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Decision Support System for Credit Risk Management: An Empirical Study

Decision Support System for Credit Risk Management: An Empirical Study

Mehmet Resul Bilginci, Gamze Ogcu Kaya, Ali Turkyilmaz
Copyright: © 2019 |Volume: 11 |Issue: 2 |Pages: 14
ISSN: 1935-5688|EISSN: 1935-5696|EISBN13: 9781522564713|DOI: 10.4018/IJISSS.2019040102
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MLA

Bilginci, Mehmet Resul, et al. "Decision Support System for Credit Risk Management: An Empirical Study." IJISSS vol.11, no.2 2019: pp.18-31. http://doi.org/10.4018/IJISSS.2019040102

APA

Bilginci, M. R., Kaya, G. O., & Turkyilmaz, A. (2019). Decision Support System for Credit Risk Management: An Empirical Study. International Journal of Information Systems in the Service Sector (IJISSS), 11(2), 18-31. http://doi.org/10.4018/IJISSS.2019040102

Chicago

Bilginci, Mehmet Resul, Gamze Ogcu Kaya, and Ali Turkyilmaz. "Decision Support System for Credit Risk Management: An Empirical Study," International Journal of Information Systems in the Service Sector (IJISSS) 11, no.2: 18-31. http://doi.org/10.4018/IJISSS.2019040102

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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.

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