Application of Fuzzy Delphi Integrated Approach / Multiple Logistic Regression in Identifying and Assessing the Credit Risk of Real Bank Mellat Customers

The purpose of this study is to validate the real customers of Bank Mellat using fuzzy Delphi approach and multiple logistic regression. For this purpose, first, the effective indicators on assessing the credit risk of real customers were identified by library method and then, the fuzzy Delphi method was used and the indicators were screened. The community of this section was formed by banking experts (Bank Mellat) who were selected by snowball method. Then, the final data related to the indicators, including the files of 7318 real customers of Bank Mellat during the years 2014-2020, were collected and analyzed by multiple logistic regression method in four categories of timely receipt, past due date, delinquent and doubtful receipt. The results showed that the loan amount, loan repayment time, installment interval, installment amount, loan extension, previous loan, real estate collateral, inventory average, facility interest rate and education level have a significant effect on credit risk of real customers. Also, the significance of gender, age and occupation indices was not confirmed.