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	<title>Definition:Severity - Revision history</title>
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	<updated>2026-06-13T19:30:34Z</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:Severity&amp;diff=7122&amp;oldid=prev</id>
		<title>PlumBot: Bot: Creating new article from JSON</title>
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		<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;Severity&amp;#039;&amp;#039;&amp;#039; refers to the magnitude of a single [[Definition:Loss | loss]] or [[Definition:Claim | claim]] in insurance, measuring how costly an individual event turns out to be rather than how often events occur. While [[Definition:Frequency | frequency]] tracks how many claims arise within a given period, severity captures the dollar amount per claim — a distinction that sits at the heart of [[Definition:Actuarial science | actuarial analysis]] and [[Definition:Underwriting | underwriting]] strategy. A book of business with low frequency but high severity, such as [[Definition:Catastrophe insurance | catastrophe]] or [[Definition:Directors and officers liability insurance (D&amp;amp;O) | directors and officers]] coverage, demands very different [[Definition:Reserving | reserving]] and [[Definition:Pricing | pricing]] approaches than a high-frequency, low-severity portfolio like standard [[Definition:Auto insurance | auto insurance]].&lt;br /&gt;
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⚙️ Insurers and [[Definition:Reinsurer | reinsurers]] analyze severity by examining historical [[Definition:Claims data | claims data]], segmenting losses by line of business, geography, and peril type. [[Definition:Actuary | Actuaries]] fit statistical distributions — such as lognormal or Pareto curves — to past loss amounts, then project future severity trends after adjusting for [[Definition:Inflation | inflation]], legal environment changes, and shifts in [[Definition:Exposure | exposure]]. These severity models feed directly into [[Definition:Loss ratio (L/R) | loss ratio]] projections, [[Definition:Experience rating | experience rating]] calculations, and the structuring of [[Definition:Excess of loss reinsurance | excess-of-loss reinsurance]] layers, where attachment points are explicitly set based on expected severity thresholds.&lt;br /&gt;
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💡 Understanding severity trends can make or break an insurer&amp;#039;s profitability. Rising claim severity — driven by factors like [[Definition:Social inflation | social inflation]], increasing medical costs, or more expensive property replacements — can erode margins even when claim counts hold steady. For [[Definition:Reinsurance | reinsurance]] buyers, severity analysis determines how much protection to purchase and where to place layer boundaries. Ignoring a creeping upward shift in severity is one of the most common reasons [[Definition:Underwriting cycle | underwriting cycles]] turn unprofitable, making this metric a critical watchpoint for [[Definition:Chief underwriting officer (CUO) | chief underwriting officers]] and [[Definition:Portfolio management | portfolio managers]] alike.&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:Frequency]]&lt;br /&gt;
* [[Definition:Loss ratio (L/R)]]&lt;br /&gt;
* [[Definition:Actuarial science]]&lt;br /&gt;
* [[Definition:Excess of loss reinsurance]]&lt;br /&gt;
* [[Definition:Social inflation]]&lt;br /&gt;
* [[Definition:Reserving]]&lt;br /&gt;
{{Div col end}}&lt;/div&gt;</summary>
		<author><name>PlumBot</name></author>
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