Credit Risk Modeling for Commercial Banks

Asrin Karimi ()

International Journal of Academic Research in Accounting, Finance and Management Sciences, 2014, vol. 4, issue 3, 187-192

Abstract: The aim of this paper is to examine the efficiency of two credit risk modeling (CRM) to predict the credit risk of commercial Iranian banks: (1) Logistic regression model (LRM); (2) Artificial neural networks (ANNs). The calculations have been done by using SPSS and MATLAB software. Number of samples was 316 and 5 dependent variables. The results showed that, artificial neural network is more proper to identify bad customers in commercial bank. The major contribution of this paper is specifying the most important determinants for rating of customers in Iran’s banking sector.

Keywords: Credit risk; modeling; artificial neural network; multiple regression; loan (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hur:ijaraf:v:4:y:2014:i:3:p:187-192

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