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Using Multiple Discriminant Analysis to Construct a Statistical Model for Predicting Bank Loan Repay and Default Custo...
ISSN: 2026 - 6480
Publisher: author
Using Multiple Discriminant Analysis to Construct a Statistical Model for Predicting Bank Loan Repay and Default Custo...
Indexed in
Mathematics and Statistics
ARTICLE-FACTOR
1.3
Article Basics Score: 2
Article Transparency Score: 3
Article Operation Score: 2
Article Articles Score: 3
Article Accessibility Score: 2
SUBMIT PAPER ASK QUESTION
International Category Code (ICC):
ICC-1102
Publisher: Koforidua Technical University
International Journal Address (IAA):
IAA.ZONE/2026394366480
eISSN
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2026 - 6480
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Abstract
Banks that lend to small businesses and individuals need to quickly assess the creditworthiness of prospective borrowers so as to reduce the probability of issuing bad loans while attempting to maintain their own profitability. It was for these reasons that credit institutions have made several attempts at modeling and reliably forecasting credit default using numerous statistical approaches. The objective of the study was to develop a model which could be used to identify likely future defaulters. The population for the study was all financial institutions were in the Eastern Region of Ghana. A number of banks that could give the needed data for the study was purposefully chosen and a random sample of 150 customers were randomly selected to provide data on the study variables which include customers
