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

Abstract

One of the most important factors of survival of financial institutes and banks in the current competitive markets is to create balance and equality among resources and consumptions as well as to keep the health of money circulation in these institutes. According to the experiences obtained from recent financial crises in the world. The lack of appropriate management of the demands of banks and financial institutions can be considered as one of the main factors of occurrence of this crisis. 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. The method of collecting theoretical framework was library research and the data were collected by two ways of data of a questionnaire and real customers’ financial data. To analyze the data of the questionnaire, 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. The final model was presented and with 95% of probability, if the next customer’s data is entered the model, it will capable of identifying accurately the degree of customer risk.

Keywords

• Risk
• Risk management
• Credit risk
• Customer classification