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A Multicriteria Approach for Modeling Small Enterprise Credit Rating: Evidence from China

机译:小型企业信用评级建模的多准则方法:来自中国的证据

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摘要

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.
机译:作为中国经济的引擎,小企业一直是中国经济发展的中心。但是,鉴于小企业贷款的特点(即借款期短,金额大,金额少和信息不完整),金融机构评估其信誉度是极具挑战性的。因此,它严重延迟并限制了小企业的融资渠道。为了缓解小企业的融资困难,本文利用中国一家区域性商业银行的687家批发和零售小企业,通过偏相关分析和概率分析,建立了由17个指标组成的信用评级指标体系。回归。然后,它利用TOPSIS和模糊C均值对我们的小型企业样本的信用等级进行评分。通过对违约歧视和ROC曲线的双重检验,已建立的指标体系的预测准确性分别达到80.10%和0.917,表明我们的信用评级系统的稳健性和有效性。

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