Sample Selection Bias in Acquisition Credit Scoring Models: An Evaluation of the Supplemental-Data Approach
Journal of Credit Risk, (9.3 - 2013)
43 Pages Posted: 9 Dec 2010 Last revised: 16 Jul 2014
Date Written: April 1, 2013
Models evaluating credit applicants rely on payment performance data, which is only available for accepted applicants. This sampling limitation could lead to biased parameter estimates. We use a nationally representative sample of credit bureau records to examine sample selection bias in account acquisition scoring models and to evaluate the effectiveness of the industry practice of using proxy payment performance for rejected applicants. Our results show that ignoring the rejected applicants significantly affects forecast accuracy of credit scores while it has little effect on their discriminatory power. Finally, we document that validating scores only on accepted applicants can be misleading.
Keywords: credit scoring, sample selection bias, reject inference, validation
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