tailieunhanh - Customer classification in banking system of Iran based on the credit risk model using multi-criteria decision-making models

The objective of the present study is to identify and classify customers according to credit risk and decisions of predictive models. The present research is a survey research employing field study in terms of the data collection method. | Customer classification in banking system of Iran based on the credit risk model using multi-criteria decision-making models Accounting 2 2016 177 184 Contents lists available at GrowingScience Accounting homepage ac Customer classification in banking system of Iran based on the credit risk model using multi- criteria decision-making models Khalil Khalilia and Kamal Khalilpourb Department of Management Mahabad Branch Islamic Azad University Mahabad Iran CHRONICLE ABSTRACT Article history One of the most important factors of survival of financial institutes and banks in the current Received December 5 2015 competitive markets is to create balance and equality among resources and consumptions as Received in revised format well as to keep the health of money circulation in these institutes. According to the experiences February 16 2016 obtained from recent financial crises in the world. The lack of appropriate management of the Accepted March 12 2016 Available online demands of banks and financial institutions can be considered as one of the main factors of March 14 2016 occurrence of this crisis. The objective of the present study is to identify and classify customers Keywords according to credit risk and decisions of predictive models. The present research is a survey Risk research employing field study in terms of the data collection method. The method of collecting Risk management theoretical framework was library research and the data were collected by two ways of data of Credit risk a questionnaire and real customers financial data. To analyze the data of the questionnaire Customer classification analytical hierarchy process and to analyze real customers financial data the TOPSIS method were employed. The population of the study included files of real customers in one of the branches of RefahKargaran Bank in city of Tabriz Iran. From among 800 files 140 files were completed and using Morgan s table 103 files were investigated. .