A study on credit strategy for small and medium-sized enterprises based on hierarchical analysis

Micro, small and medium-sized enterprises (MSMEs) are enterprises with relatively small staff size and operation scale, which are important subjects for enhancing employment and scientific and technological innovation in China, as well as an important part of China's real economy, and play an irreplaceable role in promoting economic growth and social prosperity. This paper mainly provides research solutions to solve the credit decision problems of banks for MSMEs through quantitative analysis of credit risks of MSMEs, combined with the realistic basis for banks to pursue profit maximization and risk minimization. This paper selects some enterprise data as the research sample, pre-processes the original data, and then selects six indicators to quantify the risk: input invoice efficiency, output invoice efficiency, credit rating, total invoices, total price and tax, and average profit. Based on this, this paper uses AHP hierarchical analysis to calculate index weights of 0.0664, 0.115, 0.0755, 0.1067, 0.2899, and 0.3465, respectively, to weight the indicators of each enterprise to sum up the enterprise's reputation score. Then we derive the enterprise's compliance rate from the scores and build the optimal credit decision model accordingly. Finally, we use the greedy algorithm to solve for the final strategy.