Presentation of a scenario-based optimization model for bank loan portfolio under conditions of uncertainty based on robust Mulvey's approach

In order to maintain the balance of cash flow between lenders and borrowers, banks have to use a financially appropriate ecosystem. When such a flow is rebated and or disrupted by non-performing loans (NPLs), life trends of banks and implementation of national economic policies are damaged seriously. Mis management and flexibility in lending and repaying off a loans are considered a drive force of NPLs.The aim of present research is to present a model for the optimization of bank loans portfolio under conditions of uncertainty, which is based on the robust scenario-based approach developed by Mulvey et al. uncertainty criteria set in this study include such economic factors as exchange rates, inflation, and systematic risks. This model has three objective functions: (1) increasing the returns of banks by increasing current loan, (2) decreasing the credit risk, and (3) mitigating the risk of bankruptcy based on Altman Financial Ratios, which are analyzed by using GAMS software. Using this model, bank managers based on the status and strength of each type of loan under normal circumstances and uncertainty can make the right decision to pay a certain amount of each type of loan according to the optimal limit, which reduces the credit risk and bankruptcy of the bank. The results also show that respectively systematic risk, inflation rate and exchange rate have the greatest impact on loan quality reduction.