Description: Learn about key actuarial and analytic tools and methodologies used by commercial health insurance to identify and quantify drivers of healthcare cost and utilization (including wasteful and low-value ones) and risks. Use case scenarios in which these tools and methodologies apply, such as underwriting, reinsurance, medical management for population health and chronic diseases, managed care contracting, insurance market reform, provider payment reform, etc., will also be covered. Experience from the U.S., China and other parts of the world will be shared.

Description: The key tasks of credit risk capital project under CROSS II mainly focus onL(1 )Adjustment of measurement framework; (2) Calibration of risk factors, including both credit spread risk and credit default risk;3)Introduction of concentration risk measurement; (4) Higher requirement on look-through rule.

Description: In September 2017, the China Insurance Regulatory Commission (CIRC) issued the “C-ROSS Phase II project construction plan”, planned to be used across three years’ time, by perfecting the regulations, improving the operational mechanism and strengthening the regulatory cooperation.

Description: The August/September 2013 edition of The Actuary magazine—the Society of Actuaries’ flagship publication.

Description: The October/November 2015 edition of The Actuary magazine—the Society of Actuaries’ flagship publication.

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: The document is a Call for Essays from the Society of Actuaries Research Institute. Share your real-world experiences with AI in actuarial work—challenges, wins, and lessons—to shape the future of the profession.

Description: In today’s business world, many financial decisions undergo considerable analysis before the decision is made and the decision-maker is often held accountable for the outcomes. The purpose of this research is to introduce the concept of total risk analysis (TRA), which is designed to help the decision-maker answer key questions at the time the decision is made. This paper will focus on a specific example of a typical healthcare decision: setting a budget for claims in the upcoming year. In addition to explaining TRA and providing a case study, this paper presents quantitative research regarding cost distributions for health care costs.

Description: The Mortality and Longevity and Catastrophe and Climate Strategic Research Programs are pleased to make available a report summarizing an expert panel brought together to discuss the impact of wildfires on U.S. health and life insurers.

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.