BANKING ACADEMY Banking Faculty ------ GRADUATION THESIS FACTORS AFFECTING THE LOAN REPAYMENT OF SME ENTERPRISES AT VIETINBANK – HOAN KIEM BRANCH Student’s name: Vu Ha Ly Class: K21CLCA Intake: 21 Student’s ID: 21A4010879 Supervisor: Assoc. Le Van Luyen Hanoi, May 2022 17014126247461000000 BANKING ACADEMY Banking Faculty ------ GRADUATION THESIS FACTORS AFFECTING THE LOAN REPAYMENT OF SME ENTERPRISES AT VIETINBANK – HOAN KIEM BRANCH Student’s name: Vu Ha Ly Class: K21CLCA Intake: 21 Student’s ID: 21A4010879 Supervisor: Assoc. Le Van Luyen Hanoi, May 2022 ANNOUNCEMENT I want to declare that the thesis is my independent research work. Statistics used for analysis purposes in this thesis have clear and well-founded origins and were published legitimately following the current applicable Vietnamese regulations.
Research findings in this thesis are my independent, factual, and objective work that is in agreement with the situation in Vietnam. These findings have not been published in any other studies before at the time of this thesis’s completion. Hanoi, May 23th, 2022 Student Vu Ha Ly i ACKNOWLEDGEMENTS After four years of pursuing the Bachelor of Banking – Finance of Advance Program, Banking Academy, the contents designed for the curriculums and the dedicated instruction of the teachers helped me improve a great amount of knowledge and other soft skills. This important knowledge and skills will help me a lot in my future career.
First and foremost, I would like to express my sincere gratitude to my supervisor Assoc. Le Van Luyen guided me in doing these projects. He provided me with invaluable advice and helped me in difficult periods. His motivation and help contributed tremendously to the successful completion of the thesis.
Besides, I would like to thank all the teachers of the Banking Academy, especially the Banking Faculty, who helped me by giving me advice and broadening my knowledge. Also, I would like to thank all staff of VietinBank – Hoan Kiem brach, every officer of the Corporate Customer Department, for giving me the materials and information necessary for this thesis. They had taught me many important skills and supported me in my internship. Last but not least, I would like to thank my family and friends for their support.
Without that support, I couldn’t have succeeded in completing this thesis. ii CONTENTS TABLE OF ABBREVIATIONS .vi LIST OF TABLES. vii LIST OF FIGURES. Rationale of the study.
Significance of study. Aims of the study. Objects and scope of the study. Research questions and method.
Organization of the study .7 CHAPTER 1: LITERATURE REVIEW. Credit and credit characteristics for SMEs. Definitions of credit for SMEs. Credit characteristics for SMEs.
The role of credit for SMEs. Loan repayment ability of SMEs. Definition of repayment. Methods evaluating loan repayment.
The role of assessment and analysis of factors affecting the loan repayment of SMEs. Factors affecting the loan repayment of SMEs. Factors from SME enterprises. Factors from the loan side.
Factors on the bank side. Factors on the economy .23 SUMMARY OF CHAPTER 1 .25 CHAPTER 2: THE LOAN REPAYMENT OF SMES AT VIETINBANK - HOAN KIEM BRANCH. Introduction of VietinBank - Hoan Kiem branch. History of establishment and development of VietinBank Hoan Kiem.
Method evaluating loan repayment for SMEs at VietinBank - Hoan Kiem branch. Credit activities of SMEs at VietinBank - Hoan Kiem branch. SME loan sales. SME loan sales structure.
Non-performing debt, the overdue debt of SMEs. Provision for SMEs lan losses. Reasons for unable to repay loans of SMEs at VietinBank - Hoan Kiem branch. Factors from customers.
Factors from the bank .38 SUMMARY OF CHAPTER 2. RESEARCH METHODOLOGY, FINDINGS, AND DISCUSSION. Research process and framework. Logit regression analysis.
Summary and interpretation of findings .51 SUMMARY OF CHAPTER 3. Implications from research results. Recommendations for VietinBank and Hoan Kiem branch. For the process of appraising corporate customers in general and SMEs in particular 54 4.
For credit policy. For the staff of VietinBank. Recommendations for SMEs. Recommendations for the State Bank of Vietnam .59 SUMMARY OF CHAPTER 4 .69 v TABLE OF ABBREVIATIONS Abbreviation Explanation CASA Current Account Savings Account CIC Credit Information Center EAD Exposure of Default EL Expected Loss FEM Fixed Effects Model GDP Gross Domestic Product IFC International Finance Company IT Information Technology LGD Loss Given Default MDA Multiple Discriminant Analysis NPL Non-performing Loan OLS Ordinary Least Square PD Probability of Default REM Random Effects Model ROA Return on Assets ROE Return on Equity SBV The State Bank of Vietnam SME Small and Mid-size Enterprise VCOMS VietinBank Credit Operation Management Support vi LIST OF TABLES Table Table’s Name Page Table 1.1 Classifying SMEs in Vietnam 9 Relationship between loan repayment ability and customer's Table 1.2 14 debt classification results Table 2.1 Business result of VietinBank Hoan Kiem from 2019-2021 28 Table 2.2 The customer’s rating classification at VietinBank 31 VietinBank Hoan Kiem’s SME loan sales structure 2019 - Table 2.3 32 2021 VietinBank Hoan Kiem's SME loan sales structure by Table 2.4 34 lending sectors 2019 - 2021 Non-performing debt, the overdue debt of SMEs at Table 2.5 36 VietinBank Hoan Kiem 2019 - 2021 Provision for SME loan losses at VietinBank Hoan Kiem Table 2.1 Descriptive Statics of variables 45 Table 3.2 The loan repayment of the research sample 46 Table 3.3 Correlation of independent and dependent variables 47 Table 3.4 Omnibus Tests of Model Coefficients 47 Table 3.5 The results of testing the prediction level of the model 48 Table 3.6 Variables in the Equation 48 vii LIST OF FIGURES Figure Figure's Name Page Figure 2.1 VietinBank Hoan Kiem’s organization structure 26 Figure 2.2 VietinBank Hoan Kiem loan sales structure 2019 - 2021 32 VietinBank Hoan Kiem loan sales structure by terms 2019 - Figure 2.3 33 2021 VietinBank Hoan Kiem loan sales structure by collateral Figure 2.4 35 2019 - 2021 VietinBank Hoan Kiem’s SMEs non-performing debts, Figure 2.5 36 overdue debts 2019 - 2021 viii INTRODUCTION 1.
Rationale of the study The development of the commercial banking system has always been associated with the evolution of the national economy. As the main credit intermediaries, Vietnam's commercial banks have actively supported recovering the economy and stabilizing citizens' lives, especially in 2019 - 2021, in the context of the widespread Covid-19 epidemic. According to the General Statistics Office, Vietnam welcomed 2021 with a GDP growth of only 2.91% in 2020, the lowest in the past decade. However, this result put Vietnam on the list of countries with high growth rates worldwide.
This positive signal came from implementing credit programs, timely support, and removal of difficulties for businesses across the country, significantly promoting investment and production. Credit activities for corporate customers, especially the SME segment, have continuously been prioritized in the loan portfolio of commercial banks because of their significant number in the Vietnamese market economy. Following the direction of the State Bank, VietinBank has implemented selective and effective credit growth promotion, encouraging the expansion of the retail segment and SME enterprise customers. According to Vietinbank's internal report, as of December 31, 2021, the proportion of individuals and SME loans reached 57%, a positive gain compared to 54% in 2020.
Although credit activities generate a huge profit, they also conceal many potential losses. Credit risks would exert many serious consequences by creating a domino effect for a bank and the entire financial system. Credit risk in lending activities results from various reasons, but its predecessor is the ability of customers to repay loans. The evaluation of the loan repayment of SMEs cannot rely on only the statistics on the financial statements but also on various factors from the banks or the macro- environment… It is a daunting task for banks to combine financial and non-financial elements, supporting making a loan decision.
By the end of 2021, the non-performing loan ratio of VietinBank was controlled at 1.3%, in compliance with the planned limit assigned by the State Bank and the General Meeting of Shareholders. However, in reality, non-performing loans have always existed and tend to increase, especially for loans of SMEs. Therefore, researching the factors affecting the loan repayment of 1 SMEs is essential for VietinBank to achieve its goal of sustainable and effective credit growth in the near future. Due to limited time and conditions, the writer selected the topic: "Factors affecting the loan repayment of SME enterprises at VietinBank - Hoan Kiem branch".
Previous study Many previous studies had put a great deal of effort into explaining the factors affecting the loan repayment of customers. Paving the way for forecasting financial difficulties, Ohlson (1980) used logistic regression to predict the probability of a firm’s bankruptcy. The writer used a data set of 2058 companies listed on Wall Street from 1970 to 1976. He found a negative correlation between the probability of bankruptcy and firm size, profitability, and liquidity; and a positive correlation between the probability of bankruptcy and debt.
Ajah et al. (2014) researched the creditworthiness of agribusiness in Cross River State, Nigeria, using a sample from agri-households borrowing at the Nigeria Agricultural Support Fund in 2008-2009. The results showed that creditworthiness is influenced by the household head’s education level, farm size, age, income, and experience. In addition, the study proved that the banks’ ability to manage loans also affects the customers’ loan repayment decisions.
In Vietnam, Truong Dong Loc (2011) investigated the factors affecting the capability of farmers to repay loans on time in Hau Giang province. The research applied the Probit model to the statistics collected from the survey of 436 households in 2009. The outcome exposed that the income after borrowings and the owner experience are positively correlated with the ability to repay on time, while the loan interest rate had a negative correlation. Moreover, the author also expected the relationship between the practical purpose of capital use and the timely repayment.
However, this result had no statistical significance; the use of loans had no relationship with the farmers' loan repayment. In the same year, Hoang Tung (2011) analyzed the corporate credit risk, using the logistic model on data of 463 firms listed on the Vietnamese stock market. The sample was divided into two groups: the companies with credit risk (93 companies) and those without credit risk (370 companies). The independent variables were 2 calculated from the 2009 financial statements of these firms.
From the result, the author had successfully built a function to forecast credit risk for businesses based on financial indicators with a high accuracy (the correct prediction rate of the whole sample was 98. On the other hand, the model also supported the determination of the credit ratings of businesses. Vo Van Dut (2012) studied the factor affecting the relationship between commercial banks and enterprises in Can Tho, using the data collected from 12 bank branches and 199 enterprises in Can Tho. The final figures showed that the average number of banks having relationships with a firm was 2.
Merely one-third of firms in the sample had relationships with one bank only. Specifically, there were enterprises that had relationships with more than 5 banks. Le Phuong Dung and Nguyen Thi Nam Thanh (2013) researched factors affecting the short-term bank loan of the food processing businesses listed on the Vietnam stock market. The study used the data from the financial statements in the period from 2007 to 2011 of 39 enterprises.
The writer applied a dynamic panel data model with different methodological approaches: fixed effects model (FEM) and random effects model (REM). The results indicated that the reputation of the business (measured by the operating year of the business and the form of ownership) had an impact on the ability to borrow and repay of business.