Description: Excel file to be attached to cover sheet on this same 2005-2007 individual life persistency study. Contains the actual persistency experience data from the study.

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.

Description: Term products exhibit a wide range of behavior as policyholders can elect different term periods and conversion options. While term products have been around for decades, it's only recently that longer level term products are reaching the end of the level term period. Term conversions have historically been an afterthought and are rarely modeled. Discuss the use of predictive modeling techniques such as LASSO regression and cross-validation to build models for level term lapses and post-level term shock lapses, as well as the extrapolation of experience for shorter term products to longer term products (e.g., extrapolating 20-year term experience and applying to 30-year term). Explore the use of traditional techniques to develop term conversion rates and a framework for modeling the assumption. Challenges and limitations of setting lapse and conversion rates will be discussed. By attending the session, you will: - Understand the complexities of term policyholder behavior. - Understand the challenges in developing and implementing assumptions for lapses and conversions. - Understand the application of traditional and predictive modeling techniques for term policyholder behavior.

Description: This session meets the needs of life insurance actuaries who are focused on experience studies, assumption setting, and/or product development. The presenters will use industry data to illustrate how policyholders react to product design, such as premium jumps in the PLT period and UL with high interest rate illustration, and trends in the life insurance market, including the introduction of smoking distinguished rates and the shift towards an increasing number of preferred underwriting classes.

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: "How long is long in longevity? – Jesús-Adrian Álvarez, Ph.D. - Danish Labour Market Supplementary Pension Fund (ATP), The Rate of Aging in humans is constant. New evidence – Marcus Ebeling, PhD., Research Group Mathematical and Actuarial Demography, Max Planck Institute for Demographic Research, Rostock, Germany, Department of Sociology and Demography, University of Rostock, Rostock, Germany; Roland Rau, Ph.D., Professor, Research Group Mathematical and Actuarial Demography, Max Planck Institute for Demographic Research, Rostock, Germany, C6 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Håkan Malmström, Ph.D., C6 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Anders Ahlbom, Ph.D., Professor Emeritus, Karen Modig, Ph.D., Associate Professor, C6 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden Human Lifetimes: Finite But Not Necessarily Bounded – Fei Huang, PhD., School of Risk & Actuarial Studies, UNSW Sydney; Ross Maller, Ph.D., Emeritus Professor, Xu Ning, Ph.D., Research School of Finance, Actuarial Studies & Statistics, Australian National University, Brandon Milholland, Ph.D., IQVIA Plymouth Meeting, PA."

Description: The most recent U.S. population data released by the Centers for Disease Control and Prevention (CDC) and from the U.S. Census at year-end 2021 includes the first ten months of the COVID-19 pandemic in the U.S. While we know the pandemic has had significant impacts on both the U.S. population and insured population mortality, we also see increased mortality due to many other non-COVID causes of death. Where are the biggest changes and what does this non-COVID excess mortality mean over the next few years? Take part as an expert panel hosts an interactive discussion to examine data from general population as well as from both individual life and group life experience studies to explore how these changes might spur innovation in underwriting, assumption setting and pricing.

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,"