Rating the Actual Customers of Banks based on Credit Risk using Multiple Criteria Decision Making and Artificial Intelligence Hyperbolic Regression
Publish Year: 1399
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJFMA-4-16_005
تاریخ نمایه سازی: 13 آذر 1400
Abstract:
This study wants to investigate the rating of the actual customers of banks based on credit risk using multiple criteria decision making and artificial intelligence hyperbolic regression. This is an applied research. The statistical population of the study includes the credit customers of Agriculture Bank in west branches of Mazandaran province, Iran in ۲۰۱۲-۲۰۱۶. A total of ۱۰۰ cases have been evaluated. AHP method has been used in the case of elites' comments on the prioritized seven key factors using the corresponding weighting matrix. To model the classes of creditworthy and non-creditworthy customers and to predict the appropriate model based on the evidence in the customer's credit file, artificial intelligence hyperbolic regression has been employed. Using AHP method, the rating include customer revenue, credit in the market, customers' job, the duration of the relationship with the bank, the type of collateral, the value of collateral, average account balance to facilitate the credit risk of the actual customers, respectively. Using artificial intelligence hyperbolic regression, prioritization is based on the amount of credit in the market, customer revenue, the value of collateral, the duration of the relationship with the bank, the type of collateral and customers' job.
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Authors
Reza Ehtesham Rasi
Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran. (Corresponding Author)
Meysam Karamipour
Ph.D. Student, Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Morteza Arad
Assessment Management of Keshavarzi Bank in Mazandaran Province, Nashtaroud Branch in Tonekabon
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