Preview

Review of Business and Economics Studies

Advanced search

Applying Discriminant Model to Manage Credit Risk for Consumer Loans in Vietnamese Commercial Bank

Abstract

This study estimates a two-group discriminant function to determine the expected financial health of the consumer credit customers’ of a bank of Vietnam by using five demographic, socio-economic, and loan characteristics of the sample borrowers. The estimated function is significant at one per cent level of significance and the model estimates financial health/group membership with average seventy-three per cent accuracy. Like developed countries, it is expected that use of the estimated discriminant function in the consumer credit decision making will decrease bad debts, will help to set risk based credit pricing for the clients and will make the credit granting faster and more accurate.

About the Authors

T. D. Nguyen
Banking Academy of Vietnam
Russian Federation


T. T. Do
Banking Academy of Vietnam
Russian Federation


B. N. Nguyen
Banking Academy of Vietnam
Russian Federation


References

1. Awh R.Y., & Waters D. (1974). A Discriminant Analysis of Economic, Demographic and Attitudinal Characteristics of Bank Charge-Card Holders: A Case Study. The Journal of Finance, 29 (3), 973-980. Available at: http://dx.doi.org/10.2307/2978604.

2. Boyd H.W. Jr., Westfall R., & Stasch S.F. (2005). Marketing Research: Text and Cases (7th ed., pp. 598-603). Richard D. Irwin, Inc., Homewood, Illinois-60430.

3. Capon N. (1982). Credit Scoring Systems: A Critical Analysis. Journal of Marketing, 46 (Spring), pp. 82-91. Available at: http://dx.doi.org/10.2307/3203343.

4. Credit Card Redlining. (1979). Hearings Before the Subcommittee on Consumer Affairs of the Committee on Banking, Housing and Urban Affairs, United States Senates, 96th Congress, Fist Session, on 15, June 4 & 5, 1979, Washington DC, U.S. Government Printing Office, pp. 183-184.

5. Davis R.H., Edelman D.B., & Gammerman A.J. (1992). Machine-Learning Algorithms for Credit Applications. IMA J. Math. Appl. Bus. Industry, 4, 43-51. Available at: http://dx.doi.org/10.1093/imaman/4.1.43.

6. Dinh T.H. T., & Kleimeier S. (2007). A Credit Scoring Model for Vietnam’s Retail Banking Market. International Review of Financial Analysis, 16 (5), pp. 571-495. Available at: http://dx.doi.org/10.1016/j.irfa.2007.06.001.

7. George D., & Mallery P. (2006). SPSS for Windows Step by Step: A Simple Guide and Reference, 13.0 Update (6th ed., pp. 278-292), Pearson Education.

8. Glen J.J. (2001). Classification Accuracy in Discriminant Analysis: A Mixed Integer Programming Approach. The Journal of Operational Research Society, 52 (3), 328. Available at: http://dx.doi.org/10.1057/palgrave.jors.2601085.

9. Khemakhem S., & Boujelbene Y. (2015). Credit risk prediction: A comparative study between discriminant analysis and the neural network approach. Accounting and Management Information Systems, 14 (1), 60.

10. Abdou H. & Pointon J. (2011). Credit scoring, statistical techniques and evaluation criteria: a review of the literature, Intelligent Systems in Accounting, Finance & Management, 18 (2-3), pp. 59-88.

11. Mircea G., Pirtea M., Neamtu M., & Bazavan S. (2011). Discriminant analysis in a credit scoring model. Paper of Faculty of Economics and Business Administration West University of Timisoara, Romania.

12. Bank nonperforming loans to total gross loans. Available at: http://data.worldbank.org/indicator/FB.AST.NPER.ZS?locations=VN.

13. Elena Bartolozzi, Matthew Cornford, Leticia García-Ergüín, Cristina Pascual Deocón, Oscar Iván Vasquez & Fransico Javier Plaza. (2008). Credit Scoring Modelling for Retail Banking Sector. II Modelling Week, Universidad Complutense de Madrid, 16th - 24th June 2008. Available at: http://www.mat.ucm.es/momat/2008mw/creditscoring.pdf.

14. Thanh Thi Huyen Dinh, Stefanie Kleimeier, Stefan Straetmans. Bank Lending Strategy, Credit Scoring and Financial Crises. School of Business and Economics, Maastricht University, Maastricht, The Netherlands. Available at: http://stefanstraetmans.com/attachments/File/KD_SK_SS_CreditScoring_final.pdf.

15. Hörkkö M. (2010). The determinants of default in consumer credit market. Available at: http://epub.lib. aalto.fi/en/ethesis/pdf/12299/hse_ethesis_12299.pdf.

16. Duong T., Tran V., & Ho Q. (2015, January). A Proposed Credit Scoring Model for Loan Default Probability: a Vietnamese bank case. In International Conference on Qualitative and Quantitative Economics Research (QQE). Proceedings (p. 52). Global Science and Technology Forum.

17. Hintze J. (1998). NCSS statistical software. NCSS, Kaysville, UT.


Review

For citations:


Nguyen T.D., Do T.T., Nguyen B.N. Applying Discriminant Model to Manage Credit Risk for Consumer Loans in Vietnamese Commercial Bank. Review of Business and Economics Studies. 2016;4(4):5-16. (In Russ.)



ISSN 2308-944X (Print)
ISSN 2311-0279 (Online)