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الصفحة الرئيسية » الإصدار 2، العدد 2 ـــــ فبراير 2023 ـــــ Vol. 2, No. 2 » Assessment of Credit Risk in Banks using Machine Learning and Fuzzy Logic Techniques

Assessment of Credit Risk in Banks using Machine Learning and Fuzzy Logic Techniques

Authors

M.Sc. of Business Information Systems, Business Intelligence, Helwan University

[email protected]

Abstract

Credit risk rating is a method of measuring the credit worthiness of enterprises and banks by analyzing their historical data. Credit risk rating is one of the most important problems in finance. Most Egyptian commercial banks are unable to determine and predict credit risk rating and so far, there is no accurate model in Egypt for determining and predicting for credit risk rating of these commercial banks. In this paper, the researchers propose a fuzzy logic-based model that can be used to assist in determining and predicting bank credit risk rating. Taking the rating scale of Moody’s as an output for the proposed model. The proposed model is based on financial ratios used in Egyptian commercial banks i.e., profitability, debt-paying ability, operation ability, and liquidity to determine their credit risk rating. This model was implemented using fuzzy logic in MATLAB and applied to CIB Egyptian commercial bank. This model could help the decision-makers in the Egyptian commercial banks to determine accurately the credit risk rating of these banks.