Description: Mortality is a fundamental element in the financial projections of the finances of social security programs around the world. Prominent actuaries from the U.S. Social Security Administration, Canada's Office of Superintendent of Financial Institutions and the U.K. Government Actuary's Department will discuss some of the key factors and current issues associated with these projections. Improving mortality has and will have a significant effect on the affordability and importance of income through retirement to many population segments in these countries.

Description: "Driving Longevity Through Educational Attainment – Robert L. Brown – Ph. D. Higher Age U.S. Mortality By Education and Cause of Death Trends, Inequality and Controllable Risk Factors – Andrew J. G. Cairns – MPA Ph.D., Maxwell Institute for Mathematical Sciences, and Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Edinburgh, Scotland, UK, Cristian Redondo Lour´es, Ph.D., Actuarial Solutions,"

Description: "Weighted compositional data analysis for modeling and forecasting life-table death counts – Han Lin Shang, Ph.D., Professor of Business Analytics and Director of Research at the Department of Actuarial Studies and Business Analytics at Macquarie Business School, Macquarie University, Sydney, Australia, Steven Haberman, PhD, Bayes Business School, City University of London, UK Compensation Effect of Mortality as a Challenge to Life Extension – Natalia S. Gavrilova, Ph.D., Leonid A. Gavrilov, Ph.D. Academic Research Centers, NORC at the University of Chicago"

Description: "Minimum Social Security Benefit (s) and the Alone Stage of Retirement in the U.S.? – Lori J. Curtis, PhD., Douglas Andrews, FSA, FCIA, Ph.D., University of Waterloo The Importance of Cognitive Health – Gordon Woo,Ph.D., RMS LifeRisks"

Description: The pandemic and other current events have greatly impacted the risks that individuals face during retirement. Join us to explore this topic as the results of the Society Actuaries 2021 Retirement Risk Survey are presented. Discover the findings regarding retirement concerns, preparedness and understanding individuals in the U.S. nearing retirement or those who are already retired. This marks the 11th iteration of this biennial survey completed through the SOA Research Institute’s Aging and Retirement Strategic Research Program.

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: Navigate a perspective on the process of developing estimates and projections of mortality rates, based on a Living to 100 paper by the teacher. Discover the approach and considerations an actuary (or others) can take to develop a mortality rate assumption for five time periods. It will describe techniques to estimate historical mortality rates from which to project future mortality rates.

Description: "On the decomposition of mortality models into causes of death – Andrés M Villegas Ph.D – UNSW Australia, Madhavi Bajekal, Ph.D.,HONFIA, University of London, UK, Steven Haberman, Ph.D. – Bayes Business School, University of London, UK Forecasting cause-specific mortality rates using the insights from the cointegration analysis, Séverine Arnold, PhD, Viktoriya Glushko, Department of Actuarial Science, Faculty of Business and Economics (HEC Lausanne), University of Lausanne, Switzerland"

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: Transcript of General Session 1:Implications of Longer Life Spans: What Does This All Mean to Us?