How to Measure the Quality of Credit Scoring Models
Credit scoring models are widely used to predict the probability of client default. To measure the quality of such scoring models it is possible to use quantitative indices such as the Gini index, Kolmogorov-Smirnov statistics (KS), Lift, the Mahalanobis distance, and information statistics. This paper reviews and illustrates the use of these indices in practice.
Volume (Year): 61 (2011)
Issue (Month): 5 (November)
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William Davidson Institute Working Papers Series
wp1015, William Davidson Institute at the University of Michigan.
- Evžen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," Emerging Markets Finance and Trade, M.E. Sharpe, Inc., vol. 47(6), pages 80-98, November.
- Crook, Jonathan N. & Edelman, David B. & Thomas, Lyn C., 2007. "Recent developments in consumer credit risk assessment," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1447-1465, December.
- 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.
- Thomas, Lyn C., 2009. "Consumer Credit Models: Pricing, Profit and Portfolios," OUP Catalogue, Oxford University Press, number 9780199232130.
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