Time dynamics of cyber risk
| Item Type | Conference or Workshop Item (Speech) |
| Abstract | This is the first paper to analyze the three main cyber loss datasets (Advisen, SAS OpRisk and PRC), yielding the most comprehensive cyber loss data yet considered in the literature. We first study the problem of report delay bias by applying a two-stage model and document a faster rate of increase for cyber risk frequency compared with the original data. Based on these results, we then focus on the time dynamics of cyber risk frequency and severity, where we separately study the properties of full distribution and tail of loss severity. We find the loss distribution of cyber events shifts leftwards for both monetary loss and non-monetary loss (such as accounts/records breached) in the recent period, but the trend of tail risk is different for these two types of loss. Based on our new multiple change point detection method, we show the tail risk of non-monetary loss is increasing, while the other is not, although they both consistently exhibit heavy-tailedness over time. Our results are important for cyber risk management and understanding the insurability of cyber risk. |
| Authors | Eling, Martin; Ibragimov, Rustam & Ning, Dingchen |
| Language | English |
| Subjects | business studies statistics |
| HSG Classification | contribution to scientific community |
| Date | 30 September 2022 |
| Event Title | 29th Annual Meeting of the German Finance Association |
| Event Location | Marburg, Germany |
| Event Dates | 29.09.2022-01.10.2022 |
| Depositing User | M.A. Dingchen Ning |
| Date Deposited | 03 Oct 2022 10:01 |
| Last Modified | 27 Mar 2023 00:27 |
| URI: | https://www.alexandria.unisg.ch/publications/267506 |
DownloadFull text not available from this repository.CitationEling, Martin; Ibragimov, Rustam & Ning, Dingchen: Time dynamics of cyber risk. [Conference or Workshop Item] Statisticshttps://www.alexandria.unisg.ch/id/eprint/267506
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