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🔺 '''Severity risk''' refers to the exposure an [[Definition:Insurance carrier | insurer]] or [[Definition:Reinsurer | reinsurer]] faces from the potential magnitude of individual [[Definition:Claim | claims]] or loss events, as distinct from the frequency with which losses occur. In insurance [[Definition:Risk management | risk management]], the frequency–severity split is foundational: frequency risk concerns how often claims arise, while severity risk concerns how large each claim can be. Lines of business such as [[Definition:Property catastrophe insurance | property catastrophe]], [[Definition:Aviation insurance | aviation]], [[Definition:Directors and officers liability insurance (D&O) | directors and officers liability]], and [[Definition:Cyber insurance | cyber insurance]] tend to be severity-driven, meaning that a relatively small number of claims can generate outsized losses that threaten an insurer's financial stability.

📊 Actuaries and underwriters model severity risk using statistical distributions — often heavy-tailed ones such as Pareto or lognormal — to capture the possibility that extreme losses will far exceed the average. [[Definition:Reinsurance | Reinsurance]] structures are frequently designed around severity exposure: [[Definition:Excess of loss reinsurance | excess of loss]] treaties, for instance, attach above a specified retention precisely to transfer the tail of the severity distribution to a reinsurer. [[Definition:Probable maximum loss (PML) | Probable maximum loss]] estimates, [[Definition:Catastrophe model | catastrophe models]], and scenario analyses all attempt to quantify the upper reaches of severity. Under [[Definition:Solvency II | Solvency II]] in Europe and the [[Definition:Risk-based capital (RBC) | risk-based capital]] framework in the United States, regulators require insurers to hold capital commensurate with the severity profiles of their portfolios, and Japan's solvency regime similarly differentiates capital charges based on the tail characteristics of underwritten risks.

⚠️ Failing to adequately account for severity risk has been at the heart of some of the insurance industry's most consequential financial shocks. When an insurer prices a book of business using average claim costs without properly loading for the potential of extreme individual losses, it may appear profitable until a single catastrophic event — a major hurricane, a mass tort judgment, or a systemic cyber attack — reveals the inadequacy of its [[Definition:Reserves | reserves]] and [[Definition:Capital adequacy | capital]]. This is why sophisticated [[Definition:Underwriting | underwriting]] and [[Definition:Pricing model | pricing]] approaches decompose risk into its frequency and severity components separately, allowing each to be measured, priced, and reinsured on its own terms. For [[Definition:Insurtech | insurtech]] platforms leveraging [[Definition:Artificial intelligence (AI) | artificial intelligence]] and large datasets, improving severity estimation — particularly in emerging lines like cyber — remains one of the most consequential analytical challenges in the market.

'''Related concepts:'''
{{Div col|colwidth=20em}}
* [[Definition:Frequency risk]]
* [[Definition:Excess of loss reinsurance]]
* [[Definition:Probable maximum loss (PML)]]
* [[Definition:Catastrophe model]]
* [[Definition:Loss distribution]]
* [[Definition:Tail risk]]
{{Div col end}}

Definition:Severity risk - Revision history

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