Description: This report outlines a framework for interpretable machine learning algorithms for detecting fraud in health insurance. It discusses the challenges of using black-box machine learning models in the insurance industry and proposes various interpretable methods to enhance transparency and understanding.

Description: This report is a discussion of the significant challenges involved in attempting to research with robust analysis the impact of disparities in health care access, cost and quality of care on financial wellness across racial, ethnic, socioeconomic and other demographic groups in the U.S. for reasons other than or in addition to income, wealth or employment status.

Description: "Examine the impact of traditional deductibles on health care equity and the need for innovative plan designs. You will learn about the limitations of consumer-driven health care costs broadly today, as well as alternative cost-sharing approaches that have been successful in driving consumerism without exposing members to high costs. By attending the session, you will be able to: Have a clearer understanding of the issues surrounding deductibles Be equipped with practical ideas for creating more equitable and effective cost-sharing solutions Assess the feasibility and potential impact of implementing these solutions for your own organization"

Description: The Part D program is funded through a variety of government subsidies and manufacturer discounts. The federal reinsurance, initially designed as protection from catastrophic spending, became a primary source of subsidies for the program. When the Inflation Reduction Act (IRA) is fully implemented in 2025, the funding of Part D will realign to its original intent.

Description: The SOA Research Institute along with the International Section, and the Social Insurance and Public Finance Section are pleased to make available a research report that compares international and domestic mandated paid family and medical leave programs. Special thanks to both Sections for their sponsorship of this effort.

Description: CMS has pioneered innovative strategies for Medicare and Medicaid to address Social Determinants of Health (SDOH). Employers can learn from these models to implement similar approaches for their employee populations. Learn how employers can understand and address SDOH, the incentives for doing so, and the broader benefits.

Description: Learn how insurers provide new opportunities for efficiency and value creation from product design and underwriting through customer engagement and claims. Glimpse some industry use cases for Gen AI and its outcomes as observed by the first movers.

Description: Join us in this webinar where we explore the intricate relationship between Professional Employer Organizations (PEOs) and insurance, diving into the art of risk management within this industry. Gain a comprehensive understanding of the diverse insurance products offered by PEOs, the positioning of PEOs in the actuarial landscape, and the strategic navigation of regulatory challenges.

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: 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.