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	<title>Definition:Catastrophe exposure - Revision history</title>
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	<updated>2026-04-29T20:15:38Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
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		<id>https://www.insurerbrain.com/w/index.php?title=Definition:Catastrophe_exposure&amp;diff=8668&amp;oldid=prev</id>
		<title>PlumBot: Bot: Creating new article from JSON</title>
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		<updated>2026-03-11T04:27:54Z</updated>

		<summary type="html">&lt;p&gt;Bot: Creating new article from JSON&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;📍 &amp;#039;&amp;#039;&amp;#039;Catastrophe exposure&amp;#039;&amp;#039;&amp;#039; quantifies the potential for [[Definition:Loss | loss]] that an [[Definition:Insurance carrier | insurer]] or [[Definition:Reinsurer | reinsurer]] faces from [[Definition:Catastrophe (CAT) | catastrophic events]] — hurricanes, earthquakes, wildfires, and similar large-scale perils — across its portfolio of [[Definition:Insurance policy | policies]] or assumed risks. Unlike attritional [[Definition:Exposure | exposure]], which follows relatively predictable patterns, catastrophe exposure is concentrated, correlated, and capable of producing losses that dwarf annual [[Definition:Premium | premium]] income in a single season.&lt;br /&gt;
&lt;br /&gt;
🗺️ Measuring and managing this exposure starts with geocoding insured properties and mapping them against [[Definition:Catastrophe peril | peril]] zones. [[Definition:Catastrophe modeling | Catastrophe models]] from vendors such as [[Definition:Moody&amp;#039;s RMS | RMS]], [[Definition:Verisk | AIR]], and [[Definition:CoreLogic | CoreLogic]] simulate thousands of hypothetical events to estimate the distribution of potential losses across a carrier&amp;#039;s book. Key output metrics — [[Definition:Probable maximum loss (PML) | probable maximum loss (PML)]], [[Definition:Aggregate exceedance probability (AEP) | aggregate exceedance probability]], and [[Definition:Occurrence exceedance probability (OEP) | occurrence exceedance probability]] curves — allow [[Definition:Underwriter | underwriters]] and [[Definition:Risk manager | risk managers]] to see where concentration risk is building. Armed with this data, companies set geographic limits, adjust [[Definition:Rate | pricing]] in high-hazard zones, and purchase [[Definition:Catastrophe reinsurance | catastrophe reinsurance]] or [[Definition:Insurance-linked security (ILS) | insurance-linked securities]] to cap their downside.&lt;br /&gt;
&lt;br /&gt;
⚖️ Regulators and [[Definition:Rating agency | rating agencies]] pay close attention to catastrophe exposure because an insurer with poorly managed concentrations can become insolvent from a single event. [[Definition:Risk-based capital (RBC) | Risk-based capital]] requirements, [[Definition:Stress test | stress tests]], and [[Definition:Own Risk and Solvency Assessment (ORSA) | ORSA]] filings all demand that carriers demonstrate they can absorb extreme catastrophe scenarios and still meet obligations to [[Definition:Policyholder | policyholders]]. As climate patterns shift and urban development pushes into increasingly hazard-prone areas, the imperative to understand and govern catastrophe exposure has never been more urgent.&lt;br /&gt;
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&amp;#039;&amp;#039;&amp;#039;Related concepts:&amp;#039;&amp;#039;&amp;#039;&lt;br /&gt;
{{Div col|colwidth=20em}}&lt;br /&gt;
* [[Definition:Catastrophe modeling]]&lt;br /&gt;
* [[Definition:Probable maximum loss (PML)]]&lt;br /&gt;
* [[Definition:Aggregate exposure]]&lt;br /&gt;
* [[Definition:Catastrophe reinsurance]]&lt;br /&gt;
* [[Definition:Concentration risk]]&lt;br /&gt;
* [[Definition:Risk-based capital (RBC)]]&lt;br /&gt;
{{Div col end}}&lt;/div&gt;</summary>
		<author><name>PlumBot</name></author>
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