This study investigated the development of a knowledge base for expert system for assessment of bank's legal customers. It analyzed the customers' credit risk based on experts' financial ratio analysis. Financial ratios were derived from financial statements of customers; however, the knowledge that helps banking experts to determine the relationship between customers' credit risk and financial situation has been derived from these laws. In this study, expert system considered customer financial ratios as input and prediction of credit risk level as the output. This study was a descriptive-case study research. The population consisted of credit experts of Tejarat bank who were the member of bank's credit Committee and had the right to vote for facilities approval and the individuals whose main task was providing reports for granting facilities and monitoring the use of facilities. After an initial interview and determining the evaluation criteria for facilities and determining the items for each of the criteria, a questionnaire was designed using Likert scale. Data normality test was conducted to ensure the accuracy of the collected data. T-test was performed to realize the selected criteria are important. Then, experts were asked to determine the minimum score for providing the facility to the applicant in each section of the questionnaire. The laws of expert system were provided based on determined minimum scores. Keywords: Risk Management, Credit Risk, Expert SystemIntroduction Based on the information reported by credit agencies, banks and credit card companies, credit rating primarily assesses the loan potential risk to minimize the risk of not refunding the loan. Lenders can use credit ratings in order to determine who is eligible to what sources of loan and to what interest rate. In the general perspective, the credit ratings of previous customers -both loyal and defaulting customers-is used to find the relationship between credit ratings and the set of evaluation criteria.
This study investigated the development of a knowledge base for expert system for credit risk assessment of bank's legal customers. It analyzed the customers' credit risk based on experts' financial ratio analysis. Financial ratios were derived from financial statements of customers; however, the knowledge that helps banking experts to determine the relationship between customers' credit risk and financial situation has been derived from these laws. In this study, expert system considered customer financial ratios as input and prediction of credit risk level as the output. This study was a descriptive-case study research. The population consisted of credit experts of Tejarat bank who were the member of bank's credit Committee and had the right to vote for facilities approval and the individuals whose main task was providing reports for granting facilities and monitoring the use of facilities. After an initial interview and determining the evaluation criteria for facilities and determining the items for each of the criteria, a questionnaire was designed using Likert scale. Data normality test was conducted to ensure the accuracy of the collected data. T-test was performed to realize the selected criteria are important. Then, experts were asked to determine the minimum score for providing the facility to the applicant in each section of the questionnaire. The laws of expert system were provided based on determined minimum scores.
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