Description: General Session VI

Description: Critical factors to consider as we age include where we live, who we interact with, how we get the help and support we need when we need it, and how our health care is organized and delivered. Underlying this is how we finance the cost of specialized housing, care and support. Some communities are age-friendly where we can obtain supportive services, others are not. Some people choose to live in senior housing which integrates support services, others choose to live in the community among people of all ages. Some health care systems are well designed to meet the needs of older people, others are not. The cost of living for older adults, considering all of these factors, varies by community. Explore more about the perspective of older adults, how communities have structured to meet their needs, and how society as a whole is becoming aware of and addressing a growing aging population.

Description: In this interactive forum, presenters will share best practices to get the most out of your AU program. Explore trends in regulations, big data tools and predictive models. Case studies will be used to illustrate how monitoring results can provide actionable information for management to update programs and what it all means for accelerated underwriting programs. Attendees will come away with a better understanding of how tools are evolving, regulatory trends and best practices for explaining decisions to applicants, as well as targeted changes to accelerated underwriting programs

Description: Read the Quo Vadis Reinsurance.

Description: This article summarizes five key lessons we have learned in implementing LDTI and shares our insights on practical ways to address them. This is not an exhaustive list of implementation challenges, but companies that can successfully tackle the issues we describe should have a smoother data and systems implementation transition.

Description: This session will examine bias from a social science perspective. It will discuss the three types of systemic biases using the National Institute of Standards and Technology (NIST) model. The NIST model details the three types as historical bias, societal bias, and institutionalbias. The session will also provide several examples of each type to provide a framework for identifying the social structure of bias.

Description: Discover an introduction to decomposing differences in life expectancy by age and cause of death. Take a look into demographic techniques that decompose life expectancies at birth and older ages into the portions contributed by later age groups and causes of death-. These have been in existence for some time and provide a convenient device for analyzing mortality change over time as well as differences between sexes, countries, and ethnic groups. The methods will be described and illustrated by spreadsheet examples.

Description: "Population Aging, Global Climate Change and Social Security – Sally Shen, Research Associate, Global Risk Institute, John A. Turner, Ph.D., Director, Pension PolicyClimate Change and Mortality Time for Actuaries to Pay Attention – Sam Gutterman. FSA, CERA, FCAS, FCA, HONFIA, MAAA"

Description: The Society of Actuaries Research Institute, in collaboration with Reinsurance Group of America, Incorporated, a leading global life and health reinsurer, announced findings from new research on behavioral science for the life insurance sector. This research simulated online term life insurance purchasing to test behavioral science techniques.

Description: Both LDTI and IFRS 17 have introduced numerous new metrics with most companies having only crossed the finish line, just complying with what's needed for reporting due the complexity and large amounts of data required to simply comply. How do you leverage all the work you did to get proper business insights across the organization that tie back to these reporting metrics? This presentation covers a perspective of pain points faced in getting over the the hurdle in complying with LDTI and IFRS 17, upcoming hurdles, emerging KPIs, as well as how to best manage the data, technology, and processes to produce the analysis around these KPIs efficiently.