Default Predictors in Credit Scoring: Evidence from France's Retail Banking Institution

26 Pages Posted: 16 Jun 2016

See all articles by Ha-Thu Nguyen

Ha-Thu Nguyen

University Paris West Nanterre La Defense

Date Written: June 01, 2015

Abstract

The aim of this paper is to present the set-up of a behavioral credit-scoring model and estimate such a model using an auto loan data set of one of the largest multinational financial institutions based in France. We rely on the logistic regression approach, which is commonly used in credit scoring, to construct a behavioral scorecard. A detailed description of the model-building process is provided, as are discussions about specific modeling issues. The paper then uses a number of quantitative criteria to identify the model best suited to modeling. Finally, it is demonstrated that such a model possesses the desirable characteristics of a scorecard.

Keywords: Auto Loans, Behavioral Scorecard, Credit Risk, Credit Scoring, France, Logistic Regression

Suggested Citation

Nguyen, Ha-Thu, Default Predictors in Credit Scoring: Evidence from France's Retail Banking Institution (June 01, 2015). Journal of Credit Risk, Vol. 11, No. 2, Pages 41–66, 2015. Available at SSRN: https://ssrn.com/abstract=2795520

Ha-Thu Nguyen (Contact Author)

University Paris West Nanterre La Defense ( email )

200, avenue de la Republique
Nanterre, 92000
France

Register to save articles to
your library

Register

Paper statistics

Downloads
0
Abstract Views
896
PlumX Metrics