Description: Modeling Approaches and Challenges focuses on approaches to real world simulation and the challenges and considerations in real world simulation. Topics include: A frequency domain approach to build realistic multi-horizon scenarios. (Ortec approach) Cascade models structure linking models for major asset classes and economic variables. (Moody’s approach) Overview of models, calibrations & approaches within the context of different use cases. Deterministic & stochastic approaches. Importance of model re-calibration flexibility. We will also discuss specific insights into considerations and challenges in real world simulation, which include topics like: Setting capital market assumptions and/or calibration targets. Assumptions about correlation and causality. Calibrating the model to capital markets assumptions. Validating the model against capital market assumptions. Role of history, market data and stylized facts. Importance of back testing. Calibrating the model to multiple investment horizons. Inclusion of alterative asset classes such as private equity, infrastructure, and direct real estate. Associated issues of limited data, illiquidity and greater uncertainty about calibration targets.

Description: Article describes best practices for teaching a course module that involves multiple parameters. A good example is hypothesis testing which requires consideration of the parameters, sample-size, population distribution, known variance and has as consequences whether a normal or t distribution should be used or whether non parametric methods are used. The articles recommends use of the Prime Implicant Normal Form as a means of teaching. It shows the superiority of this method over other forms such as heuristics, complete rules, or graduated approaches.

Description: A summary recap of the recent SOA Health Conference held in Dallas, TX in June of 2025. With the intentional use of AI to assist with the summary, this article gives a good overview of the recent conference with personal commentary from one of the attendees.

Description: The prospects for China's health insurance has increased significantly in 2018, incentivized by a series of favorable government policies to support the development of commercial health insurance. However, the market still lacks relatively mature products and services. Overall there is a common understanding in the industry that good coverage plus service is the foundation for health insurance future development, and product innovation plus care management is key for an insurance company to maintain sustainable development in the competition. In this presentation, Dr. Yang will discuss the market trend both at home and abroad with respect to health management as well as its impact on product design, pricing and cost control. With the development of internet and big data, today’s health actuary has a special role in taking advantage of the digital transformation and achieving a high-quality and efficient health care service model.

Description: Mindful data visualizations show the end users the end way in how to analyze and interpret your data. More importantly, they can then use this data they see to drive decisions and modeling going forward.

Description: A pension actuary and a life actuary collaborate to express public pension liability and asset issues in terms and figures that an insurer would use

Description: A brief introduction to a new SOA research on liability-driven investment benchmark model.

Description: The December 2013/January 2014 edition of The Actuary magazine—the Society of Actuaries’ flagship publication.

Description: Hot Topics in Setting Pension Return Assumptions is the third in a series, following Mathematics of Pension Return Assumption and Inflation, focusing on Effects, Forecasts, and Role in Pension Valuations. What time horizon is more appropriate for Capital Market Assumption (CMA) forecasts: mid-term or long-term time horizon, or a blend of both? How do we map the asset classes of a plan's own investment policy to the asset classes of investment forecasters' CMAs? If we use asset-smoothing for valuation assets, should we use market-driven expected returns or smoothed/average versions of them?

Description: This paper is an introduction to AI technology designed for actuaries to understand how the technology works, the potential risks it could introduce, and how to mitigate risks.