摘要
比较二战时期德国与英国航空侦察模式,分析人工智能时代下大数据保险精算模型和传统保险精算模型的区别。与传统的保险精算通过概率对风险成本进行测算不同,大数据保险分析依靠获取“全量数据”,对数据集的数据对象多维化以及进行数据关联分析,实现保险风险定价评估的成本与精度的组合优化,即有效匹配保险场景需求,拓展可保风险范围,增加保险体系的有效供给,更好地增进社会福利和效用。
By the comparison on the model aircraft reconnaissance between Germany and Britain air force, the difference of concept is also found in the traditional actuarial evaluation and big data evaluation. Under the limited-data circumstances, the traditional insurance industry evaluates the risk based on the actuarial measurement, while the new method with big data analysis can make scenario, diversified and customized analysis through the multi-dimensional data processing, providing more accurate, flexible and cost-saving resolution. For the foreseeable future, the insurance industry can combine the advantages of the two models, enlarging the scope of insurance, constructing more robust insurance system and facilitating the benefit and utility for the whole society.
作者
赵亮
ZHAO Liang(Graduate School of Chinese Academy of Social Sciences,Beijing 102488,China)
出处
《重庆交通大学学报（社会科学版）》
2019年第4期78-83,共6页
Journal of Chongqing Jiaotong University:Social Sciences Edition
关键词
保险精算
人工智能
大数据分析
actuarial science
artificial intelligence
big data analysis
