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The Data that Drives Cyber Insurance: A Study into the Underwriting and Claims Processes

Nurse, Jason R. C., Axon, Louise, Erola, Arnau, Agrafiotis, Ioannis, Goldsmith, Michael, Creese, Sadie (2020) The Data that Drives Cyber Insurance: A Study into the Underwriting and Claims Processes. In: 2020 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA). . IEEE (doi:10.1109/CyberSA49311.2020.9139703) (KAR id:80965)


Cyber insurance is a key component in risk management, intended to transfer risks and support business recovery in the event of a cyber incident. As cyber insurance is still a new concept in practice and research, there are many unanswered questions regarding the data and economic models that drive it, the coverage options and pricing of premiums, and its more procedural policy-related aspects. This paper aims to address some of these questions by focusing on the key types of data which are used by cyber-insurance practitioners, particularly for decision-making in the insurance underwriting and claim processes. We further explore practitioners' perceptions of the challenges they face in gathering and using data, and identify gaps where further data is required. We draw our conclusions from a qualitative study by conducting a focus group with a range of cyber-insurance professionals (including underwriters, actuaries, claims specialists, breach responders, and cyber operations specialists) and provide valuable contributions to existing knowledge. These insights include examples of key data types which contribute to the calculation of premiums and decisions on claims, the identification of challenges and gaps at various stages of data gathering, and initial perspectives on the development of a pre-competitive dataset for the cyber insurance industry. We believe an improved understanding of data gathering and usage in cyber insurance, and of the current challenges faced, can be invaluable for informing future research and practice.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/CyberSA49311.2020.9139703
Subjects: H Social Sciences
H Social Sciences > HF Commerce
Q Science > QA Mathematics (inc Computing science)
T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Divisions > Kent Business School - Division > Kent Business School (do not use)
Depositing User: Jason Nurse
Date Deposited: 22 Apr 2020 20:45 UTC
Last Modified: 04 Mar 2024 19:23 UTC
Resource URI: (The current URI for this page, for reference purposes)

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