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: The presenters will explore the current state of the North American mortality baseline and long-term improvement assumptions and determine what we can learn from the UK's approach. They will share research done by the Society of Actuaries and other organizations to describe how to build a better model, plus show the impact socio-economics and other factors have on longevity expectations. The presenters will offer suggestions for how U.S. and Canadian pension plan and insurance actuaries--and the industry itself--can best use this research to develop a better model for the risk management of pension plans and group annuities

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: This webcast will walk through several statistical methods for imputing race and ethnicity from U.S. datasets, highlighting strengths and weaknesses and evaluating accuracy.

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: "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: 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: "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"