Green Credit Scoring System and Its Risk Assessemt Model with Support Vector Machine

Qiang Wang, K. Lai, D. Niu
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引用次数: 4

Abstract

Green financial products such as green loans have developed quickly worldwide in the last 5 years. Green credit extended so far is already more than 1 trillion Yuan in China, and huge growth is expected with further development of a low carbon economy. As green loan undertakes social responsibility, such as environmental protection and energy saving, and is one of the key factors in policy decisions, the traditional credit scoring system and risk evaluation model can not be used since here only financial and management factors are considered. In this paper, a green credit scoring system is presented which introduces new environment and energy factors. A SVM risk assessment model is created on this basis. Finally, a real-world dataset is applied to test the green credit scoring system and the SVM risk assessment model. The result shows that the new green credit scoring and SVM risk assessment models are effective.
基于支持向量机的绿色信用评分系统及其风险评估模型
近5年来,绿色贷款等绿色金融产品在全球范围内迅速发展。到目前为止,中国已经发放了超过1万亿元的绿色信贷,随着低碳经济的进一步发展,预计将有巨大的增长。由于绿色贷款承担着环保、节能等社会责任,是决策的关键因素之一,因此传统的信用评分系统和风险评估模型只能考虑财务和管理因素,无法使用。本文提出了一种引入新的环境和能源因素的绿色信用评分系统。在此基础上建立了支持向量机风险评估模型。最后,利用一个真实数据集对绿色信用评分系统和SVM风险评估模型进行了测试。结果表明,新的绿色信用评分模型和支持向量机风险评估模型是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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