Research Article Open Access

Neuro-Based Artificial Intelligence Model for Loan Decisions

Shorouq Fathi Eletter1, Saad Ghaleb Yaseen1 and Ghaleb Awad Elrefae1
  • 1 Al-Zaytoonah University of Jordan, Jordan

Abstract

Problem statement: Despite the increase in consumer loans defaults and competition in the banking market, most of the Jordanian commercial banks are reluctant to use artificial intelligence software systems for supporting loan decisions. Approach: This study developed 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. Results: Different representative cases of loan applications were considered based on the guidelines of different banks in Jordan, to validate the neural network model. Conclusion: The results indicated that artificial neural networks are a successful technology that can be used in loan application evaluation in the Jordanian commercial banks.

American Journal of Economics and Business Administration
Volume 2 No. 1, 2010, 27-34

DOI: https://doi.org/10.3844/ajebasp.2010.27.34

Submitted On: 3 February 2010 Published On: 31 March 2010

How to Cite: Eletter, S. F., Yaseen, S. G. & Elrefae, G. A. (2010). Neuro-Based Artificial Intelligence Model for Loan Decisions. American Journal of Economics and Business Administration, 2(1), 27-34. https://doi.org/10.3844/ajebasp.2010.27.34

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Keywords

  • Business Intelligence (BI)
  • Artificial Intelligence (AI)
  • Artificial Neural Networks (ANN)
  • Backpropagation (BP) algorithm
  • Credit Scoring (CS)