A credit scoring model for Vietnam's retail banking market
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- Philosophov, Leonid V. & Philosophov, Vladimir L., 2002. "Corporate bankruptcy prognosis: An attempt at a combined prediction of the bankruptcy event and time interval of its occurrence," International Review of Financial Analysis, Elsevier, vol. 11(3), pages 375-406.
- B Baesens & T Van Gestel & S Viaene & M Stepanova & J Suykens & J Vanthienen, 2003. "Benchmarking state-of-the-art classification algorithms for credit scoring," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(6), pages 627-635, June.
- Venkat Srinivasan & Yong H. Kim, 1987. "Note---The Bierman-Hausman Credit Granting Model: A Note," Management Science, INFORMS, vol. 33(10), pages 1361-1362, October.
- D. J. Hand & W. E. Henley, 1997. "Statistical Classification Methods in Consumer Credit Scoring: a Review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 523-541, September.
- Thomas, Lyn C., 2000. "A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers," International Journal of Forecasting, Elsevier, vol. 16(2), pages 149-172.
- Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
- Bystrom, Hans & Worasinchai, Lugkana & Chongsithipol, Srisuda, 2005.
"Default risk, systematic risk and Thai firms before, during and after the Asian crisis,"
Research in International Business and Finance, Elsevier, vol. 19(1), pages 95-110, March.
- Byström , Hans & Worasinchai , Lugkana & Chongsithipol , Srisuda, 2004. "Default Risk, Systematic Risk and Thai Firms Before, During and After the Asian Crisis," Working Papers 2005:5, Lund University, Department of Economics.
- Blochlinger, Andreas & Leippold, Markus, 2006. "Economic benefit of powerful credit scoring," Journal of Banking & Finance, Elsevier, vol. 30(3), pages 851-873, March.
- Laitinen, Erkki K., 1999. "Predicting a corporate credit analyst's risk estimate by logistic and linear models," International Review of Financial Analysis, Elsevier, vol. 8(2), pages 97-121, June.
- Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
- Allen, Linda & DeLong, Gayle & Saunders, Anthony, 2004. "Issues in the credit risk modeling of retail markets," Journal of Banking & Finance, Elsevier, vol. 28(4), pages 727-752, April.
- Loretta J. Mester, 1997. "What's the point of credit scoring?," Business Review, Federal Reserve Bank of Philadelphia, issue Sep, pages 3-16.
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