摘要
建立保险行业的风险监测预警体系是维护国家金融安全、经济稳定发展的重要任务之一。本文针对保险业风险监测数据不平衡的特性,基于随机森林算法,利用重复合成采样技术,构建了保险业风险预警模型新思路。实证结果表明,模型具有一定预测能力,且随着合成采样重复次数的增加,预测效果进一步提升,在应用中具备合理性、有效性和可操作性。基于此,本文提出如下政策建议:协同推进机构与监管数字化转型、持续创新技术手段、扩充数据源以及引入多元化特征变量等。
Establishing the risk monitoring and early warning system of insurance industry is one of the most important tasks to maintain national financial security and stable economic development.Based on random forest algorithm and synthetic data generation,this study proposes a new idea to build an insurance risk early warning model due to the unbalanced risk data.The results show that the model has a certain prediction ability,and the prediction effect is significantly improved with the increase of the number of sampling repetitions(M).On this basis,suggestions are put forward to enhance the awareness of digital transformation,improve and optimize technical means,expand data sources,and introduce diversified characteristic variables.
出处
《金融监管研究》
CSSCI
北大核心
2023年第5期101-114,共14页
Financial Regulation Research
