Description: Discussion of the challenges actuaries face in selecting an interest rate for the purpose of calculating Withdrawal Liability for a Multiemployer pension fund in the US. Recent court cases are referenced.

Description: Through this Call for Essays, the SOA seeks to gather perspectives, opinions and data on how to advance the state of effective tools, products, and strategies to assist individuals, financial advisers, employers and other stakeholders.

Description: Majority of Latin American Consumers Worry About Financial Security in Retirement Yet Only 20% Have Done Any Planning:

Description: There is no silver bullet to improving retirement income outcomes for retirees. However, a combination of changes can be of significant value in addressing this overlooked issue. Although QLACs on the surface have potential value, they are not nearly as efficient as they could be. So far, employer plans have provided limited options for retirement income solutions. IRAs may not cost effectively serve the best interest of retirees. Employer plans should be encouraged to become retirement income providers and alternative approaches should be considered. The current prohibition on allowing plans to modify benefit payouts based on mortality experience should be reconsidered to allow for innovative plan income designs. Improvements to the deaccumulation stage of the retiree nest egg are challenging yet necessary.

Description: An interview with actuary Lee Gold reveals preliminary results of a recent SOA research project which surveyed employees on what retirement plan features they prefer.

Description: Our understanding of the biology of aging is increasing rapidly, creating insight into how and why any organism is aging. Some of the mechanisms by which the process of aging occurs in mammals are sufficiently well understood that clinical trials targeting them in humans to improve later life health and longevity are now being undertaken. Translating results seen in mammals to humans has the potential to increase life expectancy far beyond what we have seen historically. Come explore the current state and outlook of research.

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: 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.