The County Fair Cyber Loss Distribution: Drawing Inferences from Insurance Prices
The County Fair Cyber Loss Distribution: Drawing Inferences from Insurance Prices
复制标题
县公平网络损失分布：从保险价格中推断
DOI：
10.1145/3434403
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Simpson, Andrew C.
中科院分区：
文献类型：
--
作者：
Woods, Daniel W.;Moore, Tyler;Simpson, Andrew C.
保险费反映了每个被保险人对未来损失的预期。鉴于缺乏网络安全损失数据，市场溢价可以揭示网络损失的真实规模，尽管与损失无关的因素带来了噪音。为此，我们从26家保险公司的监管备案文件中提取了网络保险定价信息。我们提供了经验观察保费如何随保险类型，金额和保单持有人类型和时间而变化。本文提出了一种基于粒子群优化算法和期望值溢价原理的参数化分布预测方法，以减少观测价格预测的误差。然后，我们汇总了来自所有26家保险公司的6，828个观察价格的推断损失模型，以得出县公平网络损失分布。我们证明了它的价值，决策支持，将其应用到一个理论零售公司的年收入为5000万美元。结果表明，预计网络责任损失为42.8万美元，该公司每年面临10万至1000万美元网络责任损失的可能性为2.3%。该方法和由此产生的估计可以帮助组织更好地管理网络风险，无论他们是否购买保险。
Insurance premiums reflect expectations about the future losses of each insured. Given the dearth of cyber security loss data, market premiums could shed light on the true magnitude of cyber losses despite noise from factors unrelated to losses. To that end, we extract cyber insurance pricing information from the regulatory filings of 26 insurers. We provide empirical observations on how premiums vary by coverage type, amount, and policyholder type and over time. A method usingparticle swarm optimisationand the expected value premium principle is introduced to iterate through candidate parameterised distributions with the goal of reducing error in predicting observed prices. We then aggregate the inferred loss models across 6,828 observed prices from all 26 insurers to derive theCounty Fair Cyber Loss Distribution. We demonstrate its value in decision support by applying it to a theoretical retail firm with annual revenue of $50M. The results suggest that the expected cyber liability loss is $428K and that the firm faces a 2.3% chance of experiencing a cyber liability loss between $100K and $10M each year. The method and resulting estimates could help organisations better manage cyber risk, regardless of whether they purchase insurance.