A Multicriteria Approach for Modeling Small Enterprise Credit Rating: Evidence from China. Issue 11 (2nd September 2019)

• Record Type: Journal Article
• Authors: Chai, Nana; Wu, Bi; Yang, Weiwei; Shi, Baofeng
• Is Part Of: Emerging markets finance & trade. Volume 55:Issue 11(2019)
• Page Start: 2523
• Page End: 2543
• Publication Date: 2019-09-02
• Subjects: Credit rating -- default risk -- fuzzy C-means -- small wholesale and retail enterprises; JEL -- G32 -- D81 -- C61; Balkan Peninsula -- Commerce -- Periodicals; Balkan Peninsula -- Foreign economic relations -- Periodicals; Europe, Central -- Commerce -- Periodicals; Europe, Central -- Foreign economic relations -- Periodicals; Europe, Eastern -- Commerce -- Periodicals; Europe, Eastern -- Foreign economic relations -- Periodicals; Turkey -- Commerce -- Periodicals; Turkey -- Foreign economic relations -- Periodicals; Asia -- Commerce -- Periodicals; Asia -- Foreign economic relations -- Periodicals; Eurasia -- Commerce -- Periodicals; Eurasia -- Foreign economic relations -- Periodicals; 382.05
• DOI: 10.1080/1540496X.2019.1577237
• Languages: English
• ISSNs: 1540-496X

Abstract

ABSTRACT: As the engine of China's economy, small enterprises have been the central to the country's economic development. However, given the characteristics of the small enterprises loan (i.e., short borrowing period, large volume, small amount and incomplete information), it is extremely challenging for financial institutions to assess their creditworthiness. Thus, it seriously delays and restricts the financing access for small enterprises. In an attempt to relieve the financing difficulty of small enterprises, this article makes use of 687 small wholesale and retail enterprises in a regional commercial bank in China, to establish a credit rating indicator system composed of 17 indicators by using both partial correlation analysis and probit regression. It then utilizes TOPSIS together with fuzzy C-means to score the credit ratings of our sample of small enterprises. With the dual test of default discrimination and ROC curve, the prediction accuracy of the established indicator system has reached 80.10% and 0.917, respectively, indicating the robustness and validity of our credit rating system.