Description: Discover an introduction to decomposing differences in life expectancy by age and cause of death. Take a look into demographic techniques that decompose life expectancies at birth and older ages into the portions contributed by later age groups and causes of death-. These have been in existence for some time and provide a convenient device for analyzing mortality change over time as well as differences between sexes, countries, and ethnic groups. The methods will be described and illustrated by spreadsheet examples.

Description: "Population Aging, Global Climate Change and Social Security – Sally Shen, Research Associate, Global Risk Institute, John A. Turner, Ph.D., Director, Pension PolicyClimate Change and Mortality Time for Actuaries to Pay Attention – Sam Gutterman. FSA, CERA, FCAS, FCA, HONFIA, MAAA"

Description: There is value in a framework that allows a smooth transition from a qualitative assessment to a quantitative analysis as entities mature in their understanding of climate risk. In this report, a case study on climate change impact on home prices is used to illustrate a Bayesian network iterative approach to building a model for scenario analysis.

Description: This report explores how artificial intelligence can be applied to investment and retirement planning, highlighting real-world applications, risks, and recommendations.

Description: This report captures expert insights from a March 2025 roundtable on how generative AI is shaping actuarial work and insurance industry practices.

Description: The article will explore the market dynamics driving asset-intensive reinsurance in Japan, analyze how Japanese insurers are strategically utilizing both block and flow reinsurance to achieve diverse business goals, and discuss key considerations for offshore reinsurers seeking to enter this market.

Description: The cyber insurance market looks like it’s growing—rapidly, in fact. However, there’s more to the cyber insurance market than the outward appearance of strong growth. Worldwide aggregate premium’s upward trend may even be cause for alarm. The increase in premium against a flat rate of insured exposure is a key sign that the market could turn from growth to constriction if a solution isn’t found in the near future. If the cyber insurance sector hopes to reach such lofty goals as exceeding $30 billion in global premium by 2028, it’s going to need more capital. Whether directly into the insurance sector or via support from reinsurance and retrocession, fresh capital should help insurers achieve greater market penetration, build a broader foundation for ongoing expansion, and chart a course for long-term sustainable profitable growth. The same sources capital insurers have used since the early days of the market won’t be enough, though. Thankfully, the insurance linked securities (ILS) market seems poised to help, particularly with several promising recent transactions. New sources of capital could bolster the foundation for future cyber re/insurance growth.

Description: A article summarizing the SOA 2024 Regional Symposium in Riyadh

Description: In this talk, we look at two behavioral aspects: from end customers perspective and through the lens of underwriters. We will examine simple rules to improve the insurance underwriting decision to judge whether a risk is insurable and whether they have impact on increasing underwriting decision quality.

Description: Artificial intelligence is rapidly transforming the investment landscape. From natural language processing and large language models to physical AI applications like robotics, autonomous vehicles, and drones, the evolution of AI is reshaping both how we analyze data and where we find opportunity. We’ll begin by exploring the evolution of AI, which is already driving disruption across industries such as coding, customer service, and marketing. However, the future of AI is physical AI (drones, AVs, robotics). With valuations already stretched, and growing concerns about the “circular economy” and bubble risks, investors should focus on high-quality tech companies that generate free cash flow and deliver strong returns on invested capital. We'll explore examples of interesting companies across the globe: Meta, Alphabet, and Uber in the US; ASML in Europe; Tokyo Electron in Japan; TSMC in Taiwan; and BYD in China. The session will also examine how natural language processing and large language models are reshaping the way quantitative and fundamental managers extract insights from raw data. We’ll highlight how these tools are being deployed to enhance understanding of risk and return, and how they’re increasingly supporting collaboration between quant and fundamental teams.