Genetic Algorithm Based Model For Optimizing Bank Lending Decisions

Expert Systems With Applications (2017)

27 Pages Posted: 1 Nov 2018

See all articles by Noura Metawa

Noura Metawa

University of New Orleans - College of Business Administration

M. Kabir Hassan

University of New Orleans - College of Business Administration - Department of Economics and Finance

Mohamed Elhoseny

Mansoura University - Faculty of Computers & Information

Date Written: March 15, 2017

Abstract

To avoid the complexity and time consumption of traditional statistical and mathematical programming, intelligent techniques have gained great attention in different financial research areas, especially in banking decisions’ optimization. However, choosing optimum bank lending decisions that maximize the bank profit in a credit crunch environment is still a big challenge. For that, this paper proposes an intelligent model based on the Genetic Algorithm (GA) to organize bank lending decisions in a highly competitive environment with a credit crunch constraint (GAMCC). GAMCC provides a framework to optimize bank objectives when constructing the loan portfolio, by maximizing the bank profit and minimizing the probability of bank default in a search for a dynamic lending decision. Compared to the state-of-the art methods, GAMCC is considered a better intelligent tool that enables banks to reduce the loan screening time by a range of 12% to 50%. Moreover, it greatly increases the bank profit by a range of 3.9% to 8.1%.

Keywords: Lending Decision, Genetic Algorithm, Loan Portfolio, Bank Objectives

Suggested Citation

Metawa, Noura and Hassan, M. Kabir and Elhoseny, Mohamed, Genetic Algorithm Based Model For Optimizing Bank Lending Decisions (March 15, 2017). Expert Systems With Applications (2017), Available at SSRN: https://ssrn.com/abstract=3263204

Noura Metawa

University of New Orleans - College of Business Administration ( email )

2000 Lakeshore Drive
New Orleans, LA 70148
United States

M. Kabir Hassan (Contact Author)

University of New Orleans - College of Business Administration - Department of Economics and Finance ( email )

2000 Lakeshore Drive
New Orleans, LA 70148
United States

Mohamed Elhoseny

Mansoura University - Faculty of Computers & Information ( email )

Mansoura
Egypt

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