International Journal of Scientific and Education Research

Transcription

1 THE PERCEPTION OF CREDIT EMPLOYEES ON THE FACTORS AFFECTING CREDIT RISK MANAGEMENT: THE CASES OF AGRICULTURE AND RURAL DEVELOPMENT BANK BRANCHES IN HANOI OF VIETNAM Assoc. Prof. Ph.D. Pham Thi Tuyet Banking Academy of Vietnam ABSTRACT The study focused on credit analysts' perceptions of factors affecting credit risk management at Agribank branches in Hanoi, Vietnam. The five Independent Variables used include the efficiency of employees in the Bank credit; The credit policy and procedures of the Bank; The instructions of the Central bank; Information asymmetry and Risk management system. Results of the survey of 307 employees working in credit 34 Agribank branches in Hanoi showed that all five independent variables have a positive impact on credit risk management. In particular, the information asymmetry and the credit policy, procedures of the Bank have the strongest impact on credit risk management at branches of Agribank. The independent variables in this study could be used to focus Agribank's resources, prioritize the improvement of information asymmetry between customers and banks, development, improvement of policies, processes and procedures for credit, fostering knowledge for credit employee to effectively manage the credit risk at the branch, step by step bringing bad debt down below the threshold allowed by the central bank. This article published in part in a study of author on: Credit risk Management of Agribanks in Hanoi, Vietnam. Keywords: Credit, Credit risk, Credit employees, Information asymmetry, Credit Ppolicy, Procedures, Credit risk management, Agribank. INTRODUCTION The bank is a typical type of financial institution and its main function is trading in money. During the 1980s and 1990s in Vietnam, there were only several state-owned banks participating in the banking industry, so the competition was quite insignificant. The centrally planned subsidized economy ( ) had created monopoly power for the state-owned banks. As a result, the banks served their customers in a bureaucratic and red-tape manner with a deeply rooted attitude existing in a considerable part of the banking employees that the customers need them rather than they need customers. Thus, people used to have great hesitation in working with banks. Since Vietnam opened the economy, then became a member of WTO, a lot of joint stock commercial banks have been established, along with some 100% foreign - invested banks and a number of foreign bank s representative offices. This makes the competition within the banking industry become more and more intensive. To stay firmly and keep thriving in the new business environment, it s necessary that the state-owned banks undertake comprehensive reforms in Page 10

2 terms of four aspects: increase capital capability, offer competitive services (regarding quality, variety, and distinction), build effective branding strategy in response to the requirements of a more open economy. Date 26/03/1998, the Council of Ministers of the Socialist Republic of Vietnam issued Decision No.53/HDBT, the establishment of the Vietnam Bank for Agriculture and Rural Development (Agribank). Agribank is a State-owned enterprise of special grade, operating under the law on credit institutions and under the direct management of the State Bank of Vietnam. Apart from the functions of a commercial bank, the Agribank has further defined development investment tasks for rural areas by expanding medium- and long-term capital for construction. The material and technical facilities for agricultural, forestry and fishery production contribute to successfully implementing the cause of industrialization and modernization of rural agriculture. According to the Decision No.214/QD-NHNN dated 30 January 2011 of the Governor of the State Bank of Vietnam, Agribank was transformed into a one-member limited liability company owned by the state. In November 2011, Agribank was approved by the Government to supplement VND 8,445,47 billion, raising the total chartered capital of Agribank to VND 29,605 billion. As of 31/12/2016, the total assets of Agribank are VND 1,001,204,753 billion. In addition to its capital size, Agribank is also the largest bank in terms of the number of employees and the largest network of commercial banks in Vietnam. Employees of nearly 40,000 people; nearly 2,300 branches and transaction offices, Cambodia branch; agency relationships with more than 1,000 banks in nearly 100 countries and territories; trusted by millions of clients Agribank is also the leading bank in Vietnam to receive and deploy foreign projects, especially projects of the World Bank, Asian Development Bank In recent years, Agribank has been also well known for its reputation as a leading bank providing state-of-the-art and convenient service packs. Since 2010, due to the impact of the global financial crisis and the government's macroeconomic management policies, Agribank has faced many difficulties. In particular, the corruption case at Agribank South Hanoi branch was put to trial in early 2015, the defendants have caused loss of billion banks. The total outstanding loans of the four companies that the former leaders of the bank approved loans with records up to 4,000 billion (Tam. L, 2015). Agribank bad debt includes bad debt on the balance sheet and bad debt off balance sheet was 49,563 billion. In fact, Agribank's NPL ratio is 6.24% much higher than the 3% threshold set by the State Bank of Vietnam (Duong. K, 2017). One of the problems posed for existence and sustainable development of commercial banks is the capacity to manage operational risk, especially credit risk. Credit risk in banking business is often difficult to control and if it happens, its consequences are unpredictable, by the extent of its influence spread to all organizations in society, especially affecting operating macroeconomic policies of the government. Therefore, the identification of factors affecting credit risk management in the commercial bank it requires intensive research in the context of the changing business environment today. RESEARCH METHODOLOGY Research Area: The author focuses on 34 type I Branches of Agribank in Hanoi, Vietnam. These employees are currently working for at least 8 hours per working day at the above Page 11

3 Agriculture Bank branches. In the case of short-term contracts of 12 months or less, "part-time" employees, part-time workers are not surveyed in this study. Determination of sample size: According to the M. H. Alvi (2016), in this study, the total is understood to be the total number (1317) of officially recruited employees working in various positions related to credit operations, with different positions in the branches of Agribank in Hanoi. The formula of Slovin as given by Sevilla, et.al, (1998) could be useful in determining the sample size of the population: the sample chosen in this study when e = 5% and N = 1317 (the size of credit employees in the branches of Agribank in Hanoi, Vietnam), the sample size will be: 1317 n = 307 n = (.05) 2 Assessment scale Credit Handbook, Agribank (2013); Expert Interview Results by Author (2016); Ahmad, N. H., & Ahmad, S. N. (2004); Al-abedallat (2016); Hassan Al-Tamimi & Mohammed Al- Mazrooei (2007); Abedalfattah Zuhair Al-abedallat (2016); To Ngoc Hung (2015); Erika Spuchľáková, Katarína Valašková and Peter Adamkoc(2015) and author proposed. In this questionnaire, the author uses the Likert Scale 5 levels (1. Strongly disagree; 2. Disagree; 3. Neutral; 4. Agree; 5. Strongly agree). At each level of this scale showing different levels of consensus or disagreement among credit employees of Agribanks in Hanoi, Vietnam. In order to measure the factors affecting the CRM in Agribank in Hanoi, the researcher relies on the scale of 5 scales as followed: Scale Approximately Evaluate Strongly Agree Agree Neutral Disagree Strongly Disagree Analytical methods: The author uses AMOS software to analyze the results of data collected which meet the requirements of the research: Scale reliability testing; Exploratory Factor Analysis (EFA); Confirmatory Factor Analysis (CFA). RESEARCH MODEL Based on the theoretical background and qualitative research results. The research model proposed by the author includes five Independent Variables: (1) The efficiency of the employee Page 12

4 in the Bank credit Per. (2) The credit policy and procedures of the Bank Proc. (3) The instructions of the Central bank Inst. (4) Information asymmetry Asy, (5) Risk management system Sys and Dependent Variable is the Credit Risk Management - CRI Figure 1. Research model INDEPENDENT VARIABLES DEPENDENT VARIABLE Based on the proposed research model, the research hypotheses are: H1: The efficiency of the employee in the bank credit has a positive impact on the effectiveness of credit risk management. H2: There is a significantly positive relationship between the instructions of the Central Bank and the credit risk management. H3: The credit policy and procedures of the Bank has a positive impact on the credit risk management at Agribanks. H4: Information asymmetry has a significantly positive impact on the credit risk management at Agribanks. H5: Risk management system has a significantly positive impact on the credit risk management at Agribanks. RESULTS AND DISCUSSION The Result of Scale reliability Page 13

5 Variables with Corrected Item-Total Correlation less than 0.30 will be rejected. The Cronbach's Alpha coefficient of 0.6 or more can be usable in the case of new research (Nunnally, 1994). Cronbach's Alpha range from 0.7 to 0.8 is usually available, scale from 0.8 to 1.0 is a good scale. All variables have Corrected Item - Total Correlation are greater than 0.3 except 1 variable: CRI6 (coefficients of the variables is < 0.3). After eliminating of CRI6 - Establishment of credit policy on the basis of the diversification in the field of credit type and duration, and it reduces the amount of credit risk, the second Cronbach s Alpha has been carried out and the results are as follows table 1. Table 1. The Results of the Cronbach's Alpha - The third time Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Per Alpha = 0,931 Per Per Per Per Per Per Proc Alpha = 0,828 Proc Proc Proc Proc Proc Proc Inst Alpha = 0,859 Inst Inst Inst Inst Inst Asy Alpha = 0,882 Asy Asy Asy Asy Sys Alpha = 0,841 Sys Cronbach's Alpha if Item Deleted Page 14

6 Sys Sys Sys CRI Alpha = 0,937 CRI CRI CRI CRI CRI Source: Processing data of the author Table 1, shows the test reliability of the scale after the variables: Per1, Per2, Per9, Per10, Inst6, Proc7, Proc9, Proc10, Proc8, Asy1, Sys5, Sys6, Sys7, Sys8, CRI6 were excluded in the EFA step because of the coefficient of correlation the total variables are: 0.205, 0.210, 0.120, 0.116, 0.067, 0.267, 0.121, 0.103, 0.285, 0.214, 0.105, 0.114, 0.294, 0.238, respectively, less than 0.3. Thus, the proposed items measure the same concepts and the scales are reliable for using. The results of Exploratory Factor Analysis (EFA) After analyzing Cronbach Alpha for 39 independent variables and 6 dependent variables, we excluded 15 unsatisfactory variables, then continue to analyze EFA. The EFA uses the Principal Axis Factoring extraction method (Gerbing & Nerson, 1988) with a load factor 0.5 (Hair & associates, 1998) for 25 Independent Variables and 5 Dependent Variables. Bartlett's test examines the hypothesis of the correlation between observed variables. The results showed that the KMO = (0.5< = KMO < =1); and Bartlett's Test statistic = Sig = 0.00 < 0.05 (table 2); it means that the application of exploratory factor analysis in the study is appropriate. Moreover, factors have the eigenvalue >1 which explains is greater than 50% (69.606%), the observed variables are grouped exactly as the initial scale (Table 3) Table 2. KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity.901 Approx. Chi-Square df 435 Sig..000 Table 3. Pattern Matrix a Items Per6 - Employees have a broad knowledge to identify industries, occupations and investment areas of high-risk clients. Factors Page 15

7 Per4- Studying for customer credit based on the study of the elements of a credit decision credit as in the model 5Cs. Per3- Employees in bank credit pay attention to studying the cash flow for the customer as the primary source of repayment. Per7- Employees always have a thorough understanding of the procedures, regulations, and laws in credit operations. Per8- When scoring, credit rating loans, I do not ignore any criteria Per5- Employees in bank credit using modern technology in relation to the credit analysis for the client in making a credit decision Proc4- The credit policy of the bank focuses on the credit study of the customers in terms of the ability to pay and a reputation as a basis for decision credit. Proc1- The bank guide of policies and procedures available to all workers in the banking credit. Proc2- The bank cares about the existence of credit risk management and provides it with qualified staff Proc5- The presence of a clear credit policy of the bank reduces the volume of bad debts. Proc3- The credit policy of the bank is built on the basis of diversification in terms of credit type, duration, and granted amounts and accepted guarantees. Proc6- The mechanisms and policies on credit of the bank are flexible and consistent with an economic situation Inst3- The Commercial Bank provides the Central Bank with reports of bank credit periodically Inst2- The Central Bank sets certain limits on bank credit Inst4- The Central Bank sets a ceiling specified, and which might not be exceeded with regard to the granting of credit per customer. Inst1- The central bank makes periodic control of bank credit Page 16

8 Inst5- The control by the central bank on bank credit reduces the volume of bad debts..672 CRI1- Study of the elements of credit decision before the grant reduces the risk of credit Size..972 CRI3- The banking supervision of the Central Bank on extended credit by banks reduces the.920 risks of credit. CRI4- The bank's commitment to the instructions of the central bank lowers the risk of credit.819 CRI2- The focus on cash flows for the client as a principal source of repayment reduces the credit.705 risk. CRI5- The presence of a clear credit policy of the bank reduces the credit risk..687 Asy2- Most of the information and documents collected by the customer do not match the.855 financial records of the tax authorities Asy4- The majority of the conclusions in the analysis of customer records are based solely on the customer information provided and perceived,.824 my work experience. Asy3- I have difficulty in verifying the income information, financial information, real account of.788 the borrower Asy5- Collaboration with organizations and individuals to evaluate the reputation of customers in the market, the relationship between.691 the Bank and customers is a very difficult work. Sys4- Debt classification and risk provision of the branch is very accurate and close to reality.927 Sys1- The credit risk management process is very tight.727 Sys2- The internal control system to monitor the credit risk management of the branch always.673 works well Sys3- Each branch has a separate risk management department with internal control and.653 inspection department. Initial Eigenvalues % of Variance Cumulative % Source: Processing data of the author Page 17

9 Factor loadings are greater than 0.5, and the variables retained exactly as the groups in the original scale (Table 3). Thus, after the analysis of EFA, the model is not different from the proposed model; There are no new factor groups. Confirmatory factor Analysis - CFA The results of confirmatory factor analysis indicates that Chi-square = ; df = 386 (p = <0.05); Chi-square /df = (df <3); TLI = 0.939; CFI = (TLI, CFI > 0.9); GFI = > 0.8 and RMSEA = < The result indicates that correlation coefficients are less than 1, covariance tests and correlations between paired variables are statistically significant (p-value < 0.05, table 4). This implies that the factors in the model can be distinguished. Therefore, it s possible to conclude that the model is compatible with market data (Figure 2). Figure 2: Result of CFA Testing (Standardized) Source: Processing data of the author Table 4. Covariances of Variables Estimate S.E. C.R. P Per <--> Proc *** Per <--> Inst *** Per <--> CRI *** Per <--> Asy *** Per <--> Sys *** Page 18

10 Estimate S.E. C.R. P Proc <--> Inst *** Proc <--> CRI *** Proc <--> Asy *** Proc <--> Sys Inst <--> CRI *** Inst <--> Asy *** Inst <--> Sys *** CRI <--> Asy *** CRI <--> Sys *** Asy <--> Sys *** Source: Processing data of the author Table 5. Composite Reliability and Average Variance Extracted of factors Factors Number Composite Reliability Average Variance of items (CR) Extracted (%) Per % Inst % Proc % Asy % Sys % CRI % Source: Processing data of the author The results of the analysis of Composite Reliability and Extraction Deviation tests show that the factors are unidirectional and the composition of the factor, that is the multivariate scale in the independent variables, meets the requirement of the composite reliability (> 0.6) and the extraction deviation (> = 50%). This suggests that it is possible to consider the factors in the model that have distinguished values and the model is reliable. Determine the significant differences on factors that influence of credit risk management at branches Agribank In this study, the author uses a linear structural model SEM to assess the relevance of the research model and test the relationships in the model (Figure 3) Figure 3. The Results of analyzing by SEM model (Standardized) Page 19

11 Source: Processing data of the author Results of SEM analysis with Chi-square = ; df = 386 (p = <0.05); Chi-square /df = (df <3) ; TLI = 0.939; CFI = (TLI, CFI > 0.9); GFI = 0.866> 0.8 and Root mean square errors of approximation (RMSEA) = < Therefore, it s possible to conclude that the model achieves compatibility with market data. Results of Hypothesis Test Table 6. Results of Hypothesis Test (Hi) Relationships Hypothesis Estimate (Standardized) S.E. C.R. P Results CRI <--- Per H *** Accepted CRI <--- Inst H *** Accepted CRI <--- Proc H *** Accepted CRI <--- Asy H *** Accepted CRI <--- Sys H *** Accepted Source: Processing data of the author Page 20

12 Results of Hypothesis Test shows, the factors: The efficiency of the employee in the Bank credit (Per); The instructions of the Central bank (Inst); The credit policy and procedures of the Bank (Proc); Information asymmetry (Asy) and Risk management systems (Sys) has a positive effect on the credit risk management at branches Agribank in Hanoi, Vietnam. In particular, the most influential factor in the credit risk management at branches Agribank in Hanoi is Information asymmetry (with a coefficient of 0.344), followed by The credit policy and procedures of the Bank (with a coefficient of 0.282) and The instructions of the Central bank (with a coefficient of 0.190). This means, if the Information asymmetry between the customer and the bank is improved, the credit policy and the procedures of the Bank tailored fit than; the instructions of the Central bank improved matching the competition of financial markets will effectively change the effectiveness of credit risk management at Agribank branches in Hanoi, Vietnam. Results of Hypothesis test shows, The efficiency of employee in the Bank credit (with a coefficient of 0.187) and Risk management systems (with a coefficient of 0.163) has a positive effect on the credit risk management. Therefore, the hypotheses H1, H2, H3, H4, H5 are accepted (p-value <0,05) (Table 6). CONCLUSION Credit risk is a very complex type of risk and can occur at any time. Managing credit risk is an important task of commercial banks in general and of Agribank branches in particular. The identifying existing or potential credit risks and implementing sound, prudent credit policies to effectively manage and control risk, implementing effective credit granting and collection processes, are indispensable jobs in credit risk management. demanding managers and Bank employer must perform regularly and comply. From the results of the study, the author concluded and recommended the following: - The results show that information asymmetry variable was the strongest factor to affect credit risk management, followed by the credit policy and procedures of the Bank. and 3 factors are positively correlated pair wise. It means, if the bank wants to improve credit risk management, the bank should focus on information asymmetry variable and the credit policy and procedures of the Bank; - Focusing and prioritizing in-depth training in microeconomics, macroeconomics, economic development strategies in the country and in the world, banking law, Capacity to use information technology for credit employee; - Request State Bank for leaving a ceiling for credit, request bad debts volume for each branch or level of bad debt ratio per year. - The bank should create a clear credit policy for each client group by following the bank law and regulations; need to establish criteria for inspection, monitoring, credit management by the level of each loan and in accordance with the whole portfolio level. Agribank needs to upgrade its credit scoring system and customer ratings are likely to provide early warning signs of possible risks; Page 21

13 - Arranging, positioning jobs in the branch more appropriate. Separating the appraisal department and the loan department into two independent rooms in order to avoid interference in the system and grading according to the subjective desire of the lender. Additional finishing the binding logic criteria for scoring criteria such as in formation of financial statements, Balance Sheet, Business Report... REFERENCES Agribank Credit Handbook. Documents circulated internally. Abedalfattah, A.Z Factors Affecting Credit Risk: An Empirical Study of the Jordanian Commercial Banks. European Scientific Journal December 2016 edition vol.12, No.34 ISSN: (Print) e - ISSN Ahmad, N. H., & Ahmad, S. N. (2004). Key factors influencing credit risk of Islamic bank: A Malaysian case. The Journal of Muamalat and Islamic Finance Research, 1(1), Auronen. L Asymmetric Information: Theory and Applications. Paper presented in the Seminar of Strategy and International Business as Helsinki University of Technology, May 21st Alvi, M.H A Manual for Selecting Sampling Techniques in Research. Anderson, J. C., & Gerbing D. W Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103, Carmines, E.G. & Mciver, J.P Analyzing models with unobserved variables: Analysis of covariance structures, in Social measurement: Current issues, Bohmstedt, G. W & Borgatta, E.F. (ed.), Sage, Beverly Hills, CA, Duong. K. 2017, Available: [Accessed: August ]. Erika Spuchľáková, Katarína Valašková and Peter Adamkocinternational. Conference on Applied Economics, ICOAE 2015, Kazan, Russia. The Credit Risk and its Measurement, Hedging and Monitoring, University of Žilina, Faculty of Operation and Economics of Transport and Communications, Department of Economics, Univerzitná 1, 010, 26, Žilina, Slovak Republic. Hair Jr., J. F. et al., 1998, Multivariate Data Analysis with Readings. Englewood Cliffs, NJ: Prentice-Hall. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E. & Tatham, R. L Multivariate data Page 22

14 analysis (6th edn). Pearson Prentice Hall. Hassan Al-Tamimi, H. A., & Mohammed Al-Mazrooei, F Banks' risk management: a comparison study of UAE national and foreign banks. The Journal of Risk Finance, 8(4), Huong, N. T. T Internal credit rating by market segment at Vietnam Bank for Agriculture and Rural Development. National Economics University. Hung, T. N The Curriculum of Commercial Banks, Dan Tri Publishing House. Nunnally, J.C & Burnstein, I.H.1994, Pschy Chometric Theory, 3rd Edition, New York, NY: McGraw-Hill, Inc Qingsen, Z The commercial bank credit risk and industry Beijing. China financial publishing house, No. 6, Trong, H. & Ngoc, C. N. M Analysis of research data with SPSS, Statistics Publishing House. Richard. E Factors That Cause Non Performing Loans in Commercial Banks in Tanzania and Strategies to Resolve them. Journal of Management Policy and Practice 12(7)2011. Sevilla, C.G., J.A. Ochave, T.G. Punsalan, B.P. Regala and G.G. Uriarte, Introduction Research Methods. UI Press, Jakarta. Solimun, Structural Equation Modeling (SEM). Lisrel and Amos. Malang: Publisher Malang University. YI, W Investigating the Asymmetric Credit Market, China Eastern University. Page 23