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How to Measure the Quality of Credit Scoring Models

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    Abstract

    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.

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    File URL: http://journal.fsv.cuni.cz/storage/1228_rezac.pdf
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    Bibliographic Info

    Article provided by Charles University Prague, Faculty of Social Sciences in its journal Finance a uver - Czech Journal of Economics and Finance.

    Volume (Year): 61 (2011)
    Issue (Month): 5 (November)
    Pages: 486-507

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    Handle: RePEc:fau:fauart:v:61:y:2011:i:5:p:486-507

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    Related research

    Keywords: credit scoring; quality indices; lift; profit; normally distributed scores;

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    1. Anderson, Raymond, 2007. "The Credit Scoring Toolkit: Theory and Practice for Retail Credit Risk Management and Decision Automation," OUP Catalogue, Oxford University Press, number 9780199226405, September.
    2. Engelmann, Bernd & Hayden, Evelyn & Tasche, Dirk, 2003. "Measuring the Discriminative Power of Rating Systems," Discussion Paper Series 2: Banking and Financial Studies 2003,01, Deutsche Bundesbank, Research Centre.
    3. Evzen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," William Davidson Institute Working Papers Series wp1015, William Davidson Institute at the University of Michigan.
    4. Jiri Witzany, 2011. "Definition of Default and Quality of Scoring Functions," Bulletin of the Czech Econometric Society, The Czech Econometric Society, vol. 18(28).
    5. 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.
    6. Roger Newson, 2006. "Confidence intervals for rank statistics: Somers' D and extensions," Stata Journal, StataCorp LP, vol. 6(3), pages 309-334, September.
    7. 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.
    8. Thomas, Lyn C., 2009. "Consumer Credit Models: Pricing, Profit and Portfolios," OUP Catalogue, Oxford University Press, number 9780199232130, September.
    9. 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.
    10. Martin Vojtek & Evžen Koèenda, 2006. "Credit-Scoring Methods (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 56(3-4), pages 152-167, March.
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