A Credit Rating Model for Enterprises Based on Principal Component Analysis and Optimal Partition

摘要

A new credit rating model for enterprises based on principal component analysis and optimal partition is presented in this paper. Using the principal component analysis, the comprehensive credit score of each sample is obtained. After sorting the comprehensive credit score descending, the ordered samples series is generated. A clustering analysis of the ordered samples is carried out with the optimal partition method, so the clustering results are obtained definitely. And then, the comprehensive credit score of each optimal partition point is regarded as the threshold to divide the credit grades. Finally, the credit rating for enterprises is achieved. Through a specific example, it is proved that the model proposed by this paper is feasible and effective.