Assessment of Credit Status of Bank Loan Applicants Using CBR Method

Credit risk assessment is one of the key issues for banks and financial institutions and various models have been developed for this. This study uses Case Based reasoning (CBR) Model and considers a database of bank credit customers to assess the credit risk of bank applicants. For this, 9 criteria were selected based on the experts' opinion and were weighted using the Fuzzy Analytical Hierarchy Process (FAHP). Return check, housing situation and income level are the most important criteria for credit risk assessment of the bank applicants. Then, using the TOPSIS Technique, we could evaluates the similarity of the new item with actual past cases or evaluate the new applicant with the ideal option, and uses a case-based reasoning model to predict the likelihood of default or non-default applicants. Survey research was applied for this study and the research community was the records of previous bank applicants between 1390-94 years.