Expert Systems in Banking: Artificial Intelligence Application in Supporting Banking Decision-Making

Authors

  • Ahmad Abdullah Mohammed AL-Mafrji ENET’COM Universite de Sfax, Tunisia
  • Ahmed M. Fakhrudeen Software Department, College of Computer Science and Information Technology, Kirkuk University, Kirkuk, Iraq
  • Lotfi Chaari Toulouse INP, IRIT, Toulouse, France

Keywords:

Decision-making, expert system, qualitative variables, guarantee variables

Abstract

This paper aims to evaluate the role of artificial intelligence in the bank lending process. A field study is conducted at the level of several banks. The article focuses on loan files of a commercial and productive nature. To achieve our goal, we utilized multiple expert systems: Sub expert system 1, Sub expert system 2 and the main expert system. Accordingly, the linguistic variables of the proposed expert systems were subsumed into qualitative variables and confirmation variables. To access the decision-making process for granting or denying the loan, the outputs of these variables of sub-expert systems 1 and 2 are fed as inputs to the main expert system. To achieve banking business success factors (quality and time), the expert systems improve the quality of banking service provided. It is performed by reducing the number and size of financial and non-financial errors and their ability to detect error cases. Additionally, unlike the human element, expert systems are characterized by their speed in executing the orders required of them in a few moments, which reduces the time required for decision-making.

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Published

13.02.2023

How to Cite

Mohammed AL-Mafrji, A. A. ., Fakhrudeen, A. M. ., & Chaari, L. . (2023). Expert Systems in Banking: Artificial Intelligence Application in Supporting Banking Decision-Making. International Journal of Intelligent Systems and Applications in Engineering, 11(4s), 61–69. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2572

Issue

Vol. 11 No. 4s (2023)

Section

Research Article

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