Credit Risk Evaluation by Improved MCDM Models

In this paper, two improved MCDM models including Analytic Hierarchy Process (AHP) for group decision-making and revised TOPSIS model are applied for credit risk evaluation. The index weight is determined by AHP for group decision-making, which can establish the decision matrix with less subjective judgments and improve the accuracy of index weight. In the revised TOPSIS method, gray relational degree which represents the relative importance between alternative and the "ideal" solution is integrated into TOPSIS to evaluate credit risk. An illustrative case on urban commercial bank credit risk is applied to verify the two improved MCDM models. The calculated results present the lowest credit risk of urban commercial bank is superior to the highest credit risk by 34.54%.