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How is credit scoring used to predict default in China?

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  • Ha-Thu Nguyen

Abstract

In this paper, we carry out a review of literature for both traditional and sophisticated credit assessment techniques, with a particular focus on credit scoring which is broadly used as a costeffective credit risk management tool. The objective of the paper is to present a set-up of an application credit-scoring model and to estimate such a model using an auto loan data-set of one of the largest automobile manufacturers in China. The logistic regression approach, which is widely used in credit scoring, is employed to construct our scorecard. A detailed step-by-step development process is provided, as are discussions about specific modeling issues. The paper finally shows that “married”, “house owner”, “female”, age in years, “working in public institutions, foreign, or joint venture companies”, down payment rate, and maximum months on book of current accounts negatively impact the probability of default.

Suggested Citation

  • Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
    • Handle: RePEc:drm:wpaper:2015-1
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    File URL: http://economix.fr/pdf/dt/2015/WP_EcoX_2015-01.pdf
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    Cited by:

    1. Tomáš Vaněk & David Hampel, 2017. "The Probability of Default Under IFRS 9: Multi-period Estimation and Macroeconomic Forecast," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(2), pages 759-776.

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    More about this item

    Keywords

    Credit Risk; Credit Scoring; Auto Loans; 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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