الفهرس 
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Abstract
”The aim of this research is to present a proposed hybrid system for the problem of insolvent debts in credit sector which can help the decision maker in Egyptian banks in predicting the actual situation of the client and providing 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 current system in the bank depends only on the client’s failure to pay monthly installments for three consecutive months to start moving and take the necessary actions towards the client. This routine system is the basic reason of happening the problem of loans default. The research presents a different mathematical techniques to predict the default of clients, as well as to devise a modern parallel model to measure the degree of credit risk criteria that guides the bank in the following-up of the client. First the researcher presents a proposed fuzzy model that contains a complete database of non-financial factors used by the decision-maker using fuzzy logic technique, which helps in building the fuzzy rules with great accuracy that helps him 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 researcher sets some real standards to calculate non-financial factors which are related to the client, management, economic situation and project activity. The result of the proposed model concluded that the correlation factor is 95.3% between real successful payment clients and successful model clients. After that the researcher presents a comparative mathematical model to predict the default of clients, as well as to devise a modern parallel model to measure the degree of credit risk criteria that guides the bank in the following-up of the client. Altman model is one of the famous methods for default prediction, formula is used to predict the probability of loan default by using Z-scores. The Z-score is a linear combination of five coefficient-weighted common financial criteria. The researcher applies the Neutrosophic Analytical Hierarchy Process(NAHP) model on the same five common 6financial criteria which the bank can using them to provide constant following-up of the uses of the granted loan to guarantee that all terms set by the bank are met. The information was gathered in the form of neutrosophic data sets and evaluated using a novel Neutrosophic Analytic Hierarchy Process (NAHP) model. The researcher applies the proposed model in the credit department of one of the private Egyptian Banks (QNB) choosing random samples of previous real clients.”