加权
信用评级
业务
信用风险
实证研究
线性判别分析
鉴定(生物学)
信用评分
违约概率
精算学
财务
计算机科学
人工智能
统计
医学
植物
数学
生物
放射科
作者
Bin Meng,Haibo Kuang,Liang Lv,Lidong Fan,Hongyu Chen
标识
DOI:10.1080/1540496x.2021.1984226
摘要
This article establishes a novel credit rating model for small enterprises, thereby solving the problem that commercial banks cannot accurately obtain financial information about small enterprises or reasonably evaluate the credit risk of small enterprise loans. Through the identification of default status and removal of redundant information for indicator screening, this article adopts a weighting method that can be used to classify small enterprises. The empirical results show that the discriminant precision of default status by the credit rating system of China’s small enterprises, constructed by this article, is up to 91.9%. The weighting results show that in the credit rating of small enterprises, financial indicators cannot reflect all the liabilities, and the role of qualitative indicators in credit ratings is more important. This article empowers 30 indicators based on the principle of distinguishing different types of customers, classifies customers into nine different levels, and avoids the unreasonable phenomenon that default customers have higher credit scores than non-default customers. The results can help commercial banks to distinguish customers of different significance levels.
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