The consumer loan default predicting model - An application of DEA-DA and neural network

Expert Systems with Applications

Volumn 36, Issue 9, 2009, Pages 11682-11690

  Tsai, Ming Chun ^a   Lin, Shu Ping ^a   Cheng, Ching Chan ^a   Lin, Yen Ping ^a  

^a CHUNG HUA UNIVERSITY   (Taiwan)

Author keywords

Consumer loans; DEA; DEA DA; Logistic regression; Money attitude; Neural networks

Indexed keywords

CONSUMER LOANS; DEA; DEA-DA; LOGISTIC REGRESSION; MONEY ATTITUDE;

NEURAL NETWORKS;

DATA ENVELOPMENT ANALYSIS;

EID: 67349143950     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2009.03.009     Document Type: Article

References (41)

1. Avery R.B., Calem P.S., and Canner G. Consumer credit scoring: Do situational circumstances matter?. Journal of Banking and Finance 28 (2004) 835-856
2. Baesens B., Gestel T.V., Stepanova M., Poel D.V.D., and Vanthienen J. Neural network survival analysis for personal loan data. Journal of the Operational Research Society 56 (2005) 1089-1098
3. Brill J. The importance of credit scoring models in improving cash flow and collections. Business Credit 1 (1998) 16-17
4. Chen M.C., and Huang S.H. Credit scoring and rejected instances reassigning through evolutionary computation techniques. Expert Systems with Applications 24 (2003) 433-441
5. Chen H., and Volpe R. An analysis of personal financial literacy among college students. Financial Services Review 7 2 (1998) 107-128
6. Chiang R.C., Chow Y.F., and Liu M. Residential mortgage lending and borrower risk: The relationship between mortgage spreads and individual characteristics. Journal of Real Estate Finance and Economics 25 1 (2002) 5-32
7. Crook J., and Banasik J. Does reject inference really improve the performance of application scoring models?. Journal of Banking and Finance 28 (2004) 857-875
8. Desai V.S., Crook J.N., and Overstreet Jr. G.A. A comparison of neural networks and linear scoring models in the credit union environment. European Journal of Operational Research 95 1 (1996) 24-37
9. Freeman J.A., and Skapura D.M. Neural networks algorithms, applications, and programming techniques (1992), Addison-Wesley, New York
10. Frydman H.E., Altman E.I., and Kao D. Introducing recursive partitioning for financial classification: The case of financial distress. Journal of Finance 40 1 (1985) 269-291
11. Hardy Jr. W.E., and Adrian Jr. J.L. A linear programming alternative to discriminant analysis in credit scoring. Agribusiness 1 4 (1985) 285-292
12. Hayhoe C.R., Leach L., and Turner P.R. Discriminating the number of credit cards held by college students using credit and money attitudes. Journal of Economic Psychology 20 (1999) 643-656
13. Jacobs-Lawson J.M., and Hershey D.A. Influence of future time perspective, financial knowledge, and financial risk tolerance on retirement savings behaviors. Financial Services Review 14 (2005) 331-344
14. Lee T.S., and Chen I.F. A two-stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines. Expert Systems with Applications 28 4 (2005) 743-752
15. Lee T.S., Chiu C.C., Chou Y.C., and Lu C.J. Mining the customer credit using classification and regression tree and multivariate adaptive regression splines. Computational Statistics and Data Analysis 50 (2006) 1113-1130
16. Lee T.S., Chiu C.C., Lu C.J., and Chen IF. Credit scoring using the hybrid neural discriminant technique. Expert Systems with Applications 23 3 (2002) 245-254
17. Lim V.K.G., and Teo T.S.H. Sex, money and financial hardship: An empirical study of attitudes towards money among undergraduates in Singapore. Journal of Economic Psychology 18 (1997) 369-386
18. Lim V.K.G., Teo T.S.H., and Loo G.L. Sex, financial hardship and locus of control: An empirical study of attitudes towards money among Singaporean Chinese. Personality and Individual Differences 34 (2003) 411-429
19. Lin, S. P., & Lin, Y. P. (submitted for publication). Influence of money attitude toward consumer loan behavior. Applied Financial Economics.
20. Li S.T., Shiue W., and Huangc M.H. The evaluation of consumer loans using support vector machines. Expert Systems with Applications 30 (2006) 772-782
21. Malhotra R., and Malhotra D.K. Differentiating between good credits and bad credits using neuro-fuzzy systems. European Journal of Operational Research 136 (2002) 190-211
22. Mandell, L. (2005). The connection between saving financial literacy. National Credit Union Youth Week (April 17-23).
23. Noh P.J., Rohb T.H., and Hana I. Prognostic personal credit risk model considering censored information. Expert Systems with Applications 28 (2005) 753-762
24. Ong C.S., Huang J.J., and Tzeng G.H. Building credit scoring models using genetic programming. Expert Systems with Applications 29 (2005) 41-47
25. Roberts J.A., and Jones E. Money attitudes, credit card use, and compulsive buying among American college students. The Journal of Consumer Affairs 35 (2001) 213-240
26. Roberts J.A., and Sepulveda M.C.J. Demographics and money attitudes: A test of Yamauchi and Templer's (1982) money attitude scale in Mexico. Personality and Individual Differences 27 (1999) 19-35
27. Rock A. Sure ways to score with lender. Money (1984)
28. Roszbach K. Bank lending policy, credit scoring and the survival of loans. The Review of Economics and Statistics (2004) 1-30
29. Salchenberger L.M., Cinar E.M., and Lash N.A. Neural networks: A new tool for predicting thrift failures. Decision Sciences 23 4 (1992) 899-916
30. Steenackers A., and Goovaerts M.J. A credit scoring model for personal loans. Insurance: Mathematics and Economics 8 1 (1989) 31-34
31. Sueyoshi T. DEA-discriminant analysis in the view of goal programming. European Journal of Operational Research 115 (1999) 564-582
32. Sueyoshi T. Mixed integer programming approach of extended DEA-discriminant analysis. European Journal of Operational Research 152 (2004) 45-55
33. Sueyoshi T. Financial ratio analysis of the electric power industry. Asia-Pacific Journal of Operational Research 22 3 (2005) 349-376
34. Sueyoshi T. DEA-discriminant analysis: Methodological comparison among eight discriminant analysis approaches. European Journal of Operational Research 169 (2006) 247-272
35. Sueyoshi T., and Hwang S.N. A use of nonparametric tests for DEA-discriminant analysis: A methodological comparison. Asia-Pacific Journal of Operational Research 21 2 (2004) 179-195
36. Thomas L.C. A survey of credit and behavioural scoring: Forecasting financial risk of lending to consumers. International Journal of Forecasting 16 2 (2000) 149-172
37. Updegrave W.L. How lender size you up. Money (1987)
38. Vellido A., Lisboa P.J.G., and Vaughan J. Neural networks in business: A survey of applications (1992-1998). Expert Systems with Applications 17 (1999) 51-70
39. West D. Neural network credit scoring models. Computers and Operations Research 27 11-12 (2000) 1131-1152
40. Yamanchi K.T., and Templer D.I. The development of a money attitude scale. Journal of Personality Assessment 46 5 (1982) 523-528
41. Zandi M. Incorporating economic information into credit risk underwriting. In: Mays E. (Ed). Credit risk modeling (1998), Glenlake Publishing, Chicago