The barriers to sustainable risk transfer in the cyber-insurance market

Henry R K Skeoch*, Christos Ioannidis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Efficient risk transfer is an important condition for ensuring the sustainability of a market according to the established economics literature. In an inefficient market, significant financial imbalances may develop and potentially jeopardize the solvency of some market participants. The constantly evolving nature of cyber-threats and lack of public data sharing mean that the economic conditions required for quoted cyber-insurance premiums to be considered efficient are highly unlikely to be met. This paper develops Monte Carlo simulations of an artificial cyber-insurance market and compares the efficient and inefficient outcomes based on the informational setup between the market participants. The existence of diverse loss distributions is justified by the dynamic nature of cyber-threats and the absence of any reliable and centralized incident reporting. It is shown that the limited involvement of reinsurers when loss expectations are not shared leads to increased premiums and lower overall capacity. This suggests that the sustainability of the cyber-insurance market requires both better data sharing and external sources of risk tolerant capital.
Original languageEnglish
Article numbertyae003
JournalJournal of Cybersecurity
Volume10
Issue number1
DOIs
Publication statusPublished - 20 Feb 2024

Bibliographical note

© The Author(s) 2024. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Keywords

  • reinsurance
  • cyber-threats
  • insurance economics
  • security economics
  • efficient risk transfer
  • cyber-insurance
  • Monte Carlo simulations

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