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Applying Neural Networks for Loan Decisions in the Jordanian Commercial Banking System


Shorouq Fathi Eletter, Saad Ghaleb Yaseen


Vol. 10  No. 1  pp. 209-214


Artificial Neural Networks play an increasingly important role in financial applications for such tasks as pattern recognition, classification, and time series forecasting. This study develops a proposed model that identifies artificial neural network as an enabling tool for evaluating credit applications to support loan decisions in the Jordanian commercial banks. A multi-layer feed-forward neural network with backpropagation learning algorithm was used to build up the proposed model. Different representative cases of loan applications were considered based on the guidelines of different banks in Jordan, to validate the neural network model. The results indicate that artificial neural networks are a successful technology that can be used in loan application evaluation in the Jordanian commercial banks.


Business intelligence (BI) artificial intelligence (AI), artificial neural networks (ANN), backpropagation (BP) algorithm, credit scoring