Description: This article outlines Georgia State University’s (GSU) innovative approach to actuarial science education in response to the evolving demands of the profession, including data science, AI, and climate risk. It highlights a comprehensive pipeline that supports students from early career exploration through high school outreach, into personalized undergraduate academic paths, and onto professional readiness. Key features include project-based learning integrated into core actuarial courses, hands-on technical training in R and Python, and industry-aligned case studies.

Description: The implementation of the IFRS 17 insurance accounting standard has brought significant changes to the financial reporting landscape of insurance companies. With new disclosure requirements and altered profit analysis, understanding and interpreting future profitability have become a topic of concern for the industry. While stability remains a key objective for insurance companies, the earning patterns might become more volatile especially when the contractual service margin (CSM) is exhausted, and a loss component (LC) needs to be established. Reinsurance, a common risk mitigation tool, can play a pivotal role in managing earnings volatility and minimizing losses for onerous measurement units. In this article, we propose a new key performance indicator (KPI) called “loss recoverability” to assess the performance of reinsurance treaties in achieving these objectives. We explain how this KPI can be utilized in multiple scenarios to evaluate the effectiveness of reinsurance strategies and pursue stability in earning patterns.

Description: Actuarial work in the life and health insurance industry is highly data-driven and complex. Actuaries perform a wide range of tasks such as experience studies, valuation, reserving, pricing, and risk modeling, all of which require vast amounts of data and sophisticated analytics. Traditionally, many of these tasks have been carried out using Excel and other legacy tools, but as data volumes grow and the need for more accurate predictions intensifies, actuaries are turning to more robust platforms. Cloud Data & Artificial Intelligence (AI) Platforms, such as t Databricks offer a unified platform that integrates data management, analytics, and machine learning, making it a powerful tool for actuaries. In this article, we’ll explore how Cloud Data & AI platforms can be used as an actuarial workbench, enabling actuaries in the life and health sector to streamline critical tasks like experience studies, valuation, and reserving.

Description: This article summarizes findings from a recently published peer-reviewed study in the Journal of Risk and Insurance (Hanewald et al., 2025),[1], which examined how access to housing wealth affects stated demand for LTC insurance in China. We conducted a survey of homeowners aged 45-–64 across 49 cities in China and found that offering reverse mortgages or home reversion products significantly increased stated demand for LTC insurance. This article highlights the study’s key results and implications for insurers, actuaries, and policymakers.

Description: Overview of the regulatory requirements around sustainability reporting in Europe.

Description: Describing background of SOA Committee for Middle East, Africa &Pakistan (MAP) region, activities and future actions.

Description: IFRS 18: Introduction for Insurers

Description: There will be inflection points in the value of an instrument when interest rates change. These inflection points could materially impact the approximation of value change using ALM metrics. In this part of the seven-part series, I will highlight: • How to identify the inflection points; • the range of rate changes where ALM metrics may be relied upon i.e., the “validity” range, outside of which recalculation of the ALM metrics is required and the potential that one needs to rebalance the portfolio; • a technique to improve on the approximation of value change beyond the validity range; and • a technique to convert non-linear change on the yield curve to be used with duration and convexity.

Description: The 2024 Dangerous Risks survey shows respondents react to recent increases in "old favorite" risks as technology evolves and the environment moves away from the pandemic.

Description: How does mortality experience impact earnings under the new GAAP financial framework? This article discusses how to isolate key components from financial models related to decrements, as well as how to handle the changes in the financial reporting landscape including: the aggregation of insurance policies into cohorts, dynamic reserving, and the limitations imposed by caps and floors. Looking at the components of earnings, such as the present value of benefits, expenses, and premiums, and how these elements interact is critical to form a comprehensive earnings story.