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Evaluation of the Credit Risk with Statistical analysis

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  • Asrin Karimi

Abstract

The purpose of this study is to identify important variables that influence on credit risk. Statistical analysis was used. In order to achieve the purpose of this research, a frame of references has been constructed based on a wide literature review. The calculations have been done by using SPSS 18 software. Number of samples was 90 and 5 dependent variables. The achieved results indicate the relation between credit risk and independent variables were considered. The major contribution of this paper is specifying the most important determinants for rating of customers in Iran’s banking sector.

Suggested Citation

  • Asrin Karimi, 2014. "Evaluation of the Credit Risk with Statistical analysis," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 4(3), pages 206-211, July.
    • Handle: RePEc:hur:ijaraf:v:4:y:2014:i:3:p:206-211
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    References listed on IDEAS

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    2. Hussein A. Hassan Al-Tamimi & Faris Mohammed Al-Mazrooei, 2007. "Banks' risk management: a comparison study of UAE national and foreign banks," Journal of Risk Finance, Emerald Group Publishing, vol. 8(4), pages 394-409, August.
    3. Angelini, Eliana & di Tollo, Giacomo & Roli, Andrea, 2008. "A neural network approach for credit risk evaluation," The Quarterly Review of Economics and Finance, Elsevier, vol. 48(4), pages 733-755, November.
    4. Maximilian Hall & Dadang Muljawan & Lolita Moorena, 2009. "Using the artificial neural network to assess bank credit risk: a case study of Indonesia," Applied Financial Economics, Taylor & Francis Journals, vol. 19(22), pages 1825-1846.
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