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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
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    Cited by:

    1. 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).
    2. 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.
    3. 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.
    4. 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.

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