Consumer Credit Scoring

Alexandru Costangioara ()
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Alexandru Costangioara: Oradea University, Faculty of Economic Studies

Journal for Economic Forecasting, 2011, issue 3, 162-177

Abstract: After presenting the main issues in consumer credit market and introducing the issue of credit scorecards, I have used statistical modeling to predict the default probabilities of applicants in a dataset of consumer loans. I have found evidence for the superior accuracy of complex non-linear estimations. In particular, the bagging model offers better results than the traditional tree and logit estimations. The proposed statistical scorecard offers a 60 percent improvement over the baseline model. Lastly, this paper argues that the management must establish a decisional probability threshold in accordance with its propensity for risk. A higher threshold requires a greater promotional effort, although the increased costs may be compensated by a more efficient communication with clients and by more flexible contractual clauses.

Keywords: credit market; prudential regulation; statistical scorecards; logit; bagging estimations (search for similar items in EconPapers)
JEL-codes: C13 G21 (search for similar items in EconPapers)
Date: 2011
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