i • t ~ UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM NETHERLANDS PROGRAMME FOR M A IN DEVELOPMENT ECONOMICS BANK CREDIT APPRAISAL CRIT[.]
i UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS • VIETNAM- NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS BANK CREDIT APPRAISAL CRITERIA FOR BORROWING FIRMS IN VIETNAM A thesis submitted in partial fulfilment of the requirements for the degree of t MASTER OF ARTS IN DEVELOPMENT ECONOMICS By LE DiNH THUY NGAN Academic Supervisor: Asso.Prof.TRUONG QUANG THONG HO CHI MINH CITY, DECEMBER 2010 - -~ CERTIFICATION i • I hereby certify that the substance of this thesis has not been submitted for any degrees and is not being currently submitted for any other degrees I also certify that, to the best of my knowledge, and any help received in preparing the thesis and all sources used have been acknowledged in the thesis Signature ' LeDinh Thuy Ngan Date: December, 2010 • · ~ _- ACKNOWLEDGEMENT • This research 1s impossibly completed without the valuable guidance, encouragement and advice from numerous individuals including VietnamNetherlands program lecturers, friends and my family members I am really indebted and grateful to what they have done for my thesis completion First of all, I would like to send my deepest gratitude to my supervisor, Professor Truang Quang Thong who always gives advice and comments during my completion of the thesis I am grateful for Professor Nguy~n TrQng Hoai and Professor Peter Calkins for their precious advice and comments from the initial ideas of the theme for my thesis • Many especially respectful thanks are sent to my family for encouraging and providing me with an opportunity to pursue my desires in higher learning and for their love, affection and sympathy that have helped me to gain more strength and motive to complete this thesis LIST OFT ABLES Table 2.1: Rating symbols long-term and short-term debt II Table 2.2: Weighted points of non-financial criteria 14 Table 2.3: Weighted points of financial ratios and non-financial criteria 15 Table 2.4: Weighted points of financial ratios and non-financial criteria 15 Table 2.5: Rating symbols ofVCB 16 Table 2.6: Profit and tax with two different capital structure 18 Table 3.1: Sort credit rating business 25 Table 3.2: Business structure has ability to repay 26 Table 4.1: Following explain the meaning of variables (see appendix 1) 31 Table 4.2: Points of cash flow factor 37 Table 4.3: Points of management quality factor 38 Table 4.4: Points of relations with banks factor (see appendix 3) 39 Table 4.5: Points of business environment factor 40 Table 4.6: Points of other activities factor 41 Table 5.1: Descriptive Statistics 44 Table 5.2: Correlations (see appendix 4) 45 Table 5.3: Model summary (see appendix 5) 46 Table 5.4: Anova 46 Table 5.5: Coefficients of models (see appendix 6) 46 Table 5.6: Distribution graph 48 Table 5.7: Spearman rank correlation 48 Table 5.8: Standardized residual graph 49 ABBREVIATIONS BIDV: Bank for Investment and Development of Vietnam CIC: Credit information center EBIT: Earning before tax and interest rate EU: Europe FDI: Foreign Direct Investment GDP: Gross Domestic Products GSO: General Statistics Office ofVietnam MM: Modiglian Miller SBV: State Bank of Vietnam SMEs: Small Medium Enterprises U.S.: United States VCB (Vietcombank): Bank for Foreign Trade of Vietnam WACC: Weighted average cost of capital ABSTRACT Capital credit is very important in business activities of enterprises The ability to repay loans model in this thesis shows an important role when the bank make a lending decision This study examines and analyses credit rating criteria affecting borrowing firms on bank credit appraisal in Vietnam through applying cross-section data from Credit Information Center which concentrate on forty firms including the medium-sized enterprises that has equity capital more than five billions Vietnam dong or number labor more than two hundred people in leather-footwear industry The regression model is estimated based on the multiple linear regression function The ability to repay loans is dependent variable in the thesis model, and independent variables are current ratio, quick ratio, inventory turnover, receivable turnover, total asset turnover, debt to equity ratio, debt to total asset ratio, return on asset, return on common equity ratio, net profit margin ratio, delinquency ratio, cash flow, management quality, the relations with banks, business environment, other activities and corporate income tax (new added) As results, corporate income tax factor affecting Vietnam Moreover, the results seem to be appropriate to answer questions of the research, borrowing firms are perceived to be information on the lending decision at banks in TABLE OF CONTENTS LIST OF TABLES ABBREVIATIONS ABSTRACT CHAPTER 1: INTRODUCTION 1.1 Problem statement 1.2 Research objective 1.3 Research questions 1.4 Methodology 1.5 The structure ofthesis CHAPTER 2: LITERATURE REVIEW 2.1 Theory background ; 7 2.1.1 Credit appraisal 2.1.2 The definition of credit rating 2.1.3 Objective of credit rating 2.1.4 Role of credit rating 2.1.5 Principle credit rating 2.1.6 Credit rating model 2.1 The basic elements of credit rating 2.1 7.1 The number ranks of credit rating 2.1 7.2 Scale of criteria 10 2.2 Some model of credit rating 10 2.2.1 Moody's rating analysis 10 2.2.2 Z-score model of Altman 12 2.2.3 Credit rating of credit information center 13 2.2.4 Credit rating VCB 13 2.3 Corporate income tax 17 2.3.1 Assumptions and proposition ofM&M theory 17 2.3.2 MM proposition I (corporate taxes)- The value of levered firm 17 2.3.3 Optimal capital structure theory 20 2.4 Summary 21 CHAPTER 3: OVERVIEW OF LEATHER - FOOTWEAR INDUSTRY IN VIETNAM Reasons of using data in Vietnam's leather - footwear industry 23 3.2 Overview ofleather- footwear industry in Vietnam 23 3.3 Credit ratings data ofthe leather-footwear industry in year 2008 24 3.4 Summary 27 CHAPTER 4: METHODOLOGY 28 4.1 The econometric design 28 4.2 Suggested research model 29 4.3 The conceptual design 32 4.3.1 Criteria that banks use to appraise ' 23 32 4.3.1.1 Current ratio- CR 32 4.3.1.2 Quick ratio- QR 33 4.3.1.3 Inventory turnover- IA 4.3.1.4 Receivable turnover- RT 34 4.3.1.5 Total asset turnover- TAT 34 4.3.1.6 Debt to total asset ratio - DA 35 4.3.1.7 Debt to equity ratio- DE 35 4.3.1.8 Net Profit margin- NPM 36 4.3.1.9 Return on assets - ROA 36 4.3.1.10 Return on Equity- ROE 36 4.3.1.11 Cash flow- CF 37 4.3.1.12 Management quality- MQ ) 4.3.1.13 Relations with banks- RB 39 4.3.1.14 Business environment- BE 39 4.3.1.15 Other activities- OA 41 4.3.1.16 Delinquency ratio- DR 42 4.3.2 Corporate income tax (new factor)- CIT , g1-'l J 42 4.4 Data collection method 43 4.5 Summary 43 CHAPTER 5: DATA PROCESSING AND EMPIRICAL RESULTS 5.1 Descriptive statistics 5.2 Regression and hypothesis testing 44 44 45 5.2.1 Correlation analysis 45 5.2.2 Evaluating the reliability of multiple linear regression model 45 5.2.3 Test the relevance of the overall regression model 46 5.2.4 Test the significance of partial regression coefficients 46 5.2.5 Assumption of multiple linear regression model 47 5.2.5.1 Linearity Assumption 47 5.2.5.2 Homoscedasticity 48 5.2.5.3 Distribution standard of residual 49 5.2.5.4 No-serial correlation 49 5.2.5.5 Collinearity diagnostic 50 5.3 Summary CHAPTER 6: CONCLUSION 50 51 REFERENCE APPENDIX iv APPENDIX2 v APPENDIX3 V111 APPENDIX4 APPENDIX APPENDIX6 ix X Xl CHAPTER 1: INTRODUCTION This chapter starts with introduction to problem statement It then presents research objectives, questions and methodology in sections: 1.2, 1.3 and 1.4, respectively Finally, this chapter show thesis structure in section 1.5 1.1 Problem statement The world economy is currently undergoing a severe crisis The cause of the crisis is following: - Objectively, on the theory, growth and development economic generally follows cycle After a period of extreme development, it will reach the top, followed by a recession cycle With this perspective, the world economy developed rapidly in last years of previous century and peaked during the period 2001-2007 - Subjectively, these are the errors in the management economy of economic times "digital" - "virtual economy", particularly in management of financial system, money and banks, namely approximately six percents of all mortgage loans in United States were in default in 2008 Historically, defaults were less than one-third of that, i.e., from 0.25% to 2% The crisis began with the collapse of Bank Lehman Brother Investment, one ofthe largest banks in the United States, on June 2008 (BBC News, 2008) As year progressed, the United States banking and financial system, followed by the EU and Japan, were all shaken by the crash of multiple banking, corporate finance-insurance institutions In the first three months of 2009, the situation continued to deteriorate, with GDP growth in most of developed countries dropped to around negative 2.2 percent Trade turnover reduced strong (export of Eastern Asia reduced 30%, 2.2.2 Z-score model of Altman In order to strengthening the predicted bankruptcy of enterprises in credit rating model, commercial banks use predict models which have many variables Methods are used to predict the risk failure of businesses had been built and published However, Z-score model of Altman has been tested and widely accepted Credit scoring model is built by Altman ( 1981 ), the first development Then Steele (1984), Morris (1997) and other researchers develop more The general model is Z = c + "L c r I I Where as: c: constant; ri: financial ratios and non-financial criteria is used as variables; ci: coefficients of each variables in the model; i: variables The model is developed by Altman for publicly traded manufacturing firms in United States Altman as follows: Z Where = 1.2Xt + 1.4X2 + 3.3XJ + 0.6X + 1.0 X Z > 2.99 indicate non-bankruptcy, 2.2 < Z < 2.99 indicate a gray area, And Z < 1.80 indicate bankruptcy prediction Of which: • X = (Current Assets - Current liabilities) I Total Assets: measure the density of working capital in total assets • X = Retained Earnings I Total Assets: measurement ability profits • X3 =Earnings before Interest and Taxes I Total Assets: This is the most important coefficient Profit is the top goal and is determined at the existence of businesses Future loans added to the charges also show the ability to create income for enterprises • X4 =Market Value of Equity I Book Value of Total Liabilities: measuring stamina of enterprises when the property of firms decline 12 • X5 = Sales I Total Assets: the ability to create sales of property * Advantages from the model mentioned above measure risk credit by scores saying that it is relatively simple But, this model has a few disadvantages as follow: The model only allows classification borrowers with two groups as risk and no risk However, in practice the level of credit risk potential of each customers is different such as slow to repaying interest expenses, and not pay interest expenses to lost all capital Unconvincing reasons to show that the number reflects the importance of indicators in the formula is invariant Z-Scores model of Altman Model not include difficult criteria to quantify, but I think it is an important role affecting level loans (reputation of customers, the relationship between long-term banks and customers or macroeconomic criteria such as fluctuations of economic cycles) 2.2.3 Credit rating of Credit information center (CIC) Credit Information Center of State Bank implementation ranked trust businesses under the guidelines of State Bank in Vietnam in order to standardize the assessment of financial ratios criteria can apply for Commercial Bank CIC is currently using 11 financial ratios criteria, including current ratio, quick ratio, inventory turnover ratio, receivable turnover ratio, total asset turnover ratio, debt to equity ratio, debt to total asset ratio, return on asset ratio, return on common equity ratio, net profit margin ratio, delinquency ratio to the grading guidelines in Decision No 57/2002/QD-NHNN date 24 January, 2002 This model is clearly limited by the appraisal lack of non-financial criteria And this model not consider corporate income tax factor 2.2.4 Credit rating VCB Vietcombank build credit rating system with the principles of limited maximum impact financial ratios criteria by designing non-financial criteria and provide detailed instructions for the evaluation of credit rating 13 - - The financial ratios criteria is assessed by the instructions of State Bank and adjust a few statistics ratio by industry calculated from information VCB's credit data Those of non-financial criteria are built to supplement financial ratios criteria Each criterion was evaluated in the standard corresponding level of points 20, 40, 60, 80, 100 (initial points) Depending on the importance of each criteria group and criteria have different weight Based on the total points achieved after initial points with weighted to ratings Enterprises are classified in three groups: large, medium and small Each group size will be scoring system of 14 financial ratios criteria corresponding to the group-farm forestry industries- fishing, trade and services, construction and industry Financial ratios criteria including liquidity ratios (current ratio, quick ratio); activity ratios (receivable turnover ratio, inventory turnover ratio, total asset turnover ratio); debt ratios (debt to total assets ratio, debt to equity ratio, delinquency ratio), profitability ratios (return on asset ratio, return on common equity ratio, net profit margin ratio), but credit rating criteria of VCB not consider corporate income tax factor Table 2.2: Weighted points of non-financial criteria State-owned Enterprises with Other enterprises foreign investment business 20% 20% 27% Management 27% 33% 27% Relations with banks 33% 33% 31% External criteria 7% 7% 7% Other activities 13% 7% 9% Criteria Ability to pay debts from cash flow Source: VCB, Ernst & Young (2008) Table 2.2 shows that weighted points of non-financial criteria including ability to repay debts from cash flow, management quality, relations with banks, 14 business environment and other activities In addition, credit rating of enterprises are categorized by three groups is state-owned enterprises, enterprises with foreign investment and the other business in the weigh points of non-financial criteria And categorized companies by two groups are businesses have been audited and not audited as presented in Table 2.3 and 2.4 Table 2.3: Weighted points of financial ratios and non-financial criteria (not audited) State-owned Other Enterprises with enterprises business foreign investment Financial ratios 40% 35% 50% Non-financial 60% 65% 50% Criteria Source: VCB, Ernst & Young (2008) Table 2.4: Weighted points of financial ratios and non-financial criteria (audited) State-owned Other Enterprises with enterprises business foreign investment Financial ratios 60% 55% 60% Non-financial 40% 45% 40% Criteria Source: VCB, Ernst & Young (2008) Based on the total points achieved as the calculation is presented above, VCB usually uses the following 10 ranks" AAA, AA, A, BBB, BB, B, CCC, CC, C, D" from highest to lowest to denote the loaning enterprises credit rating classes as presented in Table 2.5 15 Table 2.5: Rating symbols ofVCB Points Interpretation Rating Enterprises operating effectively, the ability to self-finance 95-100 AAA good prospects of long-term development, have financial potential well, history of loan repayment is well, risk lowest Operating effectively and stability, ability to self-finance 90-94 AA high, have development, history of loan repayment is well, risk low 85-89 A 75-84 BBB Financial situation stable business effectively, history of loan repayment is well, risk relatively low Operates relatively efficiently, financial situation stable, have certain limitations about financial potential, risk average Enterprises performing at present, financial potential average, 70-74 BB 65-69 B 60-64 CCC risk average Enterprises operating sour effectively, ability to self-finance 55-59 cc activity, risk relatively high Enterprises operating effectively low, lack of management capacity, low repayment loan, risk high Enterprises poor performance, weak financial ability, weak repayment loan, risk is very high Enterprises performs poorly, extend loss, not the ability to 35-54 c self-fmance, management capacity weaknesses, debt is out of date, risk is very high