Presentation a Model for Intelligent Decision Making For The Optimal Bank Loans Provision Based On meta-heuristic Algorithms Whale and Bat

Abstract

Non-performing loans (NPL) strongly affect the health of the banking sector as well as the economies of countries. The provision of loans by banks must be safe and sound so that the bank can be financially strong in times of crisis against credit risks and bankruptcy.Failure to manage credit risk increases the risk of bank bankruptcy. Due to the importance of this issue, the present study designs a multi-objective mathematical model to reduce risks and increase bank returns.Therefore, in order to optimize the loans granted by banks in the face of uncertainty in systematic risk, exchange rate and inflation, the robust model of mathematical linear programming based on Malloy approach presented the model based on financial data from 2013 to 2017 bank using the meta-heuristic algorithms of bat and Whale in MATLAB software have been evaluated.The results show the efficiency of the model and the improvement of the rate of return (current loans) and the reduction in credit risk and bankruptcy.

Keywords

• non-performing loans
• loans optimization
• whale and bat algorithms
• credit risk
• decisions on uncertainty