%0 Journal Article
%T Comparison of Artificial Neural Networks and Logistic Regression Analysis in the Credit Risk Prediction
%A H¨¹seyin BUDAK
%A Semra ERPOLAT
%J AJIT-e : Online Academic Journal of Information Technology
%D 2012
%I AJIT-e
%R 10.5824/1309-1581.2012.4.002.x
%X 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.
%K Artificial Neural Networks
%K Logistic Regression
%K Credit Risk Prediction
%U http://www.ajit-e.org/download_pdf.php?id=58&f=58_rev1.pdf