Solving the Bank Credit Decision Problem via Revised Group Multi-Role Assignment

The Bank Credit Decision-Making Problem (BCDMP) is one of the main issues that bank operations need to face. To obtain the maximum profit value and optimal loan plan of the bank as much as possible, this article suggests converting BCDMP into a Many-to-Many Assignment Problem, which can be specified by the Multi-Role Assignment (GMRA). GMRA is a sub-model of the E-CARGO. By revised GMRA, the relationship between the enterprises and loans is converted into the relationship between agents and roles, and a multi-dimensional and multi-index evaluation method is used to evaluate the matching degrees between enterprises and loans. We use the Entropy Weight Method (EWM) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to obtain the enterprises' score for a loan through four indicators: profits, inventory, turnover ability, and credit. Then, we considered the impact of different loan interest rates on bank profits, obtained enterprise scores under different loan interest rates, and used linear programming to solve the problem, achieving good results (The bank achieved a profit margin of 5.43176% via revised GMRA).