Identification and evolution analysis of important risks in insurance industry based on the textual risk disclosures in financial reports

被引：0
|
作者：
Li B. [1 ]
Wang Y. [2 ,3 ]
Zhu X. [1 ]
Li J. [1 ]
机构：
[1] School of Economics and Management, University of Chinese Academy of Sciences, Beijing
[2] Institutes of Science and Development, Chinese Academy of Sciences, Beijing
[3] School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing
来源：
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | 2022年 / 42卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Financial report; Insurance industry; Risk disclosure; Risk evolution; Text mining;
D O I：
10.12011/SETP2020-2520
中图分类号：
学科分类号：
摘要：
Identifying and effectively supervising the important risks of the insurance industry are of great significance for maintaining the stability of the insurance industry and the entire financial industry. Most studies estimate the level of major risks based on quantitative indicators, but there are some indirectness and hysteresis. Regulators usually require insurance companies to disclose current or future potential risks in their textual financial reports. Comprehensively extracting such risk information can gather the experiences of all insurance companies' managers and identify important risks of insurance industry more directly and proactively. Therefore, the text mining method is adopted to identify the important risks of insurance industry from massive financial reports and analyze their evolutions. Based on 1682 textual risk disclosures of 214 listed insurance companies in the United States in 2006-2018, the empirical study identifies 29 important risk points. By analyzing the evolution trend of each risk point, the importance of risk points related to operational risks has shown a significant upward trend, especially the largest increase in "information system security". It is recommended that insurance companies and regulators should now attach great importance to the operational risk brought by new technologies and new business models. © 2022, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
引用
收藏
页码：333 / 344
页数：11
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