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	<title>Definition:Actuarial software - Revision history</title>
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	<updated>2026-04-30T17:23:18Z</updated>
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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;Actuarial software&amp;#039;&amp;#039;&amp;#039; refers to the specialized technology platforms and tools that [[Definition:Actuary | actuaries]] within the [[Definition:Insurance carrier | insurance industry]] use to model [[Definition:Risk | risks]], calculate [[Definition:Reserve | reserves]], price [[Definition:Insurance product | products]], project [[Definition:Cash flow | cash flows]], and ensure regulatory compliance. Unlike generic analytics or spreadsheet applications, these systems are purpose-built to handle the statistical, financial, and regulatory complexities unique to insurance — including stochastic modeling, [[Definition:Monte Carlo simulation | Monte Carlo simulations]], [[Definition:Loss development | loss development]] projections, and multi-scenario [[Definition:Capital modeling | capital modeling]]. Widely adopted platforms include Willis Towers Watson&amp;#039;s Emblem and Igloo, Moody&amp;#039;s RMS for [[Definition:Catastrophe modeling | catastrophe risk]], Milliman&amp;#039;s MG-ALFA for [[Definition:Life insurance | life]] and [[Definition:Annuity | annuity]] projections, and Arius and ResQ for [[Definition:Property and casualty insurance | property and casualty]] reserving.&lt;br /&gt;
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🔗 These tools operate across the actuarial workflow. On the [[Definition:Pricing | pricing]] side, platforms incorporating [[Definition:Generalized linear model (GLM) | GLMs]] and increasingly [[Definition:Machine learning | machine learning]] capabilities allow actuaries to segment [[Definition:Risk class | risk classes]] with granularity that was impractical a generation ago. For [[Definition:Reserving | reserving]], software automates [[Definition:Chain-ladder method | chain-ladder]], [[Definition:Bornhuetter-Ferguson method | Bornhuetter-Ferguson]], and other triangulation methods while embedding audit trails to satisfy [[Definition:External auditor | external auditors]] and [[Definition:Regulator | regulators]]. On the [[Definition:Enterprise risk management (ERM) | enterprise risk management]] front, [[Definition:Economic capital | economic capital]] and [[Definition:Solvency II | Solvency II]] internal model platforms — such as those from Moody&amp;#039;s Analytics and FIS — run thousands of stochastic scenarios to quantify tail risks under frameworks ranging from the [[Definition:Risk-based capital (RBC) | RBC]] regime in the United States to [[Definition:C-ROSS | C-ROSS]] in China. The shift to [[Definition:IFRS 17 | IFRS 17]] across much of the world has driven a major wave of software investment, as insurers in the EU, Singapore, Hong Kong, Japan, and beyond needed systems capable of calculating the [[Definition:Contractual service margin (CSM) | contractual service margin]] and [[Definition:Risk adjustment | risk adjustment]] required by the new standard.&lt;br /&gt;
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🚀 The strategic importance of actuarial software has grown sharply as the industry&amp;#039;s data volumes and regulatory demands have expanded. Manual spreadsheet-based processes — once the norm even at large insurers — introduce [[Definition:Model risk | model risk]], version-control problems, and scalability constraints that modern platforms are designed to eliminate. [[Definition:Insurtech | Insurtech]] firms and technology vendors are now challenging incumbents with cloud-native, API-driven solutions that integrate actuarial modeling directly into [[Definition:Policy administration system | policy administration]] and [[Definition:Underwriting | underwriting]] platforms, shortening the cycle from analysis to decision. For [[Definition:Chief actuary | chief actuaries]] and [[Definition:Chief risk officer (CRO) | CROs]], selecting the right software stack is no longer just an efficiency question — it directly affects the accuracy of [[Definition:Technical provisions | technical provisions]], the credibility of [[Definition:Rate filing | rate filings]], and the organization&amp;#039;s capacity to respond quickly to emerging risks like [[Definition:Cyber insurance | cyber]] and [[Definition:Climate risk | climate]].&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:Generalized linear model (GLM)]]&lt;br /&gt;
* [[Definition:IFRS 17]]&lt;br /&gt;
* [[Definition:Capital modeling]]&lt;br /&gt;
* [[Definition:Reserving]]&lt;br /&gt;
* [[Definition:Insurtech]]&lt;br /&gt;
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