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🧊 '''CyberCube''' is a [[Definition:Cyber risk modeling | cyber risk analytics]] company that provides data-driven tools to help [[Definition:Insurance carrier | insurers]], [[Definition:Reinsurance | reinsurers]], and [[Definition:Insurance broker | brokers]] quantify and manage [[Definition:Cyber risk | cyber risk]] exposure. Spun out of Symantec in 2018 and backed by significant investment from the insurance sector — including from [[Definition:Insurance-linked securities (ILS) | ILS]]-focused investors and strategic partners — CyberCube occupies a distinctive position at the intersection of cybersecurity intelligence and insurance analytics. Its platform is designed specifically for the insurance industry's needs, distinguishing it from general-purpose cybersecurity scoring services.

📊 The company's product suite spans several core functions. Its single-risk underwriting tool allows [[Definition:Cyber underwriter | cyber underwriters]] to assess the security posture and risk profile of individual accounts, drawing on outside-in scans of an organization's digital footprint combined with proprietary threat intelligence. At the portfolio level, CyberCube offers [[Definition:Catastrophe modeling | catastrophe modeling]] capabilities that simulate [[Definition:Aggregation risk | aggregation]] scenarios — such as a widespread cloud-provider outage or a global [[Definition:Ransomware | ransomware]] campaign — and estimate potential losses across a carrier's or reinsurer's entire book. These models feed into [[Definition:Capital management | capital management]] and [[Definition:Reinsurance | reinsurance purchasing]] decisions, giving risk managers quantitative inputs where actuarial data has historically been sparse. The models are used across major markets including London, Bermuda, the U.S., and increasingly in Continental European and Asian portfolios.

🌐 CyberCube's influence reflects a broader trend in the [[Definition:Insurtech | insurtech]] landscape: the emergence of specialized analytics vendors whose models shape underwriting appetite and pricing across the market. Because [[Definition:Cyber insurance | cyber insurance]] lacks the decades of [[Definition:Loss history | loss history]] available in mature lines like property or auto, the industry leans heavily on forward-looking, scenario-based modeling — and the vendors who provide it exert considerable influence over market dynamics. CyberCube's models have been adopted by a significant share of the global cyber insurance market, making its assumptions and methodologies a de facto benchmark. This concentration also invites scrutiny: regulators and market participants have raised questions about model dependency and the need for diverse analytical perspectives to avoid correlated decision-making across the industry.

'''Related concepts:'''
{{Div col|colwidth=20em}}
* [[Definition:Cyber risk modeling]]
* [[Definition:Catastrophe modeling]]
* [[Definition:Cyber insurance]]
* [[Definition:Aggregation risk]]
* [[Definition:Insurtech]]
* [[Definition:Cyber underwriter]]
{{Div col end}}

Definition:CyberCube - Revision history

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