文档介绍：The Impact of Sample Bias on Consumer Credit
Scoring Performance and Profitability
Geert Verstraeten, Dirk Van den Poel
Corresponding author: Dirk Van den Poel
Department of Marketing, Ghent University, Hoveniersberg 24, 9000 Ghent, Belgium
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The Impact of Sample Bias on Consumer Credit
Scoring Performance and Profitability
Abstract
This article seeks to gain insight into the influence of sample bias in a consumer credit
scoring model. Considering the vital implications on revenues and costs concerned with the
issuing and repayment mercial credit, predictive performance of the model is crucial,
and sample bias has been suggested to pose a sizeable threat to profitability due to its
implications on either population drainage or biased estimates. Whereas in previous
research, different techniques of reducing sample bias have been proposed and deployed,
the debate around the impact of sample bias itself has predominantly been held on a
theoretical level. The dataset that was used in this study, however, provides the opportunity
to investigate the issue in an empirical setting. Based on the data of a mail-pany
offering short term consumer credit to their consumers, we show that (i) given a certain
sample size, sample bias has a significant effect on consumer credit-scoring performance and
profitability, (ii) its effect posed of the inclusion of rejected orders in the scoring
model, and the inclusion of these orders into the variable-selection process, (iii) the impact of
the effect of sample bias on consumer credit scoring performance and profitability is limited
and (iv) in consumer credit scoring, by merely increasing the sample size of the biased
sample, the impact of sample bias can likely be reduced. Hence, we conclude that the
possible impact of any reduction of sample bias is modest i