The Evolving Landscape of Cyber Risk Coverage in P&C Policies
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V3I1P113Keywords:
Cyber insurance, P&C, Silent cyber, Ransomware, Business interruption (BI), Contingent BI (CBI), MFA, Reinsurance, incident responseAbstract
The cyber risk has ceased to be a niche, standalone risk, but has become an omnipresent risk exposure cut across Property and Casualty (P&C) lines. Carriers are remediating silent cyber faster by making it clear with explicit non-cyber exclusions or affirmative endorsement with specified triggers (security failure, system outage, data corruption), sublimits, and security warranties (MFA, EDR/XDR, immutable backups). Higher retentions, coinsurance, and stricter business interruption (BI/CBI) terms were pushed by market hardening based on the severity of ransomware, the concentration of cloud/service-providers, and events in the software supply-chain. Underwriting is now becoming data-driven, in terms of external scanning, control questionnaires and mapping vendor-dependency, with Bayesian/heavy-tail modeling, and threat-led scenarios, in order to deal with accumulation and tail correlation. Breach counsel and forensics and PR and restoration vendors are becoming more common in claims operations to contain cycle time and loss adjustment cost, and reinsurance structures (quota share, aggregate/XOL) more compatible with a more event-driven and hostile-cyber vocabulary to insure capital against systemic shocks. Regulatory pressure (e.g. privacy regimes, disclosure requirements) and contractual pressure keep increasing demand especially in SMEs and mid-market firms as product design changes to be modular coverage, defined outage parametric and prevention plus transfer provisions. The ensuing topography is that of more articulate terminologies, price-related controls, and investment-sensitive portfolio management, which puts the P&C insurers in a stronger position to maintain capacity and provide insightful resilience to the threat environment, which is adversarial and rapidly evolving
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References
[1] Camillo, M. (2017). Cyber risk and the changing role of insurance. Journal of Cyber Policy, 2(1), 53-63.
[2] Pooser, D. M., Browne, M. J., & Arkhangelska, O. (2018). Growth in the perception of cyber risk: evidence from US P&C insurers. The Geneva Papers on Risk and Insurance-Issues and Practice, 43(2), 208-223.
[3] Reetz, M. A., Prunty, L. B., Mantych, G. S., & Hommel, D. J. (2017). Cyber risks: Evolving threats, emerging coverages, and ensuing case law. Penn St. L. Rev., 122, 727.
[4] Karri, N. (2021). Self-Driving Databases. International Journal of Emerging Trends in Computer Science and Information Technology, 2(1), 74-83. https://doi.org/10.63282/3050-9246.IJETCSIT-V2I1P10
[5] Rahul, N. (2021). Strengthening Fraud Prevention with AI in P&C Insurance: Enhancing Cyber Resilience. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 2(1), 43-53.
[6] Brawley, A., Kwok, D., Lesarge, J., & Nickerson, E. (2021). Promoting Competition in P&C Insurance.
[7] Eling, M. (2018). Cyber risk and cyber risk insurance: Status quo and future research. The Geneva papers on risk and insurance-issues and practice, 43(2), 175-179.
[8] Insurance-Associated Emissions, carbonaccountingfinancials, pp. 1-82, online. https://carbonaccountingfinancials.com/files/downloads/pcaf-standard-part-c-insurance-associated-emissions-nov-2022.pdf
[9] Kurmaiev, P., Seliverstova, L., Bondarenko, O., & Husarevych, N. (2020). Cyber insurance: the current situation and prospects of development. Amazonia Investiga, 9(28), 65-73.
[10] Karri, N., & Jangam, S. K. (2021). Security and Compliance Monitoring. International Journal of Emerging Trends in Computer Science and Information Technology, 2(2), 73-82. https://doi.org/10.63282/3050-9246.IJETCSIT-V2I2P109
[11] Hatzivasilis, G., Chatziadam, P., Petroulakis, N., Ioannidis, S., Mangini, M., Kloukinas, C., ... & Panayiotou, M. (2019, September). Cyber insurance of information systems: Security and privacy cyber insurance contracts for ICT and helathcare organizations. In 2019 IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD) (pp. 1-6). IEEE.
[12] Black, R., Tsanakas, A., Smith, A. D., Beck, M. B., Maclugash, I. D., Grewal, J., ... & Lim, Z. (2018). Model risk: illuminating the black box. British Actuarial Journal, 23, e2.
[13] Peters, G., Shevchenko, P. V., & Cohen, R. D. (2018). Understanding cyber-risk and cyber-insurance. Macquarie University Faculty of Business & Economics Research Paper.
[14] Spotlight on US Property and Casualty, bcg, online. https://www.bcg.com/publications/2022/value-creators-usa-propery-casualty-insurers
[15] Egan, R., Cartagena, S., Mohamed, R., Gosrani, V., Grewal, J., Acharyya, M., ... & Ang, K. (2019). Cyber operational risk scenarios for insurance companies. British Actuarial Journal, 24, e6.
[16] Karri, N., Pedda Muntala, P. S. R., & Jangam, S. K. (2025). Predictive Performance Tuning. International Journal of Emerging Research in Engineering and Technology, 2(1), 67-76. https://doi.org/10.63282/3050-922X.IJERET-V2I1P108
[17] Pandey, S., Singh, R. K., Gunasekaran, A., & Kaushik, A. (2020). Cyber security risks in globalized supply chains: conceptual framework. Journal of Global Operations and Strategic Sourcing, 13(1), 103-128.
[18] Trufin, J., Albrecher, H., & Denuit, M. (2009). Impact of underwriting cycles on the solvency of an insurance company. North American Actuarial Journal, 13(3), 385-403.
[19] Eling, M. (2020). Cyber risk research in business and actuarial science. European Actuarial Journal, 10(2), 303-333.
[20] Paunović, M. (2019). Cyber risk management and actuarial analysis.
[21] He, Y. (2016). Cyber Risk Insurance Pricing Based on Optimized Insured Strategy. Master of Mathematics In Computational Mathematics, University of Waterloo, (s 48).
[22] Gable, J. (2005). Navigating the compliance landscape. Information Management, 39(4), 28.
[23] Boyd, C. L., Hoffman, D. A., Obradovic, Z., & Ristovski, K. (2013). Building a taxonomy of litigation: Clusters of causes of action in federal complaints. Journal of Empirical Legal Studies, 10(2), 253-287.
[24] Karri, N. (2021). AI-Powered Query Optimization. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 2(1), 63-71. https://doi.org/10.63282/3050-9262.IJAIDSML-V2I1P108
[25] Xie, X., Lee, C., & Eling, M. (2020). Cyber insurance offering and performance: an analysis of the US cyber insurance market. The Geneva Papers on Risk and Insurance-Issues and Practice, 45(4), 690-736.
