Description: "Demographic components of Future Potential Old-Age Support Ratios – Kirill Andreev, Ph.D., United Nations, Population Division, New York, Mila Andreeva, KAMA Consulting Effect of internal Migration on the Health of Taiwan’s Elderly People – Jack C. Yue, Ph.D., – National Chengchi University, Department of Statistics, Taipei, TaiwanPopulation Aging and Canada’s Social Contract: Covid-19 Catalyst for Change – Douglas Andrews, FSA, FCIA, Ph.D., Lori J. Curtis, Ph.D., – University of Waterloo"

Description: "Establishing Methods for Annual Updates to Cohort Life Expectancies – R. Dale Hall, FSA, CERA, MAAAManaging Director of Research, Society of Actuaries Research Institute Longevity Disparity across Communities in the United States – Lijia Guo, Ph.D., ASA, MAAA , US Government Accountability Office, Applied Research and Methods Division, Washington DC"

Description: Both the SOA and AARP will showcase their recent research projects highlighting the impact of marginalization on aging and retirement. Learn how being a member of a marginalized group changes your outcomes as well as your perspective on aging and retirement.

Description: What are the recent trends in mortality? Should we expect different mortality experience in a post-COVID-19 world? Join us as we review the latest emerging trends in U.S. population mortality.by the end of this session, you will understand the impact of COVID-19 on future mortality experience. You will also have an awareness of other major causes of mortality and how they are trending.

Description: Hear about some applications using quantile regression-derived individual and group claim distributions and how they may be used in various traditional health care modeling situations. The session will not focus on the technical use of quantile regression to obtain estimates of claim distributions, but more so is intended to focus on the uses of the distributions in actuarial modeling and the additive framework in assessing claims distributions. Presenters will show how actuaries can better assess risks by focusing on the individual- and group-specific claims distributions as opposed to traditional point-estimate-centric models.

Description: With mortality rates significantly higher in 2020 and 2021 due to the COVID-19 pandemic, actuaries that rely on historical experience cannot properly craft assumptions about the future due to the recent excess deaths. This webcast focuses on the practicality of using pandemic mortality experience, as well as how to overcome the practical challenges of that data implementation. Explore an overview of different approaches used by institutions in the U.S., Canada and UK and an observation of industry survey responses. There will also be a comparison to recent SOA expert opinion surveys and short term impacts on the future of U.S. mortality.

Description: Health care has changed rapidly over the past couple of years. The pandemic has shifted consumer behavior in how and where they receive health care as well as consumer attitudes toward health care. Payers continue to design innovative solutions in responses to their patient’s needs and expectations. These changes in consumer behaviors and the responses by payers are expected to impact both health care cost and utilization. Discuss changes in health care that have emerged due to the pandemic and how they are expected to influence actuarial assumptions. Explore epidemiological models commonly used in the industry, the considerations when using these models, as well as the challenges with regards to gathering and interpreting relevant experience data. By attending this session, you will be able to: Identify shifts in consumer behavior that have emerged from the pandemic and describe how payers are responding to new patient expectations. Discuss how these post-pandemic changes by consumers and payers influence medical spending. Determine which actuarial assumptions are impacted and how and if the impact is expected to be temporary or permanent. Discuss considerations taken by actuaries and challenges faced when modelling actuarial assumptions post pandemic.

Description: This article provides an overview of critical illness insurance: history, product description, and the three primary ways to offer critical illness coverage in the United States. This article also contains an illustration of an issue age premium rate calculation, as well as product features and rating applications specific to the various types of critical illness coverage.

Description: An analysis of US population mortality trends and the impact of COVID.

Description: Mortality Model Selection and Combination in RAlternative approaches for selecting mortality models and forecasting mortality have been proposed. The usual practice is to base mortality forecasts on a single mortality model selected using in-sample goodness-of-fit measures. However, cross-validation and other alternative out-of-sample measures are increasingly being used in model selection, and model combination methods are becoming a common alternative to using a single mortality model. Such methods combine predictions from multiple mortality models to reduce model choice uncertainty and improve forecast accuracy. Explore techniques to select and combine mortality models using the freely available open source R package CoMoMo (https://github.com/kessysalvatory/CoMoMo), which extends the widely used R package StMoMo (https://CRAN.R-project.org/package=StMoMo). We will use data for the USA and other countries to discuss and demonstrate four different model combination approaches including simple model averaging, Bayesian model averaging, model confidence set, and stacked regression ensembles.