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🖥️ '''Catastrophe model''' is a computational framework used by [[Definition:Insurance carrier | insurers]], [[Definition:Reinsurance | reinsurers]], and [[Definition:Insurance-linked securities (ILS) | capital market investors]] to estimate the probability and financial impact of large-scale natural or man-made disasters on insured portfolios. Often referred to simply as a "cat model," it integrates scientific data — seismology, meteorology, hydrology — with engineering vulnerability assessments and detailed exposure information to produce probabilistic distributions of potential [[Definition:Catastrophe loss | catastrophe losses]].

🔬 A typical catastrophe model operates through four sequential modules. The hazard module generates thousands of simulated events (for example, hypothetical hurricanes of varying intensity and track), the exposure module maps insured properties and their characteristics against those events, the vulnerability module estimates physical damage based on building construction and local conditions, and the financial module applies [[Definition:Policy | policy]] terms — [[Definition:Deductible | deductibles]], [[Definition:Policy limit | limits]], [[Definition:Reinsurance | reinsurance]] structures — to translate physical damage into insured losses. Vendors such as Moody's RMS, Verisk, and CoreLogic dominate the market, though a growing number of [[Definition:Insurtech | insurtech]] firms are developing open-source or AI-augmented alternatives that challenge legacy approaches.

📈 Reliable catastrophe modeling underpins nearly every major decision in [[Definition:Catastrophe risk | catastrophe risk]] management — from [[Definition:Underwriting | underwriting]] individual accounts and setting [[Definition:Premium | premium]] rates to structuring [[Definition:Reinsurance program | reinsurance programs]] and pricing [[Definition:Catastrophe bond | catastrophe bonds]]. Regulators in [[Definition:Catastrophe-exposed market | catastrophe-exposed markets]] increasingly require carriers to demonstrate model-based capital adequacy, and rating agencies factor modeled loss estimates into their assessments of insurer financial strength. Because model outputs are only as good as their inputs and assumptions, the industry devotes significant resources to model validation, sensitivity testing, and blending results from multiple vendors to avoid over-reliance on any single view of risk.

'''Related concepts'''
{{Div col|colwidth=20em}}
* [[Definition:Catastrophe loss]]
* [[Definition:Catastrophe risk]]
* [[Definition:Exposure management]]
* [[Definition:Probable maximum loss (PML)]]
* [[Definition:Aggregate exceedance probability (AEP)]]
* [[Definition:Insurance-linked securities (ILS)]]
{{Div col end}}

Definition:Catastrophe model - Revision history

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