Description: Get an in-depth explanation on how data scientists and actuaries can work together to battle the issues arising from big data. Join our focus on the insurance industry as a whole and look at data scientists' and actuaries' roles from the views of different areas of the industry. We will also focus on how data science can be a valuable tool for actuaries. After the session, you will be able to understand: - How developments in data science are shaping Insurance Industry practices - How data scientists can help actuaries - How data science can be used to improve analysis of industry experience

Description: In summer 2021, the SOA Research Institute’s Mortality and Longevity Strategic Research Program sponsored a webcast examining individual life and group life emerging mortality in a COVID-19 world. Since then, Delta and Omicron coronavirus variants have fueled waves of the virus in the U.S., boosting the total number of COVID-19 deaths since the beginning of the pandemic to near the 1 million mark. Hear an update and insights into how the life insured population is faring during COVID-19 by discussing the findings from two recent SOA Research Institute initiatives. LIMRA, Reinsurance Group of America (RGA), the Society of Actuaries (SOA) and TAI have collaborated to analyze the impact of COVID-19 on the individual life insurance industry’s mortality experience. Additionally, the SOA Research Institute has surveyed insurers to gather a high-level view of U.S. Group Term Life Insurance mortality results during the COVID-19 pandemic, comparing them to pre-pandemic mortality levels. The Group Term Life industry mortality results will be presented with monthly data through March 2022.

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

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.

Description: "Living to 100 in the time of COVID-19: A Study of Late –Life Mortality Trajectories, Leonid A. Gavrilov, Ph.D., Natalia S. Gavrilova, Ph.D., Academic Research Centers, NORC at the University of Chicago Swedish Mortality Does Not Decelerate in Recent Cohorts, or Does it? – Roland Rau, Ph. D., Professor, University of Rostock & Max Planck Institute for Demographic Research, Rostock, Germany; Marcus Ebeling, Ph.D., Karin Modig, Ph.D., Associate Professor, Anders Ahlbom, Ph.D., Professor Emeritus, Karolinska Institute, Stockholm Sweden; Kai Kaufhold, Aktuar DAV, Ad Res Advanced Reinsurance Services GmbH, Cologne, Germany; Annika Ziegler, Lukas Stake, Hochschule Koblenz & Ad Res, Germany"

Description: The session will highlight trends in recent industry mortality and lapse studies that have been conducted, including areas where individual companies typically have limited data. The sources of data feature SOA studies as well as other industry studies conducted by consultants and/or reinsurers. Gain an understanding of current drivers of mortality and lapse experience for life insurance evidenced in industry studies, and an understanding of available data to supplement experience in areas where you may have limited internal experience.