Comparative Mathematical Model forPredicting of Financial Loans Default using Altman Z-Score and Neutrosophic AHP Methods

Abstract

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 problemof loansdefault. In this paper 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-upof 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 NeutrosophicAnalytical Hierarchy Process(NAHP) model on the same five common financial 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 real clients.