IDEAS home Printed from https://ideas.repec.org/a/pal/gpprii/v46y2021i1d10.1057_s41288-020-00163-w.html
   My bibliography  Save this article

Addressing insurance of data breach cyber risks in the catastrophe framework

Author

Listed:
  • Spencer Wheatley

    (ETH Zurich)

  • Annette Hofmann

    (St. John’s University)

  • Didier Sornette

    (ETH Zurich)

Abstract

Considering data breaches as a man-made catastrophe helps clarify the actuarial need for multiple levels of analysis—going beyond claims-driven loss statistics alone—and calls for specific advances in both data and models. The prominent human element and the dynamic, networked and multi-type nature of cyber risk are perhaps what makes it uniquely challenging. Complementary top-down statistical and bottom-up analytical approaches are discussed. Focusing on data breach severity, we exploit open data for events at organisations in the U.S. We show that this extremely heavy-tailed risk is worsening for external attacker ‘hack’ events. Writing in Q2 of 2018, the median predicted number of ids breached in the U.S. due to hacking in the last 6 months of 2018 was 0.5 billion, with a 5% chance that the figure exceeds 7 billion, doubling the historical total. ‘Fortunately’, the total breach in that period turned out to be near the median.

Suggested Citation

  • Spencer Wheatley & Annette Hofmann & Didier Sornette, 2021. "Addressing insurance of data breach cyber risks in the catastrophe framework," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 46(1), pages 53-78, January.
    • Handle: RePEc:pal:gpprii:v:46:y:2021:i:1:d:10.1057_s41288-020-00163-w
    DOI: 10.1057/s41288-020-00163-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41288-020-00163-w
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41288-020-00163-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stanley Kaplan & B. John Garrick, 1981. "On The Quantitative Definition of Risk," Risk Analysis, John Wiley & Sons, vol. 1(1), pages 11-27, March.
    2. Eling, Martin & Wirfs, Jan, 2019. "What are the actual costs of cyber risk events?," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1109-1119.
    3. Hulisi Öğüt & Srinivasan Raghunathan & Nirup Menon, 2011. "Cyber Security Risk Management: Public Policy Implications of Correlated Risk, Imperfect Ability to Prove Loss, and Observability of Self‐Protection," Risk Analysis, John Wiley & Sons, vol. 31(3), pages 497-512, March.
    4. Ibragimov, Rustam & Walden, Johan, 2007. "The limits of diversification when losses may be large," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2551-2569, August.
    5. Jean-Philippe Bouchaud & Didier Sornette & Christian Walter & Jean-Pierre Aguilar, 1998. "Taming large events: portfolio selection for strongly fluctuating assets," Science & Finance (CFM) working paper archive 500044, Science & Finance, Capital Fund Management.
    6. Martin Eling & Werner Schnell, 2016. "What do we know about cyber risk and cyber risk insurance?," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 17(5), pages 474-491, November.
    7. Michael Rothschild & Joseph Stiglitz, 1976. "Equilibrium in Competitive Insurance Markets: An Essay on the Economics of Imperfect Information," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 90(4), pages 629-649.
    8. J. P. Bouchaud & D. Sornette & C. Walter & J. P. Aguilar, 1998. "Taming Large Events: Optimal Portfolio Theory for Strongly Fluctuating Assets," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 1(01), pages 25-41.
    9. Rustam Ibragimov & Dwight Jaffee & Johan Walden, 2009. "Nondiversification Traps in Catastrophe Insurance Markets," The Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 959-993, March.
    10. Spencer Wheatley & Thomas Maillart & Didier Sornette, 2016. "The extreme risk of personal data breaches and the erosion of privacy," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(1), pages 1-12, January.
    11. T. Maillart & D. Sornette, 2010. "Heavy-tailed distribution of cyber-risks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 75(3), pages 357-364, June.
    12. Kunreuther, Howard & Heal, Geoffrey, 2003. "Interdependent Security," Journal of Risk and Uncertainty, Springer, vol. 26(2-3), pages 231-249, March-May.
    13. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    14. Tatyana Kovalenko & Didier Sornette, 2016. "Risk and Resilience Management in Social-Economic Systems," Swiss Finance Institute Research Paper Series 16-30, Swiss Finance Institute.
    15. Rustam Ibragimov & Dwight Jaffee & Johan Walden, 2009. "Nondiversification Traps in Catastrophe Insurance Markets," The Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 959-993.
    16. Christian Biener & Martin Eling & Jan Hendrik Wirfs, 2015. "Insurability of Cyber Risk: An Empirical Analysis†," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 40(1), pages 131-158, January.
    17. Ibragimov, Rustam & Walden, Johan, 2007. "The limits of diversification when losses may be large," Scholarly Articles 2624460, Harvard University Department of Economics.
    18. Annette Hofmann & Hidajet Ramaj, 2011. "Interdependent risk networks: the threat of cyber attack," International Journal of Management and Decision Making, Inderscience Enterprises Ltd, vol. 11(5/6), pages 312-323.
    19. Spencer Wheatley & Thomas Maillart & Didier Sornette, 2016. "The extreme risk of personal data breaches and the erosion of privacy," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(1), pages 1-12, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Martin Eling & Kwangmin Jung, 2022. "Heterogeneity in cyber loss severity and its impact on cyber risk measurement," Risk Management, Palgrave Macmillan, vol. 24(4), pages 273-297, December.
    2. Daniel Zängerle & Dirk Schiereck, 2023. "Modelling and predicting enterprise-level cyber risks in the context of sparse data availability," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 48(2), pages 434-462, April.
    3. Zängerle, Daniel & Schiereck, Dirk, 2022. "Modelling and predicting enterprise‑level cyber risks in the context of sparse data availability," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 136276, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Bennet Skarczinski & Mathias Raschke & Frank Teuteberg, 2023. "Modelling maximum cyber incident losses of German organisations: an empirical study and modified extreme value distribution approach," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 48(2), pages 463-501, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martin Eling & Michael McShane & Trung Nguyen, 2021. "Cyber risk management: History and future research directions," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 24(1), pages 93-125, March.
    2. Gareth W. Peters & Matteo Malavasi & Georgy Sofronov & Pavel V. Shevchenko & Stefan Trück & Jiwook Jang, 2023. "Cyber loss model risk translates to premium mispricing and risk sensitivity," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 48(2), pages 372-433, April.
    3. Daniel Zängerle & Dirk Schiereck, 2023. "Modelling and predicting enterprise-level cyber risks in the context of sparse data availability," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 48(2), pages 434-462, April.
    4. Farkas, Sébastien & Lopez, Olivier & Thomas, Maud, 2021. "Cyber claim analysis using Generalized Pareto regression trees with applications to insurance," Insurance: Mathematics and Economics, Elsevier, vol. 98(C), pages 92-105.
    5. Zängerle, Daniel & Schiereck, Dirk, 2022. "Modelling and predicting enterprise‑level cyber risks in the context of sparse data availability," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 136276, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    6. Kjartan Palsson & Steinn Gudmundsson & Sachin Shetty, 2020. "Analysis of the impact of cyber events for cyber insurance," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(4), pages 564-579, October.
    7. Jevtić, Petar & Lanchier, Nicolas, 2020. "Dynamic structural percolation model of loss distribution for cyber risk of small and medium-sized enterprises for tree-based LAN topology," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 209-223.
    8. Kjartan Palsson & Steinn Gudmundsson & Sachin Shetty, 0. "Analysis of the impact of cyber events for cyber insurance," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 0, pages 1-16.
    9. Matteo Malavasi & Gareth W. Peters & Pavel V. Shevchenko & Stefan Truck & Jiwook Jang & Georgy Sofronov, 2021. "Cyber Risk Frequency, Severity and Insurance Viability," Papers 2111.03366, arXiv.org, revised Mar 2022.
    10. Matthias Degen & Dominik D. Lambrigger & Johan Segers, 2009. "Risk Concentration and Diversification: Second-Order Properties," Papers 0910.2367, arXiv.org, revised Dec 2009.
    11. Domenico Giovanni & Arturo Leccadito & Marco Pirra, 2021. "On the determinants of data breaches: A cointegration analysis," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 141-160, June.
    12. Eling, Martin & Wirfs, Jan Hendrik, 2016. "Cyber Risk: Too Big to Insure? Risk Transfer Options for a mercurial risk class," I.VW HSG Schriftenreihe, University of St.Gallen, Institute of Insurance Economics (I.VW-HSG), volume 59, number 59.
    13. Rustam Ibragimov & Johan Walden, 2010. "Optimal Bundling Strategies Under Heavy-Tailed Valuations," Management Science, INFORMS, vol. 56(11), pages 1963-1976, November.
    14. Eling, Martin & Loperfido, Nicola, 2017. "Data breaches: Goodness of fit, pricing, and risk measurement," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 126-136.
    15. Eling, Martin & Jung, Kwangmin, 2018. "Copula approaches for modeling cross-sectional dependence of data breach losses," Insurance: Mathematics and Economics, Elsevier, vol. 82(C), pages 167-180.
    16. Malavasi, Matteo & Peters, Gareth W. & Shevchenko, Pavel V. & Trück, Stefan & Jang, Jiwook & Sofronov, Georgy, 2022. "Cyber risk frequency, severity and insurance viability," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 90-114.
    17. Alessandro Mazzoccoli, 2023. "Optimal Cyber Security Investment in a Mixed Risk Management Framework: Examining the Role of Cyber Insurance and Expenditure Analysis," Risks, MDPI, vol. 11(9), pages 1-14, August.
    18. Radoslav Raykov, 2015. "Catastrophe insurance equilibrium with correlated claims," Theory and Decision, Springer, vol. 78(1), pages 89-115, January.
    19. Alessandro Mazzoccoli & Maurizio Naldi, 2022. "An Overview of Security Breach Probability Models," Risks, MDPI, vol. 10(11), pages 1-29, November.
    20. Markus Huggenberger & Peter Albrecht, 2022. "Risk pooling and solvency regulation: A policyholder's perspective," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(4), pages 907-950, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:gpprii:v:46:y:2021:i:1:d:10.1057_s41288-020-00163-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.