A neural network model for credit risk evaluation.

Intelligent Systems Research Group, Near East University, Lefkosa, Mersin 10, Turkey.
International Journal of Neural Systems (Impact Factor: 5.05). 09/2009; 19(4):285-94. DOI: 10.1142/S0129065709002014
Source: PubMed

ABSTRACT Credit scoring is one of the key analytical techniques in credit risk evaluation which has been an active research area in financial risk management. This paper presents a credit risk evaluation system that uses a neural network model based on the back propagation learning algorithm. We train and implement the neural network to decide whether to approve or reject a credit application, using seven learning schemes and real world credit applications from the Australian credit approval datasets. A comparison of the system performance under the different learning schemes is provided, furthermore, we compare the performance of two neural networks; with one and two hidden layers following the ideal learning scheme. Experimental results suggest that neural networks can be effectively used in automatic processing of credit applications.

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