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: The article provides a summary of key issues presented at the 2023 U.S. Living to 100 Symposium focused on the interests of retirement professionals and retirees. It provides an overview of the subjects covered. The discussion focused on the well-being of retirees and the development of the retirement system. It is focused on late-in-life issues and having the best life possible during that period. It balances technical and lifestyle issues, with an emphasis on mortality and longevity trends and influences. Some of the topics discussed include the impact of COVID, climate, housing, and age-friendly communities. The Elder Tech Symposium was merged into Living to 100 and includes discussion of a variety of technology approaches to improve lives and simplify support. The symposium recognized that the decisions needed and concerns during retirement are different later in life, particularly as people decline.

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: The SOA Research Institute Aging and Retirement Strategic Research Program and Retirement Section are pleased to make available a research report that examines megatrends and potential paradigm shifts, and how they may impact the future of retirement and retirement plans, as well as the macro forces that will shape those trends.

Description: Explore the findings from the research paper recently released by Milliman and the SOA, highlighting the growing need for support of informal/family caregivers. We will discuss both quantitative and qualitative data that illustrates not only the cost and burgeoning need, but the mental/emotional stressors that come along with this work.

Description: The document explores how AI-supported underwriting influences mortality slippage in accelerated underwriting and evaluates real-world applications, risks, and industry impacts.

Description: Mr. Zhao stressed that the CBRC adhered to the national principles of risk-oriented, problem-oriented, and openness-oriented, and remained fully mobilized and united to the benefit of the insurance industry. The CBRC overcame the difficulties of the epidemic and pushed forward the C-ROSS Phase II project.

Description: Learn industry best practices including challenges faced by retirees, such as needing exposure to growth, most exposed to sequencing risk, and the need for smooth returns to avoid poor investor behavior caused by risk aversion. Other topics will include how to set investment objectives which consider the members’ real-world needs and how to build portfolios and implement risk management strategies to meet those objectives. The speaker will provide real-life examples/case studies.

Description: On average, contracts receiving their first star rating receive 3.20 stars, compared to existing or established contracts receiving 3.90 stars on average. This 0.70 disparity in quality ratings creates significant hardship on new contracts when this lower star rating decreases their payments in the following calendar year. This article explores the disparity in Medicare Advantage Star Ratings between contracts receiving their first star ratings (“New” contracts) and existing contracts, including: 1. Understanding what happens to Medicare Advantage Payments when contracts receive lower star ratings? – What is the Star Rating cliff and why does it matter to new contracts? 2. Explaining when a contract receives their first star rating and how much enrollment this requires – When does the Star Rating cliff occur? 3. Noting which specific star measures “New” contracts struggle with, including those contracts under large parent organizations, contracts with rapid growth, and all other new contracts. – How can my contract avoid the Star Rating cliff?

Description: What is the difference between a Single-Payer and Universal Health Care System, and how could the U.S. implement a system that would reduce the growth of medical costs while increasing quality.