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Decision Support System for Credit Risk Management: An Empirical Study

Author

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  • Mehmet Resul Bilginci

    (Yapı Kredi Bank, Istanbul, Turkey)

  • Gamze Ogcu Kaya

    (Sampoerna University, Jakarta, Indonesia)

  • Ali Turkyilmaz

    (Nazarbayev University, Astana, Kazakhstan)

Abstract

Risk is an integrated part of the banking functions, which cannot be eliminated completely but it can be reduced by employing appropriate techniques. Credit processing is one of the core functions in the banking system, and its performance is closely related to management of the risks. The aim of this article is to develop a credit scorecard model which can be used as decision support system. A logistic regression with stepwise selection method is used to estimate the model parameters. The data that is used to construct the credit scorecard model is obtained from one of the pioneering banks in Turkish Banking Sector. The performance of the developed model is tested using statistical metrics including Receiver Operator Characteristic (ROC) curve and Gini statistics. The result reveals that the model performs well and it can be used as a decision support system for managing the credit risk by managers of the banks.

Suggested Citation

  • Mehmet Resul Bilginci & Gamze Ogcu Kaya & Ali Turkyilmaz, 2019. "Decision Support System for Credit Risk Management: An Empirical Study," International Journal of Information Systems in the Service Sector (IJISSS), IGI Global, vol. 11(2), pages 18-31, April.
    • Handle: RePEc:igg:jisss0:v:11:y:2019:i:2:p:18-31
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