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	<title>Definition:Decrement - Revision history</title>
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	<updated>2026-06-14T16:27:04Z</updated>
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		<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;Decrement&amp;#039;&amp;#039;&amp;#039; is an [[Definition:Actuarial science | actuarial]] term describing any cause that removes an individual from a defined population or exposure group — such as death, disability, lapse, surrender, retirement, or policy expiry. In insurance, decrements form the foundation of [[Definition:Life table | life tables]] and multi-decrement models that actuaries use to project the timing and probability of exits from an insured cohort, which in turn drives [[Definition:Premium | premium]] calculation, [[Definition:Reserve | reserving]], and product design. While a single-decrement model tracks only one cause of exit (commonly mortality), most real-world insurance applications require multiple-decrement analysis to capture competing risks simultaneously.&lt;br /&gt;
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🔢 Multiple-decrement models assign each possible cause of exit its own set of age- or duration-specific probabilities, and these probabilities interact because an individual who exits due to one cause is no longer exposed to the others. For example, a [[Definition:Life insurance | life insurance]] actuary modeling a portfolio of [[Definition:Endowment policy | endowment policies]] must account for mortality, voluntary lapse, surrender, and maturity as separate decrements, each affecting the expected cash flows differently. The associated [[Definition:Decrement table | decrement table]] — whether constructed from company-specific experience data or industry-standard tables published by bodies like the [[Definition:Society of Actuaries (SOA) | Society of Actuaries]] in the U.S. or the [[Definition:Institute and Faculty of Actuaries | Institute and Faculty of Actuaries]] in the UK — translates these probabilities into projected survivor counts at each future duration. Under [[Definition:IFRS 17 | IFRS 17]], the accuracy of decrement assumptions directly affects the measurement of the [[Definition:Contractual service margin (CSM) | contractual service margin]] and the pattern of profit recognition.&lt;br /&gt;
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⚙️ Getting decrement assumptions right is one of the most consequential tasks in insurance pricing and valuation. Underestimating lapse rates on a [[Definition:Universal life insurance | universal life]] block, for instance, can leave an insurer holding unprofitable policies far longer than expected, while overestimating mortality in a [[Definition:Pension | pension]] or [[Definition:Annuity | annuity]] portfolio can lead to severe [[Definition:Longevity risk | longevity risk]] exposure. Regulators across jurisdictions require insurers to demonstrate that their decrement assumptions are supported by credible experience studies and are updated periodically. As data analytics and [[Definition:Predictive modeling | predictive modeling]] capabilities advance, insurers are increasingly able to segment decrement rates by granular risk factors, improving the precision of their projections and strengthening both pricing adequacy and competitive positioning.&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:Life table]]&lt;br /&gt;
* [[Definition:Mortality rate]]&lt;br /&gt;
* [[Definition:Lapse rate]]&lt;br /&gt;
* [[Definition:Actuarial assumption]]&lt;br /&gt;
* [[Definition:Survival model]]&lt;br /&gt;
* [[Definition:IFRS 17]]&lt;br /&gt;
{{Div col end}}&lt;/div&gt;</summary>
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