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Volume 4 Number 3, Fall 2008 Research Papers Development and validation of credit scoring models Dennis Glennon
US Department of the Treasury, Office of the Comptroller of the Currency, Risk Analysis Division, Third and E Streets, SW, Washington, DC 20219, USA; email: Dennis.Glennon@occ.treas.gov Nicholas M. Kiefer
Department of Economics and Statistical Sciences, Cornell University, 490 Uris Hall, Ithaca, NY 14853-7601, USA; email: Nicholas.kiefer@cornell.edu US Department of the Treasury, Office of the Comptroller of the Currency, Risk Analysis Division, Third and E Streets, SW, Washington, DC 20219, USA; and Center for Research in Econometric Analysis of Time Series, University of Aarhus C. Erik Larson
Promontory Financial Group, 1201 Pennsylvania Avenue, NW, Suite 617, Washington, DC 20004, USA; email: ceriklarson@yahoo.com Hwan-sik Choi
Department of Economics, Texas A&M University, 3035 Allen Building, 4228 TAMU, College Station, TX 77843-4228, USA; email: hwansik.choi@tamu.edu Accurate credit granting decisions are crucial to the efficiency of the decentralized capital allocation mechanisms in modern market economies. Credit bureaus, and many financial institutions, have developed and used credit scoring models to standardize and automate, to the extent possible, credit decisions. We build credit scoring models for bankcard markets using the Office of the Comptroller of the Currency, Risk Analysis Division (OCC/RAD) consumer credit database (CCDB). This unusually rich data set allows us to evaluate a number of methods in common practice.We introduce, estimate and validate our models, using both out-of-sample contemporaneous and future validation data sets. Model performance is compared using both separation and accuracy measures. A vendor-developed generic bureau-based score is also included in the model performance comparisons. Our results indicate that current industry practices, when carefully applied, can produce models
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