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Cyber loss model risk translates to premium mispricing and risk sensitivity

Author

Listed:
  • Gareth W. Peters

    (University of California Santa Barbara)

  • Matteo Malavasi

    (Macquarie University)

  • Georgy Sofronov

    (Macquarie University)

  • Pavel V. Shevchenko

    (Macquarie University
    Saint-Petersburg State University)

  • Stefan Trück

    (Macquarie University)

  • Jiwook Jang

    (Macquarie University)

Abstract

In this paper we focus on model risk and risk sensitivity when addressing the insurability of cyber risk. The standard statistical approaches to assessment of insurability and potential mispricing are enhanced in several aspects involving consideration of model risk. Model risk can arise from model uncertainty and parameter uncertainty. We demonstrate how to quantify the effect of model risk in this analysis by incorporating various robust estimators for key model parameters that apply in both marginal and joint cyber risk loss process modelling. Through this analysis we are able to address the question that, to the best of our knowledge, no other study has investigated in the context of cyber risk: is model risk present in cyber risk data, and how does is it translate into premium mispricing? We believe our findings should complement existing studies seeking to explore the insurability of cyber losses.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:gpprii:v:48:y:2023:i:2:d:10.1057_s41288-023-00285-x
    DOI: 10.1057/s41288-023-00285-x
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    References listed on IDEAS

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