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Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution

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  • Ha-Thu Nguyen

Abstract

The aim of this paper is to present the set-up of a behavioral credit-scoring model and to estimate such a model using the auto loan data set of one of the largest multinational financial institutions based in France. We rely on a 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 model possesses the desirable characteristics of a scorecard.

Suggested Citation

  • Ha-Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," EconomiX Working Papers 2014-26, University of Paris Nanterre, EconomiX.
  • Handle: RePEc:drm:wpaper:2014-26
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    More about this item

    Keywords

    Auto Loans; Credit Risk; Credit Scoring; Logistic Regression.;
    All these keywords.

    JEL classification:

    • G3 - Financial Economics - - Corporate Finance and Governance
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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