Developing a Credit Scoring of the SMEs Manufacturing based on Multi Criteria Decision Making (MCDM) Algorithm release_wnnntyyzifeobol6vw2cdxltdy

by Shakila Saad

Published in Applied mathematics and computational intelligence by Penerbit Universiti Malaysia Perlis.

2025   Volume 14, Issue 1, p12-36

Abstract

Credit risk is a very important risk to banks since failure of borrowers to make required payment will lead to high non-performing loans. Hence, it is necessary for banks to develop a mechanism to gauge the credit risk of its borrowers. One of the methods is credit scoring. Small and Medium Enterprises (SMEs) are the backbone of the Malaysian economy comprising 98.5% of the total business established in Malaysia. Despite their importance, access to finance is relatively limited. According to banks, lending money to SMEs are risky compared to large companies due to few factors such as less of publicly available information, young and lack of collateral. Hence, this study tried to predict the credit risk of SMEs in Malaysia by developing a credit scoring that combined financial and non-financial criteria. This study proposes a credit scoring method based on MCDM algorithm that will be able to forecast the score of the potential borrowers at a certain time by using the historic information. Result obtained is verified via the comparison with the given credit risk level provided by banks and by measuring the correlation. The correlation value is 0.88640526 indicates the high positive linear relationship.
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Type  article-journal
Stage   published
Date   2025-02-17
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ISSN-L:  2289-1315
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