Original Article
International Journal of Fuzzy Logic and Intelligent Systems
Vol. 21, No. 1, March 2021, pp. 66-75
http://doi.org/10.5391/IJFIS.2021.21.1.66
ISSN(Print) 1598-2645
ISSN(Online) 2093-744X
A Proposed Fuzzy Model for Reducing the
Risk of Insolvent Loans in the Credit Sector
as Applied in Egypt
Noha Ibrahem Hasan
1
, Haitham Elghareeb
2
, Farahat Farag Farahat
1
, Ahmed
AboElfotouh
2
1
Department of Information System, Sadat Academy for Administration Science, Cairo, Egypt
2
Faculty of Computers and Information Sciences, Mansoura University, Mansoura, 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.
Keywords: Credit risk, Non-performing loans, Fuzzy information systems, Knowledge base,
Decision making
Received: Jun. 4, 2020
Revised : Jan. 9, 2021
Accepted: Jan. 22, 2021
Correspondence to: Noha Ibrahem Hasan
(noha.hassan2020@sadatacademy.edu.eg)
©The Korean Institute of Intelligent Systems
cc This is an Open Access article distrib-
uted under the terms of the Creative Com-
mons Attribution Non-Commercial License
(http://creativecommons.org/licenses/by-nc /
3.0/) which permits unrestricted non-
commercial use, distribution, and reproduc-
tion in any medium, provided the original
work is properly cited.
1. Introduction
In the Egyptian banking sector, insolvent loans are the most significant risk that banks
encounter. The ratio of non-performing loans and facilities to total loans was 9.1% at the end
of June 2018 [1].
Egyptian banks use traditional models that contain generally accepted statistical rules and
methods while specifically examining the case of the client who wants to obtain a loan. Other
banks have suffered from large losses during the retrieval of these loans due to the failure of
these models to accurately predict the actual situation of the client’s repayment, which led to
their failure to repay the loan installments on time.
The problem of complexity of the nature of non-financial and credit behavior makes it hard
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