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	<id>https://www.insurerbrain.com/w/index.php?action=history&amp;feed=atom&amp;title=Definition%3AOccurrence_exceedance_probability</id>
	<title>Definition:Occurrence exceedance probability - Revision history</title>
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	<updated>2026-07-03T10:20:59Z</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:Occurrence_exceedance_probability&amp;diff=22815&amp;oldid=prev</id>
		<title>PlumBot: Bot: Creating definition</title>
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		<updated>2026-03-31T17:52:33Z</updated>

		<summary type="html">&lt;p&gt;Bot: Creating definition&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;Occurrence exceedance probability&amp;#039;&amp;#039;&amp;#039; (OEP) is a key metric in [[Definition:Catastrophe modeling|catastrophe modeling]] and insurance [[Definition:Risk management|risk management]] that expresses the probability of any single event in a given period causing losses that exceed a specified threshold. If an insurer&amp;#039;s OEP curve shows a 1% probability at $500 million, this means there is a one-in-one-hundred chance that at least one individual catastrophe event in a year will generate losses exceeding $500 million. The OEP is distinct from the [[Definition:Aggregate exceedance probability|aggregate exceedance probability]] (AEP), which measures the likelihood that total cumulative losses from all events in a period will exceed a given level, and understanding this distinction is essential for insurers, [[Definition:Reinsurance|reinsurers]], and [[Definition:Insurance-linked securities|capital markets]] participants who structure and price risk transfer mechanisms.&lt;br /&gt;
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📐 Catastrophe models from vendors such as [[Definition:Moody&amp;#039;s RMS|RMS]], [[Definition:Verisk|AIR Worldwide]], and CoreLogic generate OEP curves by simulating tens of thousands of potential event scenarios — hurricanes, earthquakes, floods, and other perils — and computing the resulting losses to an insurer&amp;#039;s portfolio for each simulated event. The output is a probability distribution that maps return periods to loss levels: a 100-year OEP loss represents the loss level that any single event has a 1% chance of exceeding in a given year, while a 250-year OEP loss corresponds to a 0.4% probability. Insurers and reinsurers use OEP outputs extensively to set [[Definition:Risk appetite|risk appetite]] limits, determine how much [[Definition:Reinsurance|reinsurance]] or [[Definition:Retrocession|retrocession]] to purchase, price [[Definition:Catastrophe bond|catastrophe bonds]] and [[Definition:Industry loss warranty|industry loss warranties]], and allocate [[Definition:Risk-based capital|capital]] against peak peril exposures. The per-occurrence nature of the OEP makes it particularly relevant for structuring [[Definition:Excess of loss reinsurance|excess of loss reinsurance]] treaties, which respond on a per-event basis.&lt;br /&gt;
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🔎 Regulatory and [[Definition:Rating agency|rating agency]] frameworks around the world rely heavily on OEP metrics when assessing an insurer&amp;#039;s catastrophe exposure and capital adequacy. Agencies such as [[Definition:AM Best|AM Best]], [[Definition:S&amp;amp;P Global Ratings|S&amp;amp;P]], and [[Definition:Moody&amp;#039;s|Moody&amp;#039;s]] typically examine OEP results at key return periods as part of their capital model assessments, and regulators in catastrophe-exposed markets — including the United States, Japan, and Caribbean jurisdictions — often require OEP reporting as part of solvency filings. The reliability of OEP estimates depends critically on the quality of the underlying exposure data, the assumptions embedded in the catastrophe model, and the treatment of model uncertainty, which has led to ongoing industry debate about model governance, the use of multiple models, and the appropriate margin for uncertainty. As climate change alters the frequency and severity of natural catastrophes, OEP curves are becoming less stable over time, pushing insurers toward more dynamic approaches to catastrophe risk quantification rather than relying on static historical views.&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:Aggregate exceedance probability]]&lt;br /&gt;
* [[Definition:Catastrophe modeling]]&lt;br /&gt;
* [[Definition:Probable maximum loss]]&lt;br /&gt;
* [[Definition:Excess of loss reinsurance]]&lt;br /&gt;
* [[Definition:Catastrophe bond]]&lt;br /&gt;
* [[Definition:Return period]]&lt;br /&gt;
{{Div col end}}&lt;/div&gt;</summary>
		<author><name>PlumBot</name></author>
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