Description: The Individual Life Experience Committee has numerous research projects underway. Take a look at three current areas of research: the analysis of the interaction of lapse and mortality experience using data from mandatory submissions; a deep dive into old age mortality; and an update on the committee's work to establish a predictive analytics framework that will be open for all actuaries and data scientists to use. By attending the session, you will: - Better understand the research conducted by the Individual Life Experience Committee. - Better understand the link between lapse and mortality experience, appreciate some of the nuances of older age mortality, and gain knowledge about a predictive analytics framework that will be released in the future.

Description: 2009 - 2016 ILEC Mortality Report Appendices

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: Universal Life with Secondary Guarantees (ULSG) was first introduced in the late 1990's as low-cost, long-term death benefit protection. As this business ages, writers are experiencing pressured earnings from emerging experience, secondary markets for insurance products and low interest rates. In response, writers are sharpening their pencils on experience analysis and risk management with an eye for opportunities to increase the performance of their blocks.

Description: After years of discussion and debate, PrinciplesBased Reserving (PBR) is finally a reality. Small insurance companies have a unique opportunity to decide between electing for the company-wide exemption or adopting the PBR methods. This article discusses the benefits and challenges of the options available to small insurers under VM-20 as well as best practices that have been found along the way.

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: Learn more about the predictive modeling that was applied to industry data for the lapse and mortality experience in the post-level term period. Novel approaches were taken to model the shock lapse, subsequent lapse, and mortality experience. Observe a demonstration of the Tableau tool, which was built to allow users to analyze data on their own.

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"