Model of Credit Rating of Micro Enterprise Based on Fuzzy Integration

This paper selects credit data of 1688 micro enterprises in a certain commercial bank in China from 2013 to 2016 as empirical research objects. We use the combination method of t test and correlation analysis to construct credit rating indicator system, then use entropy weight method and fuzzy integration to construct credit evaluation model, and lastly divide credit rating of micro enterprises. The empirical results indicate three main points. Firstly, final constructed indicator system can significantly discriminate credit state and avoid information overlapping, and curve ROC proves credit rating indicator system is effective. Secondly, we use entropy weight method to weight indicators objectively, and evaluate credit state comprehensively based on fuzzy integration model. At last, credit rating of micro enterprises proves that upper rating has minor default enterprises, and overall micro enterprises' credit state is basically on average credit level.