In order to more effectively solve the bank personal credit rating problem with big data features, we design a bank personal credit rating scheme which can be regarded as a multi-criteria decision-making problem in a finite fuzzy covering approximation space. Moreover, we propose the TOPSIS-WAA method based on a covering-based fuzzy rough set to deal with this multi-criteriad ecision-making problem with big data features. Subsequently, we use the relevant data of some clients of ICBC to illustrate the feasibility of our method (or scheme). Furthermore, we compare three different decision-making methods with our method to demonstrate the superiority of our method. Finally, the performance of our method is verified from the perspectives of the best alternative and the optimal ranking.
