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Cyber Risk Assessment for Capital Management

Author

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  • Wing Fung Chong
  • Runhuan Feng
  • Hins Hu
  • Linfeng Zhang

Abstract

Cyber risk is an omnipresent risk in the increasingly digitized world that is known to be difficult to manage. This paper proposes a two-pillar cyber risk management framework to address such difficulty. The first pillar, cyber risk assessment, blends the frequency-severity model in insurance with the cascade model in cybersecurity, to capture the unique feature of cyber risk. The second pillar, cyber capital management, provides informative decision-making on a balanced cyber risk management strategy, which includes cybersecurity investments, insurance coverage, and reserves. This framework is demonstrated by a case study based on a historical cyber incident dataset, which shows that a comprehensive cost-benefit analysis is necessary for a budget-constrained company with competing objectives for cyber risk management. Sensitivity analysis also illustrates that the best strategy depends on various factors, such as the amount of cybersecurity investments and the effectiveness of cybersecurity controls.

Suggested Citation

  • Wing Fung Chong & Runhuan Feng & Hins Hu & Linfeng Zhang, 2022. "Cyber Risk Assessment for Capital Management," Papers 2205.08435, arXiv.org, revised Oct 2023.
  • Handle: RePEc:arx:papers:2205.08435
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    File URL: http://arxiv.org/pdf/2205.08435
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    References listed on IDEAS

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    1. 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.
    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. Li, Ling & He, Wu & Xu, Li & Ash, Ivan & Anwar, Mohd & Yuan, Xiaohong, 2019. "Investigating the impact of cybersecurity policy awareness on employees’ cybersecurity behavior," International Journal of Information Management, Elsevier, vol. 45(C), pages 13-24.
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    Cited by:

    1. Wing Fung Chong & Daniel Linders & Zhiyu Quan & Linfeng Zhang, 2023. "Incident-Specific Cyber Insurance," Papers 2308.00921, arXiv.org.

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