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📉 '''Vulnerability curve''' is a function used in [[Definition:Catastrophe modeling | catastrophe modeling]] that quantifies the relationship between a given hazard intensity — such as wind speed, flood depth, or ground acceleration — and the expected degree of damage to an insured asset. Sometimes called a damage function or fragility curve, it translates physical hazard parameters into a [[Definition:Mean damage ratio | mean damage ratio]] or probability distribution of loss for a specific structure type or portfolio segment. Vulnerability curves sit at the heart of the damage module within [[Definition:Catastrophe model | catastrophe models]] developed by vendors such as [[Definition:RMS | RMS]], [[Definition:AIR Worldwide | AIR Worldwide]], and [[Definition:CoreLogic | CoreLogic]], and they are essential for [[Definition:Underwriting | underwriting]], [[Definition:Reinsurance | reinsurance]] pricing, and regulatory [[Definition:Capital adequacy | capital adequacy]] assessments worldwide.

⚙️ Construction of a vulnerability curve begins with empirical claims data, engineering analysis, or a combination of both. For a residential property portfolio exposed to [[Definition:Hurricane | hurricane]] risk, for example, the curve might map sustained wind speeds in increments against the percentage of [[Definition:Total insured value (TIV) | total insured value]] expected to be lost. Different curves are calibrated for different construction types — timber-frame dwellings behave very differently from reinforced concrete structures — and for different perils, since flood damage accumulates with depth while wind damage escalates nonlinearly with speed. Once embedded in a catastrophe model, these curves are applied to thousands or millions of simulated events across a [[Definition:Stochastic event set | stochastic event set]], enabling the model to translate each event's physical footprint into an estimated [[Definition:Loss distribution | loss distribution]]. Adjustments for factors such as building age, local [[Definition:Building code | building code]] enforcement, and secondary characteristics like roof shape refine the output further.

🔍 Getting the vulnerability curve right has enormous financial consequences. An over-optimistic curve understates expected losses and can lead an insurer to underprice [[Definition:Property insurance | property]] or [[Definition:Catastrophe bond | catastrophe bond]] risk, eroding [[Definition:Loss reserves | reserves]] when a major event strikes. Conversely, an excessively conservative curve inflates [[Definition:Technical price | technical prices]] and may render an insurer uncompetitive. Regulators in [[Definition:Solvency II | Solvency II]] jurisdictions and under frameworks such as China's [[Definition:C-ROSS | C-ROSS]] increasingly scrutinize model assumptions — including vulnerability functions — when approving [[Definition:Internal model | internal models]] for capital calculation. As climate change shifts the frequency and intensity of [[Definition:Natural catastrophe | natural catastrophe]] events, insurers and modelers must continuously update these curves with fresh post-event data and engineering research to ensure their portfolios remain adequately priced and reserved.

'''Related concepts:'''
{{Div col|colwidth=20em}}
* [[Definition:Catastrophe model]]
* [[Definition:Exposure analysis]]
* [[Definition:Mean damage ratio]]
* [[Definition:Total insured value (TIV)]]
* [[Definition:Loss exceedance curve]]
* [[Definition:Natural catastrophe]]
{{Div col end}}

Definition:Vulnerability curve - Revision history

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