<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Actuarial Science |</title><link>http://pramo.info/tags/actuarial-science/</link><atom:link href="http://pramo.info/tags/actuarial-science/index.xml" rel="self" type="application/rss+xml"/><description>Actuarial Science</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-uk</language><lastBuildDate>Wed, 27 May 2026 14:30:00 +1000</lastBuildDate><image><url>http://pramo.info/media/icon_hu_f565da7a9ba9f05b.png</url><title>Actuarial Science</title><link>http://pramo.info/tags/actuarial-science/</link></image><item><title>Towards Fairer Retirement Outcomes: Health-Related Mortality Modelling</title><link>http://pramo.info/future/allactuariessummit/</link><pubDate>Wed, 27 May 2026 14:30:00 +1000</pubDate><guid>http://pramo.info/future/allactuariessummit/</guid><description/></item><item><title>Climate and Sustainability Learning Resource (Ongoing)</title><link>http://pramo.info/certifications/climate-sustainability/</link><pubDate>Tue, 02 Dec 2025 00:00:00 +0000</pubDate><guid>http://pramo.info/certifications/climate-sustainability/</guid><description>&lt;p&gt;This ongoing learning resource provided by the Actuaries Institute focuses on the critical intersection of climate change, environmental sustainability, and actuarial science. The syllabus covers methodologies for evaluating climate risks, modeling the financial impacts of environmental shifts, and developing sustainable strategies for long-term planning. It equips professionals with the necessary knowledge to integrate climate-related data into core actuarial workflows.&lt;/p&gt;</description></item><item><title>2025 Australasian Actuarial Education and Research Symposium - Talk</title><link>http://pramo.info/events/example/unsw-symposium/</link><pubDate>Mon, 01 Dec 2025 14:30:00 +0000</pubDate><guid>http://pramo.info/events/example/unsw-symposium/</guid><description/></item><item><title>Rethinking Mortality: A State-Based Dynamic Probabilistic Modelling Approach Using National-Scale Health Data</title><link>http://pramo.info/publications/honours/</link><pubDate>Thu, 30 Oct 2025 00:00:00 +0000</pubDate><guid>http://pramo.info/publications/honours/</guid><description>&lt;h2 id="overview"&gt;Overview&lt;/h2&gt;
&lt;p&gt;[cite_start]This thesis argues that disease-centred mortality models—incorporating health conditions, medical procedures, and medication histories—offer significantly enhanced predictive accuracy for retiree mortality compared to conventional models relying solely on age and gender[cite: 102].&lt;/p&gt;
&lt;h3 id="key-findings"&gt;Key Findings&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;[cite_start]&lt;strong&gt;Improved Accuracy&lt;/strong&gt;: The proposed models outperformed the Australian Life Tables (ALT) benchmark in both individual-level predictions and cohort-level forecasts[cite: 667].&lt;/li&gt;
&lt;li&gt;[cite_start]&lt;strong&gt;Financial Impact&lt;/strong&gt;: For a cohort of 100,000 retirees, the proportion expected to outlive their planning horizon falls from 9.9% (ALT) to 6.7% with this model[cite: 73].&lt;/li&gt;
&lt;li&gt;[cite_start]&lt;strong&gt;National Policy&lt;/strong&gt;: Implementing these models could decrease Age Pension expenditure by approximately $83.2 million per year by improving retirement drawdown strategies[cite: 74].&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 id="full-thesis"&gt;Full Thesis&lt;/h2&gt;
&lt;p&gt;The full thesis PDF is embedded below for convenient reading.&lt;/p&gt;
&lt;div style="margin-top:1rem;"&gt;
&lt;p&gt;&lt;strong&gt;Full thesis (PDF):&lt;/strong&gt; &lt;a href="thesis.pdf" target="_blank" rel="noopener"&gt;Download the thesis (PDF)&lt;/a&gt;&lt;/p&gt;
&lt;/div&gt;</description></item><item><title>ANU Actuarial School Brownbag Seminar- Talk</title><link>http://pramo.info/events/example/actuarial-brownbag/</link><pubDate>Sat, 10 May 2025 12:00:00 +0000</pubDate><guid>http://pramo.info/events/example/actuarial-brownbag/</guid><description/></item></channel></rss>