Heterogeneity in cyber loss severity and its impact on cyber risk measurement
SSCI
SCOPUS
- Title
- Heterogeneity in cyber loss severity and its impact on cyber risk measurement
- Authors
- JUNG, KWANGMIN; ELING, MARTIN
- Date Issued
- 2022-01
- Publisher
- Palgrave Macmillan Ltd.
- Abstract
- We use the world’s largest publicly available dataset of operational risk to model cyber losses and show that the Tweedie model best fits the cyber loss severity in the financial industry. Three key determinants of loss severity are firm size, contagion risk and legal liability. We also measure the size of risk based on the estimation results and show a large degree of heterogeneity across financial firms. The results are particularly relevant with respect to the recent discussion on simplifying operational risk capital requirements and reiterate the importance of considering individual firm characteristics when modelling operational losses.
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/112903
- DOI
- 10.1057/s41283-022-00095-w
- ISSN
- 1460-3799
- Article Type
- Article
- Citation
- Risk Management, 2022-01
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- There are no files associated with this item.
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