Description: When designing and pricing a healthcare product, it is not only important to know how to model frequency and severity, but it is essential to understand human behavior. Of course, the issue of anti-selection in medical insurance is well known as individuals know more about their health and prior expenditures than an insurer does. This type of behavior is certainly rational, and to be expected.

Description: This publication presents an exploratory framework that applies volatility signals—specifically the VIX and MOVE indices—to asset allocation decisions. Rather than prescribing a definitive model, the work highlights a potential pathway for linking equity and bond market risk expectations to portfolio construction. The analysis demonstrates how relative volatility between asset classes can inform dynamic weighting, opening the door to more adaptive strategies in shifting market environments. Importantly, this is not intended as a finished methodology, but as a foundation on which more experienced professionals can build. Readers with advanced backgrounds in finance, risk management, or quantitative analysis are encouraged to refine, stress-test, and extend the framework to suit their own investment contexts. By positioning the concept as a starting point rather than a conclusion, the publication invites collaboration and deeper exploration into how volatility-based metrics may enhance long-term allocation models.

Description: Inspired by other financial savings products available to Canadians, this article describes a potential solution for financing future health expenses with the creation of a Registered Health Savings Account (RHSA). This solution has been thought on the basis of four premises : 1- Individual Accountability for Health Expenses; 2- Early Savings Leads to More Accumulation; 3-PreferredTax Treatment for Personal Health Savings; 4- Complementing current public and private health systems; Main elements of the RHSA are described (Contributions, Accumulation, Utilization of account, Management by financial institutions).RHSA'S expected balances and some other results under three scenarios (a person in good health, one in poor health, and one with unexpected death at age 45) are summarized in a table. Health expenses deducted yearly from RHSA's balance were estimated using total, per capita, provincial government health expenditures by age-band for Canada, in 2020, from the Canadian Institute of Heath Information’s (CIHI), which account for 71.8% of total expenditures, that is public + private. Thus 28.2% of total expenditures were used for private health expenditures, then forecasted to 2024 and projected using a 4% annual trend. Some objections to the solution explored were anticipated as well as some refutations to these objections.

Description: As the new VM-22 framework reshapes reserving for non-variable annuities, actuaries face both opportunities and challenges. Our latest insight and highlights what you need to know about assumption setting, model validation and asset optimization ahead of 2026.

Description: Discussion of practice areas, the Society of Actuaries' strategic plan, and the Implementation Task Force on Sections and Practice Areas.

Description: The article summarizes 2013 survey results of company assumptions for term products in the post-level period. The focus is on product design, shock lapse assumptions, and mortality deterioration assumptions. This article features highlights from the larger SOA-sponsored research project on this topic published in 2013 that compiled end-of-2012 assumption data from 41 companies. This content may prove useful to product development actuaries as they consider their current post-level term assumptions.

Description: A Framework for Managing Surplus by David N. Becker from The Financial Reporter, May 1999, Issue No. 39.

Description: Help to generate ideas for formulating a pricing strategy of 2015 individual health insurance products despite having very limited claims and premium experience in early 2014.

Description: A discussion of adjustments to the issue and underwriting process to speed up the process in order to succeed with bank distribution of insurance products.

Description: Big data, predictive analytics, machine learning and AI will likely transform the insurance market and the actuarial profession. The actuarial profession is seeing changes many markets, including health and property and casualty. This article describes these trends and provides an introduction into what companies and the Society of Actuaries (SOA) are doing to adapt and capitalize on these trends.