中国保险业系统性风险的评估与预警研究——基于Attention-LSTM模型的分析  

Research on Systematic Risk Assessment and Early Warning in China’s Insurance Industry:Analysis Based on Attention-LSTM Model

作　　者：师荣蓉[1] 杨娅 SHI Rongrong;YANG Ya(School of Economics and Management,Northwest University,Xi’an,Shaanxi 710127,China;School of Mathematics,Northwest University,Xi’an,Shaanxi 710127,China)

机构地区：[1]西北大学经济管理学院,陕西西安710127 [2]西北大学数学学院,陕西西安710127

出　　处：《财经理论与实践》2025年第2期26-34,共9页The Theory and Practice of Finance and Economics

基　　金：国家社会科学基金后期资助项目(22FJYB064);陕西省社会科学基金项目(2022D012);陕西省教育厅重点科学研究计划新型智库项目(20JT067)。

摘　　要：基于保险业系统性风险传导机制和预警机制的理论分析,利用CoVaR方法评估保险业系统性风险,从微观保险机构和宏观经济环境构建Attention-LSTM模型对保险业系统性风险进行预警分析。研究发现:当遭遇重大事件冲击时,系统重要性保险机构对保险业的风险溢出增加;将金融压力指数纳入风险预警体系,其预测平均绝对误差、均方根误差和平均绝对百分比误差分别降低8.59%、7.27%和4.55%;Attention-LSTM模型能捕捉风险间的关联性和传染性,在预测准确性、泛化能力和时间稳定性方面均优于传统机器学习模型。鉴于此,应建立保险业风险分区管理体系,融合深度学习模型多维度构建保险业系统性风险预警机制。Based on the theoretical analysis of the systemic risk transmission mechanism and early warning mechanism in the insurance industry,this study uses CoVaR method to evaluate the systemic risk of the insurance industry,and constructs Attention-LSTM model from the micro insurance institution and macroeconomic environment to carry out early warning analysis of the systemic risk in the insurance industry.The results indicate that when the insurance industry is hit by major events,systemically important insurance institutions have an increased risk spillover effect on the insurance industry.By incorporating the financial stress index into the risk warning system,the mean absolute error,root mean square error,and mean absolute percentage error of predictions are respectively reduced by 8.59%,7.27%,and 4.55%.The Attention-LSTM model can capture the correlation and contagion between risks,and it outperforms traditional machine learning models in prediction accuracy,generalization ability,and time stability.In view of this,it is necessary to establish a risk zoning management system for the insurance industry,and integrate deep learning models to build a multidimensional systematic risk early warning mechanism in the insurance industry.

关 键 词：保险业系统性风险 评估 预警 Attention-LSTM模型 

分 类 号：F842[经济管理—保险]