Dissertation submitted in partial fulfillment of the Requirement for the MSc in Finance FINANCE AND INVESTMENT DISSERTATION ON Impact of credit risk on the financial performance of Vietnamese banks DO TRUNG NGHIA ID No: 23081362 Intake 7 Supervisor: Ph.D Pham Thu Thuy September 2024 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 Pham Thu Thuy Date: 08 Sep 2024 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.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.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. LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT .3 Relation between Credit risk and Bank performance .1 The theoretical literature .2 The empirical literature .2 Relation between Non-performing loan and financial performance .3 Relation between capital adequacy ratio and financial performance .4 Relation between cost-efficiency ratio and financial performance .5 Relation between average lending rate and financial performance .6 Relation between liquidity ratio and financial performanc .7 Relation between loan loss provision and financial performance.
DATA AND EMPIRICAL METHODOLOGY .1 Financial performance of bank. EMPIRICAL RESULTS AND DISCUSSIONS .2 Impact on the profitability .3 Results of the effect of credit risk on the financial performance and hypothesis results .1 Recommendation for commercial bank .2 Recommendation for State bank of Vietnam. CONCLUSION AND IMPLICATIONS .2 Contribute and limitation. 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 Abbreviation Full Form NPLs Non-Performing Loans ROA Return on Assets ROE Return on Equity CAR Capital Adequacy Ratio ALR Average Lending Rate NIM Net interesr margin FEM Fixed Effects Model REM Random Effects Model GLS Generalized Least Squares SBV State Bank of Vietnam VAMC Vietnam Asset Management Company SIZE Size of banking organization BCBS Basel Committee on Banking Supervision IFRS International Financial Reporting Standards LLP Loan Loss Provision GDP Gross domestic product INF Inflation ALR Average lending rate CER Cost effieciency ratio LR Liquidity ratio LLP Loan loss provision AGE Age of banking organization CRISIS Crisis of Covid Pandemic 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 1 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.