Description: The Society of Actuaries Strategic Research Program Steering Committee is pleased to release this report examining how well people estimate their own life expectancy.

Description: The presenters will highlight differences in mortality that result from socioeconomic issues. Topics will include the differences in cause-specific mortality among different socioeconomic classes, trends in these gaps over time, and recommendations for reducing inequalities in life expectancy in the future.

Description: The session offers high-level initial steps to get started using R, as well as a list of helpful resources for both general data science and actuarial science with R. Attendees will learn about popular R packages to perform practical tasks such as importing, transforming and visualizing data, as well as packages commonly used by actuaries. You will also be introduced to the markdown package for creating reproducible and reusable analyses and workflows. By the end of the session, you will be familiar enough with using R and RStudio to begin incorporating these tools in your day-to-day work as an actuary

Description: The observations and methodologies demonstrated in this article can help actuaries further analyze population mortality trends by causes of death and by socioeconomic status.

Description: This report covers the latest emerging trends in U.S. population mortality. The SOA relied upon data furnished by the Centers for Disease Control and Prevention (CDC). Observations are based on the CDC’s recent release of 2018 mortality experience, along with prior mortality experience data from 1999 through 2017.

Description: Uncertainty of a predictive model is a fact of life that many insurers could be overlooking at their peril without a framework for assessing it. The article provides a framework to understand the prediction uncertainty, which can be critical for the insurance operations using predictive models. Coin toss example explains model uncertainty and randomness inherent in making predictions to the number of heads expected. A mortality analysis case study illustrates how the Bayesian methodology can be used to develop the prediction uncertainty. In particular, the article shows that the Bayesian framework is a way to combine historical data and actuarial judgment, and directly address the model uncertainty through its posterior distribution.

Description: A data format for mortality tables along with applications.

Description: A document summarizing key observations on historical U.S. population mortality rates by gender and single year of age for calendar years 2000-2018.

Description: The presenters will address innovations in health and wellness designed to mitigate and/or manage mortality risk. The presenters will briefly review the latest research on the leading causes of death and share ways that life insurers and insurtech partnerships are using technology, customer engagement and scientific advances to enhance/extend the lives of policyholders. The presenters will draw from industry research and reinsurer studies and from the latest initiatives in health and wellness innovations.

Description: A table of present historical U.S. population mortality rates by gender and single year of age for calendar years 2000-2018.