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Heterogeneity in cyber loss severity and its impact on cyber risk measurement

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...

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Autores principales: Eling, Martin, Jung, Kwangmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Palgrave Macmillan UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169022/
http://dx.doi.org/10.1057/s41283-022-00095-w
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author Eling, Martin
Jung, Kwangmin
author_facet Eling, Martin
Jung, Kwangmin
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description 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.
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spelling pubmed-91690222022-06-07 Heterogeneity in cyber loss severity and its impact on cyber risk measurement Eling, Martin Jung, Kwangmin Risk Manag Original Article 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. Palgrave Macmillan UK 2022-06-06 2022 /pmc/articles/PMC9169022/ http://dx.doi.org/10.1057/s41283-022-00095-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Eling, Martin
Jung, Kwangmin
Heterogeneity in cyber loss severity and its impact on cyber risk measurement
title Heterogeneity in cyber loss severity and its impact on cyber risk measurement
title_full Heterogeneity in cyber loss severity and its impact on cyber risk measurement
title_fullStr Heterogeneity in cyber loss severity and its impact on cyber risk measurement
title_full_unstemmed Heterogeneity in cyber loss severity and its impact on cyber risk measurement
title_short Heterogeneity in cyber loss severity and its impact on cyber risk measurement
title_sort heterogeneity in cyber loss severity and its impact on cyber risk measurement
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169022/
http://dx.doi.org/10.1057/s41283-022-00095-w
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