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原始链接: https://news.ycombinator.com/item?id=43821578
Hacker News上的一篇文章讨论了一篇博客文章,该文章声称发现了碰撞数据中的保险欺诈。评论者们主要批评这篇文章的方法论和结论,认为该分析缺乏足够的严谨性来支持其大胆的断言。担忧包括未能考虑已识别特征之间的相关性(例如,多次单车事故可能源于同一个驾驶员),忽略了大数定律,以及没有提供诸如碰撞后更换保险等可疑行为的基准比率。一些用户质疑该博客文章戏剧化的语气,强调其反复声明并非因果证明,同时又将调查结果呈现为欺诈的确凿证据。讨论还强调了行车记录仪的潜在益处,并深入探讨了安装的挑战以及欺诈影响所有人保险的更广泛问题。一位评论者指出,文章不合理地排除了与毒品/酒精相关的碰撞事故,并引用了联邦调查局关于涉及醉酒驾驶员的虚构事故的报告。
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Firstly, there's no account for correlation between the features identified. The article mentions VINs which have several single-vehicle accidents, for example, but someone who has one single-vehicle accident is probably more likely to have another. Switching coverage is another of those potentially-correlated features; if you claim and it bumps your premium, aren't you likely to shop around as a result?
Secondly, there's no attempt to account for the law of large numbers. It's incredibly unlikely that someone has three single vehicle accidents in a year, but because the probability of that is nonzero, we know that with enough vehicles on the road then someone is going to do it.
The article covers itself by acknowledging this, of course, but if you title your blog post "We Found Insurance Fraud in Our Crash Data" then you should actually do that.
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