1. 西南财经大学经济数学学院,四川 成都 611130
2. 江苏汇誉通数据科技有限公司,江苏 苏州 215123
3. 电子科技大学经济与管理学院,四川 成都 611731
[ "杨扬(1987-),男,博士,西南财经大学经济数学学院讲师、硕士生导师,主要研究方向为信用风险管理、管理信息系统、集团管控、风险投资。" ]
[ "周一懋(1982-),男,江苏汇誉通数据科技有限公司大数据事业部总监、工程师,主要研究方向为数据挖掘、信用评价、项目管理、系统平台设计等。" ]
[ "周宗放(1950-),男,电子科技大学经济与管理学院教授、博士生导师,风险分析与数据科学研究中心主任,中国科学院/汇誉通大数据联合实验室特聘研究员,主要研究方向为信用风险管理、信用评估、优化理论与方法等。" ]
网络首发:2017-01,
纸质出版:2017-01-20
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杨扬, 周一懋, 周宗放. 基于文本大数据的企业信用风险评估[J]. 大数据, 2017,3(1):2017006.
Yang YANG, Yimao ZHOU, Zongfang ZHOU. Credit risk evaluation with text big data from text[J]. Big data research, 2017, 3(1): 2017006.
杨扬, 周一懋, 周宗放. 基于文本大数据的企业信用风险评估[J]. 大数据, 2017,3(1):2017006. DOI: 10.11959/j.issn.2096-0271.2017006.
Yang YANG, Yimao ZHOU, Zongfang ZHOU. Credit risk evaluation with text big data from text[J]. Big data research, 2017, 3(1): 2017006. DOI: 10.11959/j.issn.2096-0271.2017006.
相较于个人信用风险评估,银行关于企业信用风险评估的资料具有更多的文本信息且标准化程度更高,然而文本信息中蕴含的大量关于企业信用风险的增量信息却没有得到有效利用。通过对我国上市公司年报以及网民评论的文本进行分析,探索了文本大数据对企业信用风险评估的作用。研究发现,年报管理层讨论与分析的风险提示内容、独立董事意见中关于关联交易的非正式感情表达以及网民关于公司风险的评论对于企业信用风险评估都具有明显的增量信息。
Banks have more text information pertaining to credit risk of enterprises.This information is more complete and standardized compared with that of individuals.Nevertheless
this incremental information of enterprise credit risk
which is contained in documents has not been effectively utilized by banks.The role of text big data on credit risk evaluation through annual reports and commentaries of crowds on networks was explored.It found that both the annual reports and crowds’ commentaries significantly contain the incremental information on credit risk of enterprises.
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