Description: The SOA, with SCOR as the researcher, completed an experience study of post-level term (PLT) lapse and mortality. In the first part of this session, the presenters will cover the key findings of the traditional analysis regarding the shock lapse, the PLT lapse and mortality experience. The remainder of the session will focus on the results of the predictive modeling, which will provide further insights into policyholder behavior in the post-level term period.

Description: After a sustained period of mortality improvement, U.S. population mortality improvement has stagnated in recent years. The presenters will discuss mortality improvement trends in the U.S. population and the causes of death contributing to these trends. U.S. population cause of death trends will be analyzed and compared to trends in the insured population. Mortality rates for major causes of death will be compared between the U.S. population and the insured population. In addition, assumption setting for both older age and later duration mortality as well as mortality improvement will be covered.

Description: 2021 ImpACT Conference - Session 3D: Individual Life Experience: Committee, Contest, COVID-19 and Data Update 10.26.21 Recording

Description: U.S. population death statistics and trends often occupy COVID-19 briefings and daily headlines. There are also publicly available mortality data sources for actuaries and others to perform their own analysis. Yet industry studies examining the impact of COVID-19 on insured populations are in their infancy. In this webcast, presenters will provide insights into how the life insured population is faring during COVID-19 by discussing the findings from two recent SOA research initiatives. LIMRA, RGA Reinsurance, the Society of Actuaries and TAI have collaborated on an effort to analyze the impact of COVID-19 on the individual life insurance industry’s mortality experience. Additionally, the SOA has surveyed insurers to gather a high-level view of U.S. Group Term Life Insurance mortality results during the COVID-19 pandemic and comparing them to pre-pandemic mortality levels.

Description: For actuaries interested in term life insurance, add this webcast to your calendar. Our panel of experts will discuss term life insurance from the following perspectives: Pricing Product development Reserving Risk management They will also discuss exploring data visualizations using Tableau.

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: SARS-CoV2 will impact our post-pandemic future. Morbidity more than mortality will impact the life and health business in the mid-term. But how does this temporary disruption in health care elicit long-tail implications on other common diseases and changes in lifestyles? Find out how mid-term pricing could be affected using one case scenario and also show how mental health will particularly shape the post-pandemic future (individually and societal), not only due to long COVID. Review the experience of the insured policies and discuss future ideas for COVID-19 research at the Society of Actuaries Research Institute. Consider recent causes of death studies, as well as reported claims analyses to help expedite the analysis of recent experience. Join us where experts from both the medical and actuarial disciplines join forces to discuss this important topic.

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: Discuss population mortality improvement trends in the U.S. This will include analysis of cause of death data and trends in mortality pre-pandemic and during the pandemic. We will also discuss ways to think about translating population mortality improvement to an insured population.Learning outcomes includea better understanding of the drivers of recent mortality improvement and insights on how to create a company view on mortality improvement.

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.