COMBINATION OF DISCRIMINANT ANALYSIS AND ARTIFICIAL NEURAL NETWORK IN THE ANALYSIS OF CREDIT CARD CUSTOMERS
Istanbul Arel University, Turkey
The decrease in the rate of legal proceedings for the bank loans in the last two years caused an increase in the importance of efficiency along with a decrease in financial resources. When it is paid attention to the distribution in the rate of non-performing loan, it is seen that the most important share belongs to credit cards. Efficient risk management in banking and efficient use of resources depends on taking the necessary actions today by forecasting the potential risks. This study is directed to quick and correct assessment of the credibility of credit card customers. The objective of this study is to present an alternative approach regarding the assessment of credit card customers by using discriminant and artificial neural network methods together. The analysis, applied to the data set which is comprised of 133 samples and being comprised of discriminant and artificial neural network combination, was found to be statistically significant.
Key Words:Credit Cards, Banking, Financial Crisis, Discriminant Analysis, Artificial Neural Networks.
JEL codes:C44, C45, G21.