Classification of Customers of Banking Network Based on Credit Risk with Anticipating Models and Multiple Indicators Decision Making

Document Type : Original Article

Authors

1 Assistant Professor of Accounting, University of Kurdistan

2 Assistant Professor of Public Management, Payame Noor University, Tehran, Iran

3 M.A. Student of Accounting, University of Kurdistan, Sannandaj, Iran

Abstract

The purpose of this study is to classify customers of banking network on the basis of credit risk with anticipating models and multiple indicators decision making. Because one of the major factors in banking is credit risk, therefore, banks are interested in decreasing the credit risk using different methods. Descriptive data were randomly collected from 385 customer documents (250 individual customers and 135 company customers) of Melli Bank of Iran. The results indicate that both models of TOPSIS and LOGIT can be used in classifying good and bad customers by managers of credit institutes; however, TOPSIS model can better estimate than LOGIT.

Keywords

Journal of Iranian Accounting Review
Volume 3, Issue 9
April 2016
Pages 81-108

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