Predicting the probability of default for small and medium enterprises based on financial indications

MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY -oOo - NGUYEN DIEU LINH PREDICTING THE PROBABILITY OF DEFAULT FOR SMALL AND MEDIUM ENTERPRISES BASED ON FINANCIAL INDICATORS GRADUATION THESIS MAJOR: FINANCE & BANKING CODE: 7340201 HO CHI MINH CITY, 2021 MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY NGUYEN DIEU LINH PREDICTING THE PROBABILITY OF DEFAULT FOR SMALL AND MEDIUM ENTERPRISES BASED ON FINANCIAL INDICATORS GRADUATION THESIS MAJOR: FINANCE & BANKING CODE: 7340201 SCIENCE INSTRUCTOR Ph.D NGUYEN MINH NHAT HO CHI MINH CITY, 2021 i ABSTRACT The internal credit rating system always plays an important role at commercial banks in assessing customers' credit risk and assisting the bank in making credit decisions as well as in management activities, risk treatment at the bank At the same time, the Government has been building a legal framework for the credit rating to improve information transparency and support for banks to control credit risk from the beginning as well as support the stock market, the bond market to promote capital mobilization through the stock market, protect the rights and interests of investors Researching and selecting suitable rating models will significantly contribute to the development of credit rating activities in Vietnam However, the current models for predicting default probability have certain limitations and are being debated, inconsistency about these models' reliability, which leads to difficulty in choosing the model is suitable to predict the probability of default of the business Besides, determining which financial ratios affect the ranking results is always the goal, which needs to be studied in default prediction research Up to now, there are still not many studies published in Vietnam on selecting models to forecast the probability of default of enterprises based on financial indicators Therefore, the thesis focuses on the issue of "Predicting the probability of default for Small and Medium Enterprise based on financial indicators" to provide commercial banks systematically a theoretical basis and empirical evidence related to the selection of an appropriate business bankruptcy prediction model to contribute to improving the efficiency in credit risk management of the bank in the future Based on the importance and necessity, the objective of this study is to: (i) determine the criteria of an appropriate forecasting model; (ii) how to choose a model capable of predicting the default probability of Small and Medium Enterprises (SMEs) at Vietnamese commercial banks based on financial indicators The results obtained from this study aim to provide additional quantitative scientific evidence to answer which predictive model gives the best results in predicting the probability of default of medium firms and small in Vietnamese commercial banks; (iii) The most important ii contribution of this study is to develop a basic idea in the use of financial indicators to forecast the default probability of SMEs, thereby contributing to improving efficiency results in the credit risk control of commercial banks in Vietnam in the coming time SMEs play a major role in most economies, particularly in developing countries SMEs account for the majority of businesses worldwide and are important contributors to job creation and global economic development Micro, small and medium enterprises, commonly known as small and medium enterprises, are smallsized enterprises in terms of capital, labor or turnover Small and medium enterprises can be divided into three categories based on their size: micro enterprises, small enterprises and medium enterprises According to the World Bank Group's criteria, a micro enterprise is an enterprise with a number of employees less than 10 people; a small enterprise with a number of employees from 10 to less than 200 people and a capital of 20 billion or less; medium enterprises have from 200 to 300 employees with capital of 20 to 100 billion Probability of default is an important component applied in many credit risk analysis and risk management activities According to Basel II, it is a key parameter used in calculating the level of economic capital capable of absorbing risks at credit institutions PD is one of the most useful ratios for classifying borrowers All banks, whether using standard or other advanced methods must provide supervisors with an internal estimate of the PD relative to the borrower to the extent of the score The ranking result based on PD is considered relatively accurate as it is calculated on the firm's actual financial ratios and can practically reflect the business's state PD can effectively reduce credit risk if fully considered Through a review of domestic and foreign studies shows that financial institutions can apply many different credit rating models to predict the default probability of enterprises These predictive models can be polynomial models, logit models, probit models, artificial neural network models Besides, these ranking models use inputs or different financial indicators to forecast the bankruptcy of a business Financial ratios are commonly used as short-term solvency, rate of return/total assets, total iii liabilities/total assets However, with data sets built in different periods, the conclusions about choosing the appropriate credit rating model and financial indicators affecting the probability of default in the researchers are different, as well as the application in Research to predict the possibility of default of SMEs customers in Vietnam according to the author which is a new point Through the analysis, comparison and synthesis of the above studies and related issues, the author has pointed out some research gaps, proposing the proposed research model and expected method for the topic To accomplish the research objectives, the author implemented through 04 stages according to the following steps: Stage one is collect and process data; The second phase select the input variables of the model; The third stage run the regression on selected credit rating models (the logit model, the probit model, the complementary log-log model); The last stage use the Confusion matrix and F1 - Score to evaluate each model's regression results On that basis, select an appropriate credit rating model and has the ability to predict well the probability of default of customers The study was conducted based on the data, which are taken from the annual financial statements of approximately 400 companies from 2017 to 2019 These financial statements have been audited to ensure the quality of the information source Out of 400 businesses, there are 31 businesses in the field of consumer goods trading; 35 enterprises in the petroleum business sector; 39 businesses in the automotive business; 40 enterprises in the construction and installation industry; 43 enterprises in the pharmaceutical industry and medical equipment; 45 enterprises in the textile and garment industry; 47 enterprises in the fisheries sector (fish, shrimp, clam, ); 54 businesses in the iron and steel industry and 66 businesses in the agricultural sector (rice, coffee, pepper, ) Based on the studies, the author selected 14 financial indicators as independent variables for the credit rating models in the research paper Through analyzing the regression results from parametric models, and based on criteria calculated from the confusion matrix (Accuracy, Sensitivity, Specificity, Precision, F1 - Score) to compare and evaluate the ability to predict default iv probability of each model Thereby finding a suitable model to predict the default probability of enterprises The final result of the research shows that there are 5/14 variables play an important role in predicting the default probability of customers, these are Income before tax/Total assets, Total liabilities/Total assets, Earnings before tax, interest and amortization/Long-term debt, Average cost of goods sold/Inventory and Total revenue/Total assets Through the research results, commercial banks can evaluate and select customers in practice to minimize the risk that customers cannot repay their loans From the research results, the author proposes some suggestions for commercial banks on the development of the internal credit rating system in the coming time The thesis has found a model to predict the solvency (default probability) of SMEs customers at commercial banks in Vietnam The model can help stabilize credit quality, minimize arising bad debts Customers with a qualified credit rating (rated A or higher) combined with the results of measuring the good repayment capacity according to the model will have a low probability of incurring bad debt, according to which credit risk for this group of customers is small The model can be seen as a supporting tool for commercial banks in credit granting, assuring credit quality, and facilitating an efficient, safe, and sustainable expansion and growth From there, it can help banks select and maintain a good customer structure, promote marketing strategies towards low-risk customers and develop a network of reputable customers, ensuring debt repayment The model results are the basis for commercial banks to orient credit shrinking to weak customers (high probability of default) and effective credit growth for wellperforming customers (low probability of bankruptcy) Simultaneously, building a credit policy suitable for each type of customer in terms of credit terms, interest rates, fees, requirements for security measures…to ensure safety in operation On the other hand, information to measure the solvency and the results of the model also reflects many problems related to the business performance of the business and v the field - production and business sector As a result, the model becomes a source of information for future credit policy analysis, assessment, forecast and administration vi DECLARATION This thesis is the author’s own research, the research results are truthful, in which there is no previously published content, or the content made by others except the full citations cited in the thesis The author Nguyen Dieu Linh vii ACKNOWLEDGEMENTS First of all, I would like to express my sincere thanks and express my deep ratitude to the teachers of Banking University of Ho Chi Minh City for their enthusiastic teaching, as well as consolidating the solid foundation knowledge, helping me successfully complete the university curriculum In particularly, I would like to express my sincere thanks to Mr Nguyen Minh Nhat for giving me the detailed guidance and wholehearted assistance in completing the graduation thesis Without his thoughtful support, it would be difficult for me to complete this thesis well Due to my limited practical experience, the content of the graduation thesis cannot avoid some shortcomings, I am looking forward to receiving further advice from teachers to learn more experiences I believe these experiences are extremely valuable so that I can develop myself well in the future I sincerely thank you! viii TABLE OF CONTENTS ABSTRACT i LIST OF ABBREVIATIONS x LIST OF FIGURES x LIST OF TABLES xi CHAPTER 1: INTRODUCTION 1.1 The urgency of the research 1.2 Research Objectives 1.3 Research Questions 1.4 Research Subjects 1.5 Research Methods 1.6 Expected Contributions 1.7 The Structure of Research CHAPTER 2: LITERATURE REVIEW 2.1 Small And Medium Enterprises (SMEs) 2.2 Probability Of Default (PD) 11 2.3 Financial Indicators 13 2.4 Overview of probability of default models 14 2.4.1 probability of default models 14 2.4.2 The difference between Logit model, Probit model and Complementary log-log model 21 2.5 Related studies 22 2.5.1 Related studies in Vietnam 22 2.5.2 The other related studies 24 CHAPTER 3: DATA AND METHODOLOGY OF RESEARCH 27 Gross profit/Net revenue -1.45 0.33 -1.29 -0.98 0.21 -1.07 Income before tax/Net revenue -2.82 0.24 -2.47 -1.95 0.15 -2.18 Income before tax/Total assets -1.69 0.21 -1.84 -1.31 0.10 -1.54 Earnings before tax/Equity -1.64 0.30 -1.32 -0.98 0.20 -1.06 Total liabilities/Total assets -2.03 0.29 -1.91 -1.87 0.47 -1.61 Total Liabilities/Equity -1.97 0.41 -1.82 -1.68 0.89 -1.49 Short-term assets/Short-term 0.24 2.28 0.18 0.12 1.58 0.12 liabilities (Current Assets - Inventories)/Shortterm 0.14 2.09 0.12 0.09 1.02 0.05 Liabilities Profit before tax and -30.13 22.18 -29.76 -28.94 8.36 -27.40 interest/Interest Earnings before tax, interest and -48.09 124.93 -47.85 -47.06 0.70 -33.21 amortization/Longterm debt Cash and cash 0.001 0.09 0.0009 0.0009 0.14 0.001 equivalents/Equity Average cost of goods 3.632 5.19 3.509 3.140 3.48 3.010 sold/Inventory Receivables/Average Revenue 0.104 1.05 0.097 0.079 0.34 0.062 Total revenue/Total assets 0.60 0.86 0.57 0.50 0.68 0.51 Company G H I K L M … Financial Indicator Gross profit/Net revenue 0.58 0.19 0.31 0.49 -0.67 -1.21 … Income before tax/Net revenue 0.42 0.13 0.22 0.23 -1.35 -2.56 … Income before tax/Total assets 0.39 0.18 0.23 0.78 -1.21 -1.19 … Earnings before tax/Equity 0.35 0.22 0.34 0.82 -0.78 -1.31 … Total liabilities/Total assets 0.31 0.18 0.25 0.58 -1.88 -2.33 … Total Liabilities/Equity 0.46 0.29 0.46 0.49 -1.06 -1.91 … Short-term assets/Short-term 2.97 1.90 2.27 2.36 0.10 0.24 … liabilities (Current Assets - … Inventories)/Shortterm 2.53 1.87 2.08 1.40 0.14 0.15 Liabilities Profit before tax and 25.09 21.69 22.98 19.60 -30.70 -37.12 … interest/Interest Earnings before tax, interest and 30.70 22.05 30.03 20.10 -31.00 -45.19 … amortization/Longterm debt Cash and cash 0.12 0.08 0.10 0.09 0.009 0.001 … equivalents/Equity Average cost of goods 6.87 4.70 5.11 5.68 2.74 3.432 … sold/Inventory Receivables/Average Revenue 1.11 0.98 1.04 1.15 0.057 0.098 … Total revenue/Total assets 0.91 0.77 0.88 0.89 0.45 0.63 … Source: Statistics from the author ... Basel Committee (Basel II, 2004) Therefore, the thesis focuses on the issue of "Predicting the probability of default for Small and Medium Enterprise based on financial indicators" to provide...MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY NGUYEN DIEU LINH PREDICTING THE PROBABILITY OF DEFAULT FOR SMALL AND MEDIUM ENTERPRISES BASED ON FINANCIAL. .. objectives, the research questions, the subjects and scope of the study, the research method, and the main content of the thesis 1.1 The urgency of the research In recent times, the Covid-19