网络损失模型风险转化为保费定价错误和风险敏感性。

Gareth W Peters, Matteo Malavasi, Georgy Sofronov, Pavel V Shevchenko, Stefan Trück, Jiwook Jang
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摘要

在本文中,我们在处理网络风险的可保性时,重点关注模型风险和风险敏感性。评估可保性和潜在错误定价的标准统计方法在涉及模型风险考虑的几个方面得到了加强。模型风险可能源于模型的不确定性和参数的不确定性。我们展示了如何在该分析中量化模型风险的影响,方法是结合关键模型参数的各种稳健估计量,这些参数适用于边际和联合网络风险损失过程建模。通过这一分析,我们能够解决一个问题,据我们所知,没有其他研究在网络风险的背景下进行过调查:网络风险数据中是否存在模型风险,它如何转化为保费定价错误?我们认为,我们的发现应该补充现有的研究,以探索网络损失的可保性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Cyber loss model risk translates to premium mispricing and risk sensitivity.

In this paper we focus on model risk and risk sensitivity when addressing the insurability of cyber risk. The standard statistical approaches to assessment of insurability and potential mispricing are enhanced in several aspects involving consideration of model risk. Model risk can arise from model uncertainty and parameter uncertainty. We demonstrate how to quantify the effect of model risk in this analysis by incorporating various robust estimators for key model parameters that apply in both marginal and joint cyber risk loss process modelling. Through this analysis we are able to address the question that, to the best of our knowledge, no other study has investigated in the context of cyber risk: is model risk present in cyber risk data, and how does is it translate into premium mispricing? We believe our findings should complement existing studies seeking to explore the insurability of cyber losses.

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