability

Keywords: Credit risk, bad debt, financial performance, Vietnam commercial bank

Table of contents

CHAPTER 01: INTRODUCTION 1

CHAPTER 2 LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT 5

2.1 Credit risk 5

2.2 Bank performance 6

2.3 Relation between Credit risk and Bank performance 7

2.3.1 The theoretical literature 7

2.3.2 The empirical literature 9

2.3.2 Relation between Non-performing loan and financial performance 11

2.3.3 Relation between capital adequacy ratio and financial performance 13

2.3.4 Relation between cost-efficiency ratio and financial performance 14

2.3.5 Relation between average lending rate and financial performance 14

2.3.6 Relation between liquidity ratio and financial performanc 15

2.3.7 Relation between loan loss provision and financial performance 16

CHAPTER 3 DATA AND EMPIRICAL METHODOLOGY 18

3.1 Data 18

3.2 Model specification 19

3.3 Variable measurements 20

3.3.1 Financial performance of bank 20

3.3.2 Credit risk 21

3.4 Estimation strategy 27

CHAPTER 4 EMPIRICAL RESULTS AND DISCUSSIONS 29

4.1 Descriptive statistic 29

4.2 Impact on the profitability 39

4.3 Results of the effect of credit risk on the financial performance and hypothesis results 46

CHAPTER 5: RECOMMENDATION 56

5.1 Recommendation for commercial bank 56

5.2 Recommendation for State bank of Vietnam 60

CHAPTER 6 CONCLUSION AND IMPLICATIONS 65

6.1 Conclusion 65

6.2 Contribute and limitation 68

REFERENCES 72

APPENDIX 72

Discolosure statement 78

Additional information 78

Funding 78

Table of tables Table 1 :Summary of explanatory variables and dependent variables 25

Table 2: The descriptive statsitcs of of the variables 29

Table 3: Correlation analysis - the pairwise correlation matrix for variables 33

Table 4: VIF test 36

Table 5: The Hausman test results 37

Table 6: Testing for autocorrelation 38

Table 7: Heteroskedasticity tests 39

Table 8: Modified Wald test for groupwise heteroskedasticity in fixed effect regression model 40 Table 9: Wooldridge test for autocorrelation in panel data 40

Table 10: Regression results with fixed effects model of banking organizations 41

Table 11: Breusch and Pagan Lagrangian multiplier test and Wooldridge test 43

Table 12: Regression results with random effects model of banking organizations 44

List of Abbreviations

SIZE Size of banking organization BCBS Basel Committee on Banking Supervision IFRS International Financial Reporting

Standards

CHAPTER 01: INTRODUCTION

Banks act as profit-seeking intermediaries between borrowers and lenders in economies (Dietrich, 2017) Commercial banks’ position as financial intermediaries ensures that funds are directed into productive projects as documented by Hadad (Hadad, Hall, & Santoso, 2021) The role played by commercial banks in economies is crucial and cannot be overemphasized Moreover, commercial banks also provide capital for industries through loans, for expansion purposes Generally, economies and industries perform well when there is a robust and vibrant financial sector (Le & Thuy, 2020) It is acknowledged that commercial banks mostly accept deposits and give out loans—the principal operation of commercial banks (Nkem & Akujima, 2017), and also a significant source of income for the banks (Chipeta & Muthinja, 2018) However, in executing these important roles as financial intermediaries, commercial banks face different forms of risks due to the dynamic structure and the complex nature of the economic environment in which operate According to Sriyana et al, the risks faced by banks can be classified into 6 categories which including credit risk, liquidity risk, market risk, operational risk and legal risks (Sriyana, 2016) Each of these risks may lead to negative impacts on financial institutions' profitability, market value, liabilities, and equity The primary source of income of the banking sector consists

of loans granted by commercial banks Therefore, credit risk is one of the most important risks faced by banks Credit risk is defined by The Basel Committee on Banking Supervision, as the probability of partial or total loss of outstanding loan due to nonpayment of the loan on time An increase in credit risk raises the marginal cost of debt and equity and increases the cost of the bank's funding correspondingly (Wachter, 2018) A risk arising from a trading partner's failure to fulfill its contractual obligations on time or at any later time may considerably jeopardize the operation efficiency of the banking organization

A bank with a high credit risk has a high bankruptcy risk that endangers depositors The high level

of non-performing loans in the Bank's balance sheet reduces the bank's profitability and affects the operation efficiency Banks are exposed to credit risk more than the risks mentioned above Therefore, effective credit risk management in financial institutions has become vital for these institutions' survival and growth Through effective credit risk management, banks not only support the sustainability and profitability of the operations but also contribute to economic stability and efficient allocation of capital within the economy Gadzo et al emphasize that credit risk is the main risk faced by banks and other financial institutions (Gadzo, 2019), while Wireko

and Forson (2017) identify financial distress as a result of poor credit risk management Credit risk causes significant difficulties in both raising capital and developing credit products as well as maintaining relationships with other customers, leading to instability in their operations (Ozili, 2017) However, Tan argues that banks accept higher credit risk because they expect to be compensated by higher profits, and it is a trade-off situation (Poudel, 2012)

Kaaya indicates that credit risk is the costliest risk in commercial banking and has a tremendous effect relative to other threats faced by commercial banks because it directly impedes its soundness (Kaaya, 2013) In Vietnam, after a period of hot credit growth with many exposed risks, since

2011, the State Bank of Vietnam (SBV) has begun to strictly control the credit growth of the banking sector and considers it an important tool in managing monetary policy Since then, the financial situation and business activities of each commercial bank (CB) have become the basis for the SBV to annually assign specific credit growth targets On the part of CBs, in recent times, the structure of revenue sources has expanded and the proportion of non-interest income has increased However, with the characteristics of financial intermediation in banking activities, lending is still the key business of banks and credit risk always plays a dominant role in the health and operation of banks Credit risk is controlled at an appropriate level from the perspective of the country will greatly support economic growth, from the perspective of banks will help them achieve good profits from the main business Thus, in the context that lending is always an important channel of operation of banks and the economy, at the same time there are requirements for a transparent and unified credit management mechanism, understanding the factors affecting credit quality is a necessary issue, in line with the practice of state management and business development of social resources (Suela, 2019) After the global economic crisis in 2008 - 2009, the bad debt ratio at banks in Vietnam increased sharply above the recommended level of the State Bank of Vietnam (SBV) Moreover, the bad debt ratio in the banking system in Vietnam during this period could be four times higher than the reported level (Nguyen & Nguyen, 2021) Recently, due to the impact of the COVID-19 pandemic and the Russia - Ukraine conflict, the global economy fell into a severe recession and Vietnam is no exception The bad debt ratio tends to increase from the end of 2022 The increase in bad debt can lead to a capital crisis and depositors may lose confidence in banks, which can lead to mass withdrawals causing a systemic crisis According to statistics, by the end of June 2023, the bad debt ratio of the credit institution system was at 3.36% (1.69% at the end of 2020, 1.49% in 2021, 2022) The ratio of bad debt on the balance

sheet, debt at the Vietnam Asset Management Company (VAMC) that has not been processed, and potential debt that has become bad debt compared to the total outstanding debt was at 5.1% In the end of 2023, credit in the entire economy reached about VND 12,749 trillion, an increase of 6.92% The quality of corporate governance at banks in Vietnam is not uniform Good corporate governance will contribute to building a stable and sustainable banking system Banks that do well

in corporate governance can promote operations and improve business efficiency, improve access

to capital markets, reduce capital costs, increase asset value, and enhance corporate reputation One of the most important points of bank governance is risk management In Vietnam, several banks have completed risk management standards according to international standards Basel II, and Basel III, and are implementing international financial reporting standards (IFRS) However, the Vietnamese banking system has not achieved uniformity in applying these international standards Achieving international standards across the system helps prevent the negative impacts

of crisis events, limit losses, and spillover effects when a crisis occurs, and support more favorable post-crisis handling

From a theoretical perspective, many studies have examined the impact of credit risk on the profitability of commercial banks (CBs), but the results are inconsistent Some previous studies have shown the adverse impact of credit risk on the financial performance of commercial banks (Jacob, 2022) Other studies have shown that credit risk is positively related to bank profitability (Alshatti, 2017) In this context, several studies have stated the relationship between monetary policy, credit risk and financial performance of banks (Nguyen & Nguyen, 2021), but there is still

a lack of studies that directly address the relationship between credit yand bank performance in the context of pre- and post-financial crisis This leads to a research gap in determining the relationship between credit risk and financial performance of commercial banks with different measurements and reliable models, taking into account the impact of financial crisis Therefore, this study directly addresses this issue because of its important role in the Vietnamese economy The findings are expected to contribute both theoretical and practical in the context of an emerging country The study makes some contributions to literature and knowledge as far as the credit risk and financial performance of commercial banks are concerned More importantly, this study is executed after the roll-out of Basel II by bank of Vietname commercial bank that focuses on credit, market, and operational risks It is also prepare bank in Vietnam adoption of the International

Financial Reporting Standards (IFRS) 9 to be applied by banks in Vietnam for the impairment and provision of credit losses Therefore, the outcome of the study would be of great importance to policymakers, bank workers, bank executives, board members, and financial investors, among others It would help these group of individuals to take proactive measures to mitigate credit risk Furthermore, the findings would aid policymakers in developing correct structures to safeguard the financial performance of the banking industry This would then ensure that the banking industry

is robust and vibrant in order to continue its important role of expediting economic growth Finally, the present study uses an important financial performance measure economic value added which previous studies have not considered in the analysis of credit risk and financial performance nexus The remainder of this research is structured as follows: Section 2 encompasses a comprehensive literature review Section 3 elucidates the methodological framework employed in this study Moreover, Section 4 encapsulates a succinct synthesis of the principal findings and outcomes Ultimately, Sections 5 and 6 respectively expound upon the conclusions drawn and proffer recommendations stemming from this research endeavor

CHAPTER 2 LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT

2.1 Credit risk

The credit intermediation role of banks is fraught with the prime challenge of a credit default, borrowers not able to repay the loans obtained from their banks (Musyoki, 2022) The Merton (1977) default model introduced credit risk theory, which relates a firm’s credit risk to its capital structure in terms of its equity and debt obligation The failure of borrowers to meet their obligations to their banks will affect the capital structure of the banks Central banks are also faced with the challenge of ensuring that banks have adequate processes and procedures to safeguard them against delinquent loans through the periodic issuance of guidelines to banks and the imposition and implementation of sanctions when the guidelines are breached These actions by central banks are all geared to avoid chaos in the financial system and for terms and conditions of financial covenants to be mutually respected between banks and their customers Nonetheless, banks are poised to charge higher interest rates for credits with probable higher default risks (Roodman, 2019) The financial performance of banks must be balanced with how well their credit risk exposures are managed Moreover, it is expected that banks’ management teams will seek and deploy appropriate methodologies to manage their credit risk exposures, albeit within the boundaries of their respective central banks’ prudential guidelines and code of corporate governance (Alshatti, 2017)

Donald et al (1996) defined Credit risk simply as the potential that a bank borrower or counterpart will fail to meet its obligations by agreed terms The goal of credit risk management is to maximize the risk-adjusted rate of return by maintaining credit risk exposure within acceptable parameters Banks need to manage the credit risk inherent in the entire portfolio as well as the risk in individual credits or transactions The effective management of credit risk is a critical component of a comprehensive approach to risk management and is essential to the long-term success of any banking organization According to Tan et al , the banking industry has also made strides in managing credit risk (Tan, 2019) Until the early 1990s, the analysis of credit risk was generally limited to reviews of individual loans, and banks kept most loans on their books to maturity Today, credit risk management encompasses both loan reviews and portfolio analysis Moreover, the development of new technologies for buying and selling risks has allowed many banks to move away from the traditional book and hold lending practice in favor of a more active strategy that

seeks the best mix of assets in light of the prevailing credit environment, market conditions, and business opportunities Much more so than in the past, banks today can manage and control obligor and portfolio concentrations, maturities, and loan sizes, and to address and even eliminate problem assets before they create losses (Baidoo, 2019) Many banks also stress test their portfolios on a business line basis to help inform their overall management There are three stages in the credit process: the first is the simple risk control of the business avoiding being over-concentrated in any one sector, estimating the probability of defaulting, and assessing recovery

2.2 Bank performance

The performance of a company is a measure or indicator of whether a company can be said to be able to work well or not In the performance systematics itself, there are many separate factors and indicators of whether the company is said to be healthy or not so many companies are active in analyzing, evaluating, and arranging strategies in the hope of improving the company's performance The same is the case with the banking sector The bank itself makes the performance

of a bank an indicator of whether the bank is healthy or not which is measured within a certain maturity or period Assessment of a company's financial performance is one way that management can fulfill its obligations to funders and to achieve the goals set by the company Bank financial performance is a description of the bank's financial condition in a certain period, both in terms of raising funds and channeling funds, which are usually measured by indicators of capital adequacy, liquidity, and bank profitability

Bank profitability is a reflection of how banks are run given the environment in which they operate Healthy and sustainable profitability plays a vital role in maintaining stability in the banking sector (Wireko, 2017) However, it does not necessarily mean that profitability should be as high as possible because higher profitability may be an indicator of higher market power but lower competition, thus hindering improvements in efficiency and effective intermediation of savings However, lower profitability not only discourages private agents from conducting banking activities but decreases bank capacity to absorb negative shocks as well (Fama, 1985) Bank efficiency measures how inputs to the banking operation can be minimized to produce a certain amount of output or how to use a certain amount of inputs to maximize output production This reflects management’s skills at appropriately allocating input and output An important performance indicator and an alternative measure to bank efficiency, bank productivity has

received much attention from economists and policymakers and has been examined by empirical literature on European and transition economies (Kaimu, 2021) Similar to bank efficiency, bank productivity measures total output per unit input used in production Banks that demonstrate higher productivity indicate they can produce a certain amount of outputs using fewer inputs or can use a given amount of inputs to produce a higher quantity of outputs Bank productivity places much greater emphasis on the impact technology has on bank production than does bank efficiency According to Marshal , bank performance has two indicators, namely quality and quantity, while the dimensions of bank performance are the dimensions of profitability and risk (Marshal, 2016) Jalal also explains again that the measures used as a proxy for profitability are RoA (Return on Assets) and RoE (Return on Equity), while in the risk dimension, the measures used as a proxy are NPL (Non-performing loans) and LLP (Loan Loss Provision) According to Gitman and Zutter, Profitability is the ability of a company to generate profits Profitability is used as an indicator in measuring the performance of a bank Companies that generate good profits or profits will invite and attract investors to invest their funds Investors will see whether a company has financed in terms of good profits as well as healthy returns or returns According to Taswan, the measurement

of profitability at banks can use RoA and RoE RoA (Return on Assets) is the ability of a company

to manage its assets to generate profits by prioritizing the level of effectiveness and efficiency of its use RoA (Return on Assets) was chosen as an indicator for measuring financial performance because the RoA increases, the company's profitability also increases, so it can be said that the bank's financial performance is successful in following the wishes and goals of shareholders and the company, namely increasing profitability (Noman, 2015) RoE (Return on Equity) according

to Gitman and Zutter is a measurement of the return obtained on the investment of ordinary shareholders in the company Meanwhile, RoE (Return on Equity) according to Taswan is a ratio that measures a company's ability to generate net income from its equity capital

2.3 Relation between Credit risk and Bank performance

2.3.1 The theoretical literature

The theoretical and empirical literature underpinning this study are discussed in this section The theoretical literature the study considers includes the theory of information asymmetry, the theory

of moral hazard and adverse selection, the loan pricing theory, and the agency theory Stiglitz

(2002) defines information asymmetry as a situation where one party to an economic transaction possesses more information than the other party Spence (1973) proposes a more realistic assumption to back the theory of asymmetric information He opines that one party often has better knowledge of a deal than the other party It is common for a borrower to know more than the lender about their ability to repay a loan received Similarly, the seller of a product is more aware of the quality of the product than the buyer A company’s directors know more about the company’s actual performance than the shareholders Also, policyholders are more conscious of their exposure than the insurance provider Kane and Malkiel (Kane, 1965) and Fama (Fama, 1985) are of the view that a bank can only know about the characteristics of a borrower if it grants more loans to the borrower than if it relies on the borrower’s details It is simpler for a bank to estimate a borrower’s risk of default based on historical evidence Information asymmetry may lead to the bank, giving out bad loans even at the initiation stage of the loan process The presence of asymmetric information may result in banks’ financial performance ultimately being impacted by credit risk

Information asymmetry is closely linked to moral hazard and adverse selection Moral hazard and adverse selection are general concepts used in finance and risk management to characterize circumstances where there is a disadvantage to one party involved in a transaction A moral hazard occurs when asymmetric information arises between parties engaged in a contract That is when there is a change in one party’s behavior after signing the contract However, with adverse selection, asymmetric information between both parties is non-existent or is open to one party only The existence of asymmetric information makes it difficult for the parties to make the right decisions about the risk of the potential contract (Rwayitare, 2016) This theory is essential for many economic interactions Most contracts feature both adverse selection and moral hazards and loan contracts are no exception Borrowers often have more accurate information about their ability to repay a loan but may only give information that will favor them in the loan application process According to Akerlof, moral hazard is evident in the actions of both the lender and borrower, which may lead to a competitive bias and reduce the quality of products and services provided (Akerlof, 1970) Krugman defines a moral hazard as a scenario where one party chooses how much risk to take with the expectation that the other party must bear the cost should the event not go as planned (Krugman, 2009) Information asymmetry is the root cause of moral hazard and adverse selection Gladwell indicates that the theory of moral hazard and adverse selection has a

major effect on banks and may lead to lower profits, lower liquidity, and higher pricing of loans Moral hazard and adverse selection can result in borrowers not repaying loans, and this can cause

a substantial increase in credit risk and thus impact on financial performance (Gladwell, 2019) Furthermore, what determines the price of a loan are the actual cost of the loan, profit, and risk premium The loan pricing theory suggests that banks consistently fix extreme lending rates According to Sakyi, the problem of moral hazard, adverse selection, and asymmetric information should be taken into consideration when setting loan rates to ensure interest income maximization (Sakyi, 2021) Stiglitz (Stiglitz, 2012) reports that after obtaining loans and advances, most borrowers develop moral hazard habits by engaging in riskier ventures The pricing of a loan affects the overall volume of loans that will be disbursed Without conducting proper due diligence

to assess moral hazard behaviors, risky loans will be priced lower than they ought to and therefore raise credit risk should loan default occur High lending rates can cause an adverse selection problem attracting risk-averse borrowers only This may lead to a reduction in loan portfolio diversification and increase concentration within a customer base, which can also significantly increase credit risk

Last but not least, the agency theory indicates that there are conflicts of interest between bank shareholders and management Unfortunately, these conflicts of interest incur agency costs to the principal–agent arrangement between debtors and shareholders of commercial banks (Yeasin, 2022) The credit risk between commercial banks and their debtors rises when shareholders get involved in the financing of investments Banks will make tremendous gains from the success of these risky financial investments The credit risk loss of these investments, however, is entirely borne by the bank and affects its financial performance

2.3.2 The empirical literature

Financial performance of commercial banks is a prerequisite for the success of commercial bank performance assessment in the context of increasing competition in the financial market Therefore, bank management must achieve high financial performance to meet the expectations of stakeholders before achieving any other goals However, the stability and survival of banks as well

as the financial system are mainly determined by the ability of banks to manage credit risk (Umoh, 2019) This puts banks in front of trade-offs, especially in difficult economic contexts Herald et

al argued that the level of credit loss provisioning is a consequence of previous credit risk, it

increases operating costs and reduces the financial performance of banks because of reduced profits (Herath, 2021) Therefore, bad debts or provisions for credit losses are often considered as the output of credit risk in previous studies (Dietrich, 2017) Tan argues that there is a trade-off between risk-taking ability and financial performance of banks (Tan, 2019) Once banks are exposed to higher credit risk, they usually expect to earn higher profits However, the financial performance of banks may be reduced when they are exposed to potential credit risks, such as failure to collect previous loans Some studies show a positive association between credit risk and financial performance of banks (Embaye, 2018) Other studies have shown unfavorable results (Oketch, 2018) A firm can manage its internal factor effectively, then the firm can be high profitability, while, on the other hand, these factors are mismanaged It would adversely affect the firm's balance sheet and income statement (Nguyen Q K., 2022) Different authors discuss different bank-specific variables and firm performance in their studies The bank-specific variables used in this study are cost-efficiency ratio (CER), average lending rate (ALR) and liquidity ratio (LR) Aspal et al (2019) used two types of factors (macro and bank-specific factors) and inspected their connection with the financial performance of the commercial bank in India (Ajao, 2019) Gross domestic product (GDP) and inflation are used as proxies of macroeconomic factors

A bank-specific variables’ proxy includes capital adequacy ratio, asset quality, management efficiency, liquidity and earnings quality Data of 20 private banks have been used from 2008 to

2014 The panel data pointed out that one macroeconomic factor is significant (GDP), and another factor (Inflation) is insignificant All bank's specific factors (earning quality, asset quality, management efficiency and liquidity) significantly affect the financial performance except the CAR (insignificant) Haile et al (2018) conducted their study to explore the nature of the interrelation between bank-specific (BS) and macroeconomic determinants with the banking performance of Azerbaijan (oil-dependent economy) (Haile, 2022)

On the empirical front, some studies have also been conducted For instance, (Nguyen & Nguyen, 2021) examine the link between banks’ profitability and credit risk in Vietnam The study shows a significant positive relationship between profitability and credit risk measured by net charge-off rate, pre-provision profit as a proportion of overall new loans and advances and non-performing loan rate A positive relationship is also revealed between profitability, bank growth, bank depth capital, and bank size Similarly on Ghana, using return on asset (ROA) and return on equity (ROE)

as measures of financial performance and capital adequacy ratio and non-performing loans as

measures of credit risk, Khai (Nguyen Q K., 2022) reveal a significant positive relationship between banks’ profitability and credit risk Also, Marshal and Onyekachi investigate the relationship between credit risk and performance of selected banks in Nigeria (Marshal, 2016) The results show that bank performance and non-performing loans to loan advances are positively related In a related study, Suela assesses the influence credit risk has on commercial banks’ performance in Nigeria (Suela, 2019) The findings reveal that credit risk has a significant negative effect on the performance of banks Also, loans and advances to total deposit are revealed to have

a negative effect on banks’ performance A similar result is obtained by Ebenezer and Omar (2016), also for Nigeria Again, Noman et al reveal that credit risk impacts negatively on financial performance of banks in Bangladesh (Noman, 2015) The study measures financial performance using return on asset, return on equity and net income margin

2.3.2 Relation between Non-performing loan and financial performance

Credit risk is measured using capital adequacy ratio, loan loss ratio to gross loans, non-performing loans to gross loans and loan loss ratio to non-performing loans When a commercial bank cannot collect the expected amount from the borrower in the form of interest and principal amount within

90 days, it is called a non-performing loan or NPL In other words, NPLs are also known as bad

or impaired loans Commercial banks consider these loans as risky assets, and they can significantly affect their performance NPL is used by many researchers as a significantly strong indicator to identify the management’s approach regarding credit risk and its impact on bank performance A bank's management should implement the proper guidelines of the State Bank of Pakistan and the Basel Accord with reference to risk (Suyanto, 2021) As postulated by some prior research, NPL and bank performance have a negative relationship (Sheikhi, On a generalization of the test of endogeneity in a two stage least squares estimation , 2022)

Furthermore, Kolapo investigates the relationship between credit risk and profitability of banks (Kolapo, 2022) The results indicate that the effect of non-performing loans to total loans and advances on profitability (measured by return on asset) is positive It is also observed that bank size and profitability are positively related Sheikhi et al investigate the influence of credit risk on commercial banks’ profitability in the United Kingdom (Sheikhi, On a generalization of the test of endogeneity in a two stage least squares estimation., 2022) Profitability is measured using return

on asset and return on equity, whereas credit risk is proxied by impairments and non-performing

loans The results show that there is a positive relationship between credit risk measures and the profitability indicators Gadzo (Gadzo, 2019) also show that credit risk (measured by capital adequacy ratio, non-performing loans, and loan loss provision) has a negative effect on banks’ profitability (measured by net profit margin, return on equity and return on asset) The results further indicate that macroeconomic variables such as consumer price index, gross domestic product, and interest rate have negative effect on profitability In a related study, Bhattarai (2023) reveals that banks’ performance is negatively impacted by the non-performing loan ratio Cost per loan assets has a positive impact on banks’ performance (Bhatt, 2023) Bank size is revealed to have a positive relationship with banks’ performance However, the effect of capital adequacy ratio and cash reserve are insignificant

Nguyen shows that the NPL ratio of commercial banks in Vietnam plays a decisive role in financial performance, captured by ROA and ROE during the period 2012-2021 (Nguyen & Nguyen, 2021) This can be explained by the extremely high interest rates that banks charge based on their high-risk potential, leading to high profits in these cases Conversely, some studies on the credit risk of commercial banks indicate that it harms financial performance Cheng studied the role of credit risk and the performance of commercial banks in China, using additional variables to measure the cost of each loan (Cheng, 2020) The findings indicate that the NPL ratio and capital adequacy ratio have a statistically significant negative impact on ROA; while cost per loan has a marginally positive impact on ROA NPLs and operating costs play a significant role in reducing the financial performance of private commercial banks in China This seems to be contrary to the view in previous studies that credit risk indicators are usually positively related to profitability, based on the trade-off view

Le investigated the negative impact of bad debt on financial performance but did not find a significant impact of credit loss provision on financial performance (Le & Thuy, 2020) Nguyen used credit loss provisions as a measure of credit risk, showing that credit risk negatively affects the financial performance of banks (Nguyen Q K., 2022) The authors argue that banks with higher capital adequacy are willing to take risky investments to obtain high profits, contributing to improving profitability under uncertain conditions However, studies on this topic have not yet presented a clear picture in Vietnam, especially in the context of the financial crisis Therefore, this study continues to inherit previous studies to explore the relationship between credit risk and the financial performance of banks in the context of Vietnam In summary, according to Musyoki

and Kadubo (2012) and Alshatti (Alshatti, 2017), credit risk is considered to cause difficulties in recovering bad debts as well as increase the cost per bank asset Therefore, high credit risk leads

to high costs while reducing the return cash flow Based on the above arguments, the study proposes:

Hypothesis 01: There is a negative and significant relationship between NPLs and commercial banks' financial performance

2.3.3 Relation between capital adequacy ratio and financial performance

The capital adequacy ratio (CAR) is a key financial metric that measures a bank's ability to absorb potential losses arising from its operations and assets, particularly loans and investments It is a critical aspect of bank regulation and supervision aimed at ensuring the stability and soundness of financial institutions CAR determines the organisation's performance and is used to examine the strength of a financial organisation Banks with adequate CAR can generally absorb the losses

of expected risk, meet financial obligations, and provide sustainable shelter to avoid solvency For

an ideal financing structure, banks should use the combination of debt and equity, which would help them improve the values of common and preferred stock Capital adequacy has two types Tier I capital adequacy emphasises absorbing losses, while Tier II assures the safety of depositors

by making such strategies which aim to avoid losses The results of the past research show the positive effect of CAR on bank performance (Akbar, 2023) On the other hand, some researchers exhibited a negative relation between CAR and bank performance (Wahyuni et al., 2023) This study hypothesises that CAR negatively affects bank performance Oluwafemi et al (2013) conducted their study to check the relationship between credit risk and monetary gain of the banking sector and used NPL and CAR as indicators of credit risk Blum and Hellwig (1995) pointed out that CAR are the amounts kept by the banking sector that protect them from insolvency risk, while NPLs is the amount not being paid even after the due date of 90 days has been passed And after performing the analysis, results imply that both factors, CAR and NPL, affect the ROE, but the CAR is less significant than NPL Adebayo et al (2011) conduct the Russia on the emerging problem of credit risk management and investigate the nature of the relationship with the profitability of the rural banks NPLs are used as the proxy of credit risk, while ROE and ROA calculated proxies to quantify the financial performance The study results show a significant positive interrelation between NPLs and bank financial performanc as the loan losses increase the

performance and profitability, showing an increasing trend Some other researches (Adebayo et al, 2011; Oluwafemi et al, 2013; Chimkono et al, 2016) also conduct their studies to examine the nature of linkages between credit risk and financial performanc of banks; a chunk of studies found

a negative relationship between credit risk and banks’ financial performing, while others found positive and insignificant relationship between both factors Therefore, the situation is not clear The present study uses this phenomenon and NPLs The capital adequacy ratio is used as two proxies of credit risk and checks its relationship with Vietnam financial performing banking sector Based on the abovementioned discussion, our study develops these two hypotheses:

Hypothesis 02: There is a positive and significant relationship between capital adequacy ratio and commercial banks' financial performance

2.3.4 Relation between cost-efficiency ratio and financial performance

The cost efficiency ratio is the ratio of how to efficiently and effectively control the operating cost

of a bank Berger and DeYoung (1997) conduct their study on problem loans and cost-efficiency

in commercial banks and make four hypotheses, and one hypothesis is related to bad management (cost-efficiency) When management has less or no control over their operation and cannot perform

in their day-to-day operation, the result of all inefficiencies that their loan portfolio crease and CER also increase Studies (Berger and DeYoung, 1997; Chimkono et al., 2016; Ghosh, 2015) were conducted to determine the relationship between the CER and financial performance Some studies pointed out a significant negative relationship between the CER and financial performance

At the same time, some other researchers conclude a positive or insignificant relationship between the CER and financial performance Therefore, there is much contradictory situation that exists Based on the literature of CER and financial performance, the following hypothesis is developed:

Hypothesis 03: There is a negative and significant relationship between the cost effiency ratio and commercial banks' financial performance

2.3.5 Relation between average lending rate and financial performance

Lending is considered the heart of the banking sector, so commercial banks mainly engage in lending and earn their profits Monetary authorities also use the lending rate as a tool to control the economy of a country (Chimkono et al., 2016) Suppose banks or monetary authorities increase lending rates, then in order to compensate for this high lending rate In that case, investors usually

invest in a high-risk project, which increased the chance of default (Hamza, 2017) A chunk of empirical studies tested to investigate the tie-up between the ALR Adebayo et al (2011) organized the research paper in Nigeria from 2000 to 2010 to ascertain the linkages between bank lending rate and performance The result of the data shows that in the short and as well as in the long run, there is a significant positive relationship between the lending rate of a bank and the performance

of a bank Likewise, some other studies (Chimkono et al., 2016; Hamza, 2017) also pointed out a positive relationship between the lending rate of a bank and the performance of a bank; on the handsome, other studies pointed out a negative or insignificant relationship between the lending rate and firm performance, so the situation is still not clear After examining previous literature, a hypothesis is developed between the ALR and financial performance:

Hypothesis 03: There is a positive and significant relationship between the average lending rate and commercial banks' financial performance

2.3.6 Relation between liquidity ratio and financial performance

Bank liquidity is vital in determining a commercial bank's overall performance and stability It affects a bank's risk management capabilities, depositor confidence, funding costs, lending capacity, investment opportunities, regulatory compliance, market perception, stress resilience, and operational efficiency Francis et al (2015) define liquidity as, the liquidity of an asset, determined by how quickly this asset can be converted or transferred into cash Liquidity is used

to fulfill short-term liabilities rather than long-term (Siddique et al., 2020; Raphael, 2013) Adebayo et al (2011) mentioned banks are unable to pay the required amount to their customers,

it is considered bank failure Sometimes liquidity risk affects the whole financial system of a country Banks that balance short-term liquidity needs and long-term growth goals are better positioned to navigate the challenges and capitalize on the opportunities available in the financial landscape Bank liquidity is directly associated with the bank's performance; as the value of liquidity changes, it changes the sustainable performance of the bank Many other factors bring changes in liquidity value that result in insolvency or failure of the bank The better management

of banks for the value of liquidity can bring positive changes in the value of this variable Many researchers (Awaluddin et al., 2023; Zamore et al., 2023) have stated that bank liquidity significantly affects the sustainable performance of commercial banks This study hypothesizes that bank liquidity positively affects bank performance Financial performance and liquidity, on

the other hand, a chunk of studies (Francis et al., 2015; Hamza, 2017) revealed significant negative tie-up between liquidity and financial performance, while some other studies pointed out that there

is no significant relationship between liquidity and financial performance Therefore, the studies show a contradictory result, so the current study takes the bank-specific measures (LR, ALR study and CER) and checks its interconnection with commercial banks' financial performance Therefore, the studies show a contradictory result, so the current study takes the bank-specific measures (LR, ALR study and CER) and checks its interconnection with commercial banks' financial performance Different other studies conducted used macroeconomic factors (Accornero

et al., 2018; Hamza, 2017; Ghosh, 2015), but the current study is based on bank-specific factors (unsystematic risk) because this risk could be controlled by effective management risk and financial performance The study used few important bank-specific variables (LR, ALR study and CER), as well as NPLs and capital adequacy and check their relationship with the financial performance of commercial banks The liquidity ratio and financial performance hypothesis are given as:

Hypothesis 05: There is a positive and significant relationship between the liquidity rate and commercial banks financial performance

2.3.7 Relation between loan loss provision and financial performance

Loan-loss provisioning policy is critical in assessing financial system stability, in that it is a key contributor for fluctuations in banks’ profitability and capital positions, which has a bearing on banks’ supply of credit to the economy (Beatty and Liao, 2009) In principle, loan loss provisions allow banks to recognize in their profit and loss statements the estimated loss from a particular loan portfolio(s), even before the actual loss can be determined with accuracy and certainty as events unfold and are actually written off In other words, loan-loss reserves should result in direct charges against earnings during upturns in the economic cycle, as banks anticipate future losses

on the loan portfolio when the economy hits a downturn When these anticipated loan losses eventually crystallize, banks can then draw on these reserves, thereby absorbing the losses without impairing precious capital and preserving banks’ capacity to continue extending the supply of credit to the economy Ideally, the level of loan loss provisioning, should be able to reflect the beliefs of bank management on the quality of the loan portfolio that they have, indicating that provisions should be able to cover the whole spectrum of expected credit losses if they are to think

of provisions as a measure of true credit risk (Dugan, 2009) For another, accounting frameworks only allow provisioning for losses that have already been incurred as of a financial statement date, which does not really address the concept of “expected losses” (Li, 2009) Moreover, a surplus of funds relative to the appropriate level of prudent loans being granted could lead to the chasing of yields and the lowering of credit risk perception, and hence, corresponding provisions If provisions are not able to cover the whole spectrum of potential loan defaults once an economic downturn occurs, then, naturally, the bank will need to cover the excess loss from its capital Ramlall (2009) & Miller and Noulas (1997) stated the negative relationship between credit risk and profitability It shows that whenever there is negative relationship between them, then it signify that greater risk linked with loans, higher the level of loan loss supplies which thereby and create

a trouble at the profit-maximizing strength of a bank

Hypothesis 06: There is a neagtive and significant relationship between the loan loss provison and commercial banks financial performance

CHAPTER 3 DATA AND EMPIRICAL METHODOLOGY

3.1 Data

This research used annual data of 27 listed Vietnam commercial banks from 2011 to 2023 because research can access publicity of data sources The total charter capital of the 27 listed banks selected in the study is 671,571 billion VND (equivalent to 27.51 billion USD) at the end of 2023, compared to the total charter capital of 37 commercial banks of 705,043.32 billion VND (State Bank of Vietnam, 2024) In Vietnam, there are currently 49 banks, including the following banks: State Bank, joint stock commercial banks, joint venture banks, foreign bank branches in Vietnam and banks with 100% foreign capital Non-listed banks are mainly joint-venture banks and foreign bank branches in Vietnam and 100% foreign-owned banks with insignificant capital compared to the total banking industry (Except Agribank and SCB) Therefore, the research sample is highly representative and significant to the whole banking organization The researcher selected yearly data from the year 2011 to the year 2023 (base on post-audited yearly financial report) to fill the time research gap of previos research of Trang (2020) and Vo (2020) The data for this study was obtained from the the several yearly financial statement and post-audit consolidated financial statements of Vietnamese commercial banks Subsequently, the researcher purposefully adopted for banks that furnished comprehensive financial reports, encompassing the balance sheet, income statement, cash flow statement, and accompanying financial notes Additionally, supplementary data sources were judiciously integrated into this analysis, incorporating Fiin Pro, data sourced from the State Bank of Vietnam, information gleaned from the websites of the scrutinized commercial banks, as well as data from the General Statistics Office of Vietnam, Foreign commercial banking in Vietnam and the Ministry of Finance Once collected, the data underwent

a process of importation into an Excel file, where it was meticulously reviewed, edited, and encoded Subsequently, the data underwent a rigorous data cleaning procedure, designed to identify and rectify errors, address empty cells devoid of information, rectify inaccuracies, and ultimately ensure the completeness of the data matrix Following this data cleaning stage, the researcher utilized Stata 17 software to perform calculations and process the data in accordance with the specified model

3.2 Model specification

This research has one problem variable, financial performance, while regressors variables are credit risk and bank-specific variables Our model is consistent based on the research of Ameni Ghenimi (2017), the author uses a model to show the impact of credit risk on the financial stability

of Vietnamese commercial banks ROA and ROE will be used as a measure of financial performance, while credit risk will be measured by NPL ratio and LLP ratio and five specific variables: CER, LR, ALR, CAR, SIZE and AGE Various studies (Hamza, 2017; Belas, 2018) emphasize some macro and micro variables that need to be controlled when measuring financial performance because these factors are the influential factors Two control variables: growth rate

of GDP (GDP) and inflation (INF) are used in this model

Due to the nature of the data, the panel estimation technique is appropriate in this research In addition, the heterogeneity among the individual banks is taken into consideration by the panel estimation technique (Kwashie et al., 2021) The equations are specified as follows:

𝑅𝑂𝐴𝑖,𝑡 = 𝛼𝑖,𝑡 + 𝛽1𝑁𝑃𝐿𝑖,𝑡+ 𝛽2CER𝑖,𝑡+ 𝛽3𝐶𝐴𝑅𝑖,𝑡+ 𝛽4𝐴𝐿𝑅𝑖,𝑡 + 𝛽5𝐿𝑅𝑖,𝑡 + 𝛽6𝐿𝐿𝑃𝑖,𝑡 + + 𝛽7𝐼𝑁𝐹𝑖,𝑡 + 𝛽8𝐴𝐺𝐸𝑖,𝑡+ 𝛽9𝐺𝐷𝑃𝑖,𝑡 + 𝛽10𝐶𝑅𝐼𝑆𝐼𝑆𝑖,𝑡 (1)

𝑅𝑂𝐸𝑖,𝑡 = 𝛼𝑖,𝑡 + 𝛽1𝑁𝑃𝐿𝑖,𝑡 + 𝛽2CER𝑖,𝑡+ 𝛽3𝐶𝐴𝑅𝑖,𝑡+ 𝛽4𝐴𝐿𝑅𝑖,𝑡+ 𝛽5𝐿𝑅𝑖,𝑡 + 𝛽6𝐿𝐿𝑃𝑖,𝑡+ + 𝛽7𝐼𝑁𝐹𝑖,𝑡 + 𝛽8𝐴𝐺𝐸𝑖,𝑡+ 𝛽9𝐺𝐷𝑃𝑖,𝑡+ 𝛽10𝐶𝑅𝐼𝑆𝐼𝑆𝑖,𝑡 (1)

The author considers the financial crisis conditions by adding the dummy variable CRISIS to the model The variable CRISIS takes the value of 1 to represent the crisis conditions from year 2020

to 2023, and takes the value of 0 to represent normal conditions in the remaining years of the research period (from 2011 – 2019)

Within the framework of banking performance and risk assessment, the following econometric models are employed to examine the interplay between key financial metrics and bank outcomes The performance and fund diversify model is expressed above with ROA representing the return

on assets ratio, ROE signifying the return of equity ratio, and the coefficients β0 (the intercept),

β1, β2, β3, β4, β5, β6, β7, β8, β9 and β10 are the coefficients of the respective independent

variables to be estimated, and ε is the error term

The indices i and t represent the number position of i bank in year t, and I,t represents the individual-specific effect that remains constant over time These models offer a comprehensive framework for evaluating credit risk and bank financial performance by considering various financial indicators and their associated coefficients of profitability of commercial bank in Vietnam

3.3 Variable measurements

3.3.1 Financial performance of bank

The dependent variable, financial performance, in this study is measured by return on asset and return on equity This study uses these indicators because of the advantages over other measures such as net interest margin (NIM) For instance, NIM has been criticized for not explaining the extent to which management maximizes shareholders’ wealth (Kadar & Rikumahu, 2018) According to Sinkey (1992), ROA and ROE is best for evaluating the performance of commercial banks because it takes into consideration differences due to financial leverage and avoids distortions Sinkey further adds that ROA offers better information to bank management to influence the decisions which may contribute to the development of the largest shareholder wealth The Stern Stewart Corporation (Stern & Shew, Citation1995) notes that ROE is the best and most realistic measure of performance as it is more accurate in estimating an organization's actual economic profit

Return on assets is a financial performance proxy used to show earnings from how a bank’s assets are used over a given time frame ROA and ROE shows the proportion of how profitably the bank’s assets and equity are used in income generation It is a portion of a company’s income to its total assets It shows how effective the performance of the banks’ management is regarding profit generation from limited resources

𝑅𝑂𝐴 = 𝑁𝑒𝑡 𝑖𝑛𝑐𝑜𝑚𝑒

𝑇𝑜𝑡𝑎𝑙 𝑎𝑠𝑠𝑠𝑒𝑡𝑠 (1)

𝑅𝑂𝐸 = 𝑁𝑒𝑡 𝑖𝑛𝑐𝑜𝑚𝑒

𝑇𝑜𝑡𝑎𝑙 𝑒𝑞𝑢𝑖𝑡𝑦 (2)

3.3.2 Credit risk

With regard to the independent variables, non-performing loans are critical indicator of credit risk

in commercial banks Non-performing loans are measured by the percentage of loan defaults against the aggregate volume of the bank’s loans This study expects non-performing loans to affect banks’ financial performance negatively This is because, a higher non-performing loan implies that a higher percentage of loans disbursed are not recouped and this apparently impacts on the financial performance of the bank negatively Results from Herath et al(2021), and Yeasin (2022) have indicated a negative relationship between non-performing loans and financial performance

of commercial banks In Vietnam, bad debt is defined as debt in groups 3, 4 and 5 according to Circular No 08/2017/TT-NHNN dated August 1, 2017 of the State Bank of Vietnam The credit loss provision ratio measures the amount identified and accounted for in operating expenses to prevent possible debts A higher ratio implies a worse quality of the loan portfolio, and it is positively correlated with bad debt and high credit risk (Alshatti, 2015)

𝑁𝑃𝐿 =𝑁𝑜𝑛 𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑖𝑛𝑔 𝑙𝑜𝑎𝑛

Loan loss provision (LLP) is an accounting practice used by banking institutions to recognize potential losses from non-performing loans (NPLs) Banks set aside a portion of their income as provisions to cover anticipated loan defaults, ensuring that their balance sheets reflect the risk of credit losses Loan loss provisions are crucial for maintaining a bank's financial health, risk management, and regulatory compliance, especially in periods of economic uncertainty when loan defaults are more likely to increase Loan loss provisioning is rooted in the principles of prudential regulation and accounting standards aimed at ensuring that banks maintain sufficient reserves to cover credit losses Provisions are an essential part of credit risk management, allowing banks to prepare for future loan defaults and mitigate the adverse effects on their profitability and capital adequacy

LLPR = Provision for credit losses/ Total loans and advances (4)

3.3.3 Bank specific factors

Capital adequacy ratio is the proportion of the bank’s available resources to its risk-weighted credit exposures It also refers to the bank’s holdings of equity capital and other securities as buffers against volatile assets Through its effort to control capital adequacy globally, the Basel Committee

on Banking Supervision (BCBS) expects internationally operating banks to have a capital adequacy ratio of at least 8% However, for commercial banks in Vietnam, the minimum threshold CAR as target by the SBV must reach at least 10 - 11% in 2023 and at least 11 to 12% in 2025 The capital adequacy ratio measures the financial ability of a bank which is tracked continuously

by regulators Theoretically, banks with a sound capital adequacy ratio have excellent financial performance A bank with a reliable capital adequacy ratio may bear any losses and prevent insolvency This study expects the relationship between capital adequacy ratio and banks’ performance to be positive as revealed in studies by Embaye et al (2017), Herath et al (2021), and Kaimu and Muba (2021)

𝐶𝐴𝑅 = ((Tier1 Capitalit + Tier2 Capitalit)/ Total Risk weighted Assetit ) ∗ 100% (5)

The cost-efficiency ratio is a crucial metric in evaluating the operational efficiency of banking institutions It measures the proportion of operating costs relative to operating income, providing

a clear picture of a bank’s ability to manage costs and generate profits The CER is widely utilized

by financial institutions, regulators, and analysts to assess a bank's operational performance, sustainability, and competitiveness A lower ratio generally reflects higher efficiency, while a higher ratio signals inefficiency or rising costs relative to income The theoretical framework underpinning the cost-efficiency ratio is grounded in the efficiency theories of firm behavior According to the neoclassical theory of the firm, efficiency refers to the optimal utilization of resources to minimize costs and maximize output (Coelli, Rao, O’Donnell, & Battese, 2005) In banking, this concept extends to the effective management of operational costs relative to income from core banking activities Financial intermediation theory also underpins the CER relevance, emphasizing the role of banks as intermediaries in efficiently allocating capital between savers and borrowers (Diamond & Dybvig, 1983) Banks strive for operational efficiency to maintain competitive advantage, improve profitability, and satisfy regulatory requirements The CER acts

as a critical indicator of this operational efficiency As highlighted by Berger and Mester (1997), operational efficiency can be examined through both cost efficiency (controlling costs relative to output) and profit efficiency (maximizing profits relative to costs and income)

CER = Total operating cost/ Total revenue (6)

The average lending rate (ALR) refers to the weighted average interest rate that banks charge borrowers on loans It is a critical metric in the banking sector, as it directly influences borrowing costs, profitability, and economic activity The ALR serves as an indicator of the overall cost of credit in an economy and is influenced by various factors, including central bank policies, market conditions, and risk premiums Understanding the dynamics of the average lending rate is essential for evaluating the financial health of banking institutions, the effectiveness of monetary policy, and the accessibility of credit for consumers and businesses The determination of the average lending rate is rooted in several economic and financial theories, including the theory of interest rate determination and the risk-based pricing model According to the classical theory of interest, the lending rate is determined by the supply and demand for loanable funds (Keynes, 1936) Central banks influence the supply of money through monetary policy tools such as open market operations and the setting of policy interest rates As a result, commercial banks adjust their lending rates based on the cost of borrowing from the central bank and the availability of credit in the broader financial market The risk-based pricing model also plays a crucial role in determining the average lending rate This model posits that the lending rate reflects not only the bank’s cost of funds but also the borrower’s risk profile (Stiglitz & Weiss, 1981) Banks charge higher interest rates to riskier borrowers to compensate for the increased likelihood of default, which explains why lending rates vary across different sectors and customer segments A higher lending rate generally boosts bank profitability, but excessive increases can stifle demand for credit, reducing loan volumes and overall income Studies by Ho and Saunders (1981) show that banks adjust their lending rates to maximize ROE while balancing credit risk

ALR= Net interest income/ Total assets (7)

The liquidity ratio is a critical financial metric used in banking organizations to measure their ability to meet short-term obligations with liquid assets It reflects a bank's capacity to fulfill deposit withdrawals, cover short-term debts, and manage cash flow needs The liquidity ratio is pivotal for financial stability, particularly in mitigating liquidity risk, which arises when a bank cannot quickly convert assets into cash without significant losses The concept of liquidity in banking is deeply rooted in the theory of financial intermediation Banks act as intermediaries between savers and borrowers, holding liquid assets to meet the demands of depositors while investing in less liquid assets to generate returns (Diamond & Dybvig, 1983) Maintaining an

optimal balance between liquid assets and investments is crucial for bank stability and profitability According to the liquidity preference theory (Keynes, 1936), banks must balance the trade-off between holding liquid, low-yield assets and investing in less liquid, higher-yield assets Holding more liquid assets improves the liquidity ratio but may reduce returns, while excessive illiquid assets increase profitability risks While higher liquidity ratios improve financial stability, they may come at the expense of profitability Liquid assets, such as government bonds or central bank reserves, typically offer lower returns than loans or investments in financial markets Therefore, banks need to strike a balance between holding sufficient liquidity to meet obligations and investing in higher-yielding, less liquid assets to maximize profits (Dietrich et al., 2014)

LR = Total loans/ Total deposits (8)

Bank size is measured as the natural logarithm of the bank’s total assets Bank size is widely used

in the financial sector to indicate possible economies or diseconomies of scale The study expects bank size to influence banks’ financial performance positively This is because, bigger banks are asserted to benefit from economies of scale and prospects for diversification and this enhances their performance

Banksize = Log(Total assets) (9)

Age is measured by how long a bank has been in existence It also indicates the experience of the bank The relationship between age and banks’ financial performance is expected to be positive as indicated in studies by Boahene et al (2012), Bhattarai (2016) and Kutum (2015) This stems from the assumption that older banks have more credit risk management expertise and therefore reduce the negative impact on their financial performance This is supported by the moral hazard and adverse selection theory, which indicate that historical data available about a borrower will reduce adverse selection and in turn reduce credit defaults All other things being equal, older banks will have more historical data to assess prospective borrowers as compared to newer banks

AGE = Age of commercial banks from established to the year calculated (10)

in GDP will lead to a higher demand for loans and higher deposits and this is likely to enhance the financial performance of the banks Inflation is the persistent rise in the general price levels of goods and services

GDP = Growth rate of gross domestic products

INF rate indicates that the price level of the same general basket of goods and services increases over a time period The change in price over time of the basket of goods and services is reflected

by the consumer price index (CPI) This was heavily discussed in the literature (see, for example, Claessens et al., 2001; Drakos, 2002; Alexiou & Sofoklis, 2009; Kasman et al., 2010; Tarusa et al., 2012)

Inflation = Annual inflation rate declared by world bank yearly

The COVID-19 pandemic, represented as the CRISIS variable, has significantly impacted the relationship between credit risk and profitability in banking organizations Research shows that the pandemic led to a surge in non-performing loans (NPLs) as businesses and consumers struggled, increasing credit risk and threatening bank profitability (Demirgüç-Kunt, Pedraza, & Ruiz-Ortega, 2021) However, some studies suggest that banks that adapted their risk management and accelerated digital transformation were able to mitigate the adverse effects (Bian et al., 2021) Government interventions, such as loan forbearance and stimulus programs, also temporarily stabilized credit markets (Auer et al., 2021) While the pandemic heightened credit risk, many banks demonstrated resilience, preserving profitability through strategic responses This highlights the complex impact of external shocks like COVID-19 on the credit risk-profitability relationship

in banking organizations

The author considers the financial crisis conditions by adding the dummy variable CRISIS to the model The variable CRISIS takes the value of 1 to represent the crisis conditions, and takes the value of 0 to represent normal conditions in the remaining years of the research period

Table 1 :Summary of explanatory variables and dependent variables

sign

Dependent

variables

Credit risk

performing loans

Non-NPL Total nonperforming loan/

Total loans

Elshaday

et al (2018)

Loan loss provision

LLP Loan loss provison/ Total

assets

Ai Zaidanin

et al (2021)

-

Control

variables

specific factors

Bank-Return on asset

ROA Net income/ Total assets Ogboi et

al (2013), Zou et al (2014), Bhattarai (2016)

-

Return on equity

ROE Net income/Eequity Ogboi et

al (2013), Zou et al (2014), Bhattarai (2016)

Capital adequacy ratio

CAR ((Tier1 Capitalit + Tier2

Capitalit)/ Total Risk weighted Assetit )* 100%

Elshaday

et al (2018)

+

efficiency ratio

ALR Net interest income/

Liquidity ratio

LR Total loans/ Total deposits Elshaday

et al (2018)

+/-

Bank size BS Ln(total assets) Vo et al

Age AGE Age of commercial banks

from established to the year calculated

Vuong et

al (2023) +

Control

variables

Other factors

Inflation INF Annual inflation rate

declared by word bank yearly

Vo et al (2022) +/-

Gross domestic products

GDP Growth rate of gross

domestic products

Vo et al (2022) +/-

Covid Pandemic

CRISIS Panel data:

From 2011 – 2019: 0 value

as powerful tools for disentangling intricate dynamics, particularly in panel data settings These models provide a robust analytical framework for investigating complex interplays among variables, while effectively addressing concerns related to unobserved heterogeneity and time-invariant characteristics In this context, the integration of FEM and REM methodologies into empirical investigations demonstrates a commitment to both methodological refinement and insightful inquiry

The FEM, rooted in its premise of subtracting individual-specific means from the data, represents

a tailored approach to examining the evolution of variables within entities over time By effectively

accounting for unobservable entity-specific effects, the FEM contributes to a comprehensive understanding of the temporal dynamics shaping financial phenomena Conversely, the REM, which accommodates unobserved individual-specific effects by treating them as random variables, complements the FEM by offering insights into average effects across entities The REM is particularly pertinent when the research objective encompasses a broader perspective that transcends entity-specific variations

The robustness and reliability of research findings are contingent upon the adherence to fundamental econometric assumptions, paramount among which are the absence of heteroscedasticity and autocorrelation within the model specifications To ascertain the fidelity of the empirical results, this study diligently applies the Modified Wald test to scrutinize the presence

of heteroscedasticity The null hypothesis posited by the Modified Wald test postulates equal variances among the errors, indicating homoscedasticity Conversely, the alternative hypothesis contends that the errors exhibit unequal variances, indicative of heteroscedasticity In embracing the null hypothesis, the research affirms the constancy of error variance, thereby validating the unbiasedness of the estimated regression coefficients vis-à-vis the true coefficients of the independent variables across the population In the context of time series data, autocorrelation manifests when a variable and its lagged counterpart exhibit temporal correlations, potentially skewing the reliability of regression coefficient variances and compromising hypothesis testing validity To address this concern, the null hypothesis postulated by the Wooldridge test stipulates the absence of autocorrelation By embracing this null hypothesis, the research safeguards against the repercussions of autocorrelation-induced bias and bolsters the integrity of inferences drawn from the model outcomes This meticulous scrutiny of autocorrelation resonates with the scholarly discourse championed by seminal works such as Wooldridge (2010), affirming the centrality of addressing autocorrelation for sound econometric analysis

CHAPTER 4 EMPIRICAL RESULTS AND DISCUSSIONS

4.1 Descriptive statistic

The present research paper provides empirical evidence on the interconnection between credit risk and bank-specific/internal factors on financial performance of commercial banks in Vietnam To analyze the data set, first, the study applies the descriptive analysis to identify the big picture of the data, then the correlation section and at the end, regression results are discussed

Table 2: The descriptive statsitcs of of the variables

in relation to their total assets The standard deviation for Return on Asset is 0.012, while the

average profitability (mean = 1.9%) is modest, indicated that there is a notable dispersion across banks Some banks achieve significantly higher returns on assets (up to 7.4%), while others barely

break even (as low as 0.2%) This level of profitability is generally consistent with banks in emerging markets, where growth opportunities are accompanied by significant risks The range form ROA suggests that some banks are more efficient in utilizing their assets to generate profit, while others struggle, potentially due to higher risk exposure or inefficiencies

The Return on Equity (ROE) exhibits a larger standard deviation of 0.128, reflecting substantial differences in how effectively banks are utilizing shareholders’ equity to generate profits With a mean of 22.1%, Vietnamese banks generally provide strong returns to shareholders, but the wide

range from 1.7% to 64.6% and the corresponding standard deviation highlight that some banks are

significantly outperforming others This disparity may be attributed to varying levels of capitalization, lending practices, or risk exposure, where larger banks may benefit from economies

of scale and stronger financial management, while smaller or riskier banks may struggle with profitability In the context of Vietnam, such a high ROE is indicative of the aggressive expansion strategies employed by many commercial banks in recent years, fueled by strong GDP growth and favorable macroeconomic conditions

The NPL ratio (Mean = 2.2%) is a critical measure of credit risk It indicates the percentage of loans that are in default or close to default In Vietnam, the banking sector has made significant strides in reducing NPLs following reforms and tighter regulatory controls implemented by the State Bank of Vietnam (SBV) The average of 2.2% is manageable but still concerning, as it points

to some level of risk in banks' loan portfolios The range from 0.5% to 29.8% highlights a vast disparity in risk exposure among banks The Non-Performing Loan (NPL) ratio, with a standard deviation of 0.021, indicates notable variation in credit risk management Some commercial banks, particularly smaller or less well-capitalized ones, struggle with much higher NPLs, which could threaten their stability and operation effiency This aligns with the situation in Vietnam’s banking sector, where many banks especially state-owned and smaller commercial banks, face challenges

in managing credit risk, particularly in sectors like real estate and small and medium-sized enterprises (SMEs) Larger banks like Vietcombank and Vietinbank, however, tend to have lower NPL ratios, demonstrating more effective credit risk management

The Crisis Indicator (CRISIS) variable, with a mean value of 0.308 and a standard deviation of 0.462, exhibits considerable variability across the sample The range of this variable extends from 0.000 to 1.000, reflecting the presence of both non-crisis and crisis periods within the dataset This substantial range and high standard deviation underscore the diverse economic conditions

represented, highlighting the variable's capacity to capture significant fluctuations in the presence and severity of economic crises The mean value indicates that crises are present in approximately 30.8% of the observations, illustrating a moderate prevalence of crisis conditions within the observed timeframe from 2011 – 2023

The Capital Adequacy Ratio (CAR) is another vital risk metric that reflects the bank's buffer against potential losses CAR shows a standard deviation of 0.037 with a mean of 10.5%, most banks exceed the regulatory minimum of 8%, but the range from 5.5% to 26.6% demonstrates that some banks are significantly undercapitalized, making them more vulnerable to financial shocks The higher standard deviation indicates that while many banks have strengthened their capital positions, there remains a significant gap between the best- and worst-capitalized institutions The higher the CAR, the more capable a bank is of absorbing losses and protecting depositors Vietnamese commercial banks must meet minimum CAR thresholds as mandated by Basel II regulations, with 8% being the global standard A mean CAR of 10.5% suggests that most banks

in Vietnam maintain healthy capital reserves, which is crucial for financial stability However, with some banks showing a minimum CAR of 5.5%, there are concerns about undercapitalization in a few institutions, which might struggle to withstand economic shocks The variability in CAR across banks indicates that while large banks typically meet or exceed regulatory requirements, smaller banks might face challenges in raising sufficient capital This is particularly relevant in Vietnam, where many banks are undergoing restructuring to meet international standards as part

of the country’s broader financial sector reforms

The cost-to-income ratio (CER) has a standard deviation of 0.066, reflecting varying levels of efficiency across banks While the mean CER is relatively low at 23.2%, the standard deviation suggests that some banks are operating with much higher costs relative to income (up to 56.4%), highlighting inefficiencies in cost management and revenue generation Lower CER values indicate higher efficiency, as banks can generate more income relative to their costs The Vietnamese banking sector has been improving its efficiency, but variations in CER show that some banks operate with higher costs relative to their income, potentially due to inefficient processes or higher operational costs in smaller banks This disparity in operational performance can be attributed to differences in scale, technology adoption, and management practices

The Asset-Liability Ratio (ALR) and Liquidity Ratio (LR) further reflect the risk management practices of banks, with ALR averaging 0.029 and LR showing a mean of 0.891, suggesting that

most banks maintain high liquidity levels relative to liabilities The Liquidity Ratio (LR), with a standard deviation of 0.186, shows considerable variation in how well banks are positioned to meet short-term obligations While the average LR is 89.1%, indicating generally strong liquidity positions, some banks have significantly lower liquidity, which may expose them to higher liquidity risk during periods of economic stress This variability underscores the importance of robust liquidity management, particularly in the rapidly growing Vietnamese market LLP measures the reserves set aside by banks for potential loan losses With an average of 0.8%, Vietnamese banks show a conservative approach to provisioning, ensuring that they are somewhat protected against potential defaults However, given the variability in NPL ratios, some banks might need to increase their provisions to better cushion against rising credit risks

The average age of banks in the dataset is 24 years, with a range from newly established banks (0 years) to much older institutions (66 years) This indicates that most Vietnamese commercial banks are relatively young, which may influence their strategic decisions and market behavior Younger banks are still in the process of establishing strong market positions and developing efficient internal processes, which could make them more vulnerable to economic volatility or rapid expansion strategies In contrast, older banks might have more established systems and be better equipped to withstand market fluctuations Inflation is a critical macroeconomic variable affecting interest rates and the cost of borrowing The mean inflation rate of 4.85% reflects Vietnam’s macroeconomic environment, where inflationary pressures have been somewhat volatile, as indicated by the wide range from 0.631% to 18.678% Banks need to manage their loan pricing and interest rate strategies carefully in this environment Periods of high inflation, as seen in the maximum value, can lead to increased borrowing costs, affecting loan demand and overall profitability, while lower inflation offers a more stable backdrop for lending activities Larger banks, as indicated by higher values of Bank Size (BS), typically possess more resources and diversification options to manage risk The average bank size (logarithm of total assets) is 5.130, with the smallest bank size at 4.167 and the largest at 6.362 This suggests that the Vietnamese banking sector consists primarily of mid-sized banks, though there are significant differences across institutions Larger banks, represented by higher BS values, likely enjoy competitive advantages in terms of risk management and profitability, benefiting from economies of scale In contrast, smaller banks may face more significant challenges in balancing growth with risk controls GDP growth provides a key context for the overall economic environment in which banks

operate The mean GDP growth rate of 8.7% reflects Vietnam’s rapid economic expansion, with growth rates ranging from 2.5% to a high of 17.3% Such high growth creates opportunities for banks to expand their loan portfolios and boost profitability, particularly during peak economic periods However, it also brings challenges, as banks must balance this expansion with maintaining adequate risk controls to avoid excessive exposure to bad loans during times of economic overheating or downturns

Table 3: Correlation analysis - the pairwise correlation matrix for variables