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Comparison of Artificial Neural Networks and Logistic Regression Analysis in the Credit Risk Prediction

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Author(s): Hüseyin BUDAK | Semra ERPOLAT

Journal: AJIT-e : Online Academic Journal of Information Technology
ISSN 1309-1581

Volume: 3;
Issue: 9;
Start page: 23;
Date: 2012;
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Keywords: Artificial Neural Networks | Logistic Regression | Credit Risk Prediction

ABSTRACT
Credit scoring is a vital topic for Banks since there is a need to use limited financial sources more effectively. There are several credit scoring methods that are used by Banks. One of them is to estimate whether a credit demanding customer’s repayment order will be regular or not. In this study, artificial neural networks and logistic regression analysis have been used to provide a support to the Banks’ credit risk prediction and to estimate whether a credit demanding customers’ repayment order will be regular or not. The results of the study showed that artificial neural networks method is more reliable than logistic regression analysis while estimating a credit demanding customer’s repayment order.
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