A Proposed Fuzzy Model for Reducing the Risk of Insolvent Loans in the Credit Sector as Applied in Egypt

Abstract

Non-financial analysis is one of the varied crucial directive tools of credit study that is used for judging whether the client has a genuine desire to pay the assigned amounts of the loan at its maturity dates. Fuzzy logic can help to solve the problem of dealing with factors of non-financial analysis by converting the linguistic variables to numerical variables to calculate their accuracy. This study proposes a fuzzy model that contains a complete database of non-financial factors used by the decision-maker using a fuzzy logic technique, which helps in building the fuzzy rules with great accuracy and helps in predicting the actual situation of the client. In addition, it provides constant following-up of the uses of the granted loan to guarantee that all terms set by the bank are met so that the bank can avoid future defaulting of the client. The proposed model is applied in the credit department of a private Egyptian bank (QNB), with random samples of previous real clients. Some real standards are set to calculate non-financial factors that are related to the client, management, economic situation, and project activity. The results of the proposed model revealed that the correlation factor is 95.3% between real successful payment clients and successful model clients. To guarantee the accuracy of the knowledge base quality and validation, the knowledge model was presented to the credit manager of the bank under study (expert), who provided a full evaluation of the results of the proposed model compared to the actual situation of clients.