论文标题
索赔历史是否会成为弃用的评级因素？实时道路风险模型的最佳设计方法
Will claim history become a deprecated rating factor? An optimal design method for the real-time road risk model
论文作者
论文摘要
随着远程信息处理和自动驾驶的流行，将越来越多的评分因素（例如里程，路线，驾驶行为等）引入精算模型中。关于选择评级变量的合理性和准确性有很多疑问和争议，但这并不涉及被广泛接受的历史索赔记录。最近，特斯拉保险（Tesla Insurance）发布了新一代基于安全得分的保险，而不论事故历史记录如何。前瞻性的专家和学者开始讨论未来的汽车保险费制造系统中的索赔历史是否会消失。因此，本文提出了一种新的风险变量消除方法以及实时的道路风险模型设计框架，并得出结论认为，索赔历史将被视为“噪音”因素，并在付费驱动器模型中贬低。
With the popularity of Telematics and Self-driving, more and more rating factors, such as mileage, route, driving behavior, etc., are introduced into actuarial models. There are quite a few doubts and disputes on the rationality and accuracy of the selection of rating variables, but it does not involve the widely accepted historical claim records. Recently, Tesla Insurance released a new generation of Safety Score-based insurance, irrespective of accident history. Forward-looking experts and scholars began to discuss whether claim history will disappear in the future auto insurance rate-making system. Therefore, this paper proposes a new risk variable elimination method as well as a real-time road risk model design framework and concludes that claim history will be regarded as a "noise" factor and deprecated in the Pay-How-You-Drive model.
