Credit Rating of Small Business with Trapezoid Fuzzy Linguistic Variables

Abstract

For the credit information of small business is mostly qualitative, trapezoid fuzzy linguistic variables (TFLVs) are brought forward to describe them. The formula of the expected value of TFLVs is defined, and some of its properties are studied. Based on the expected value, an approach to ranking the decision alternatives in multiple attribute decision making(MADM) with TFLVs is developed. A trapezoid fuzzy linguistic weighted averaging operator is utilized to aggregate the decision information, and all alternatives are ranked by comparison the expected value of TFLVs, then the expected value is mapped to credit rating. Finally, an empirical example about credit rating of small business from some commercial bank is illustrated, the results indicate that the method can carry out linguistic computation processes easily without loss of linguistic information, and thus makes the decision result reasonable and effective. This paper builds a new frame and view on credit rating of small business.