Description: Mortality improvement for the U.S. general population has stagnated in recent years and then further deteriorated with the COVID-19 pandemic. However, mortality improvement by socioeconomic factors such as education and income has varied widely during this time period. Explore with us cause-of-death mortality rate trends as well as overall mortality improvement trends by different socioeconomic factors. Join a discussion on approaches that companies can take to proxy the insured population by applying socioeconomic factors to the general population with the goal of better understanding future mortality trends for the insured population.

Description: Cardiovascular disease (CVD) remains the leading cause of death among older adults in the United States. While genetics play a foundational role in establishing risk, disease progression is heavily shaped by lifestyle behaviors, environmental exposures, and social determinants of health. This Webcast will summarize key insights from an expert panel discussion on the evolving landscape of cardiovascular mortality at older ages.

Description: "This session will explore the critical challenges and solutions surrounding algorithmic fairness in the life insurance industry. The presenters will delve into the fundamental mechanisms of model bias, examining how predictive algorithms can yield outcomes that systematically discriminate against certain groups through flawed machine learning processes, erroneous assumptions, or biased data. Participants will gain insights into the various manifestations of bias in insurance models and understand their profound implications for both consumers and insurers. Real-world case studies and examples from the insurance industry will illustrate these concepts, while a discussion of recent regulatory developments will provide context for compliance requirements. This session is essential for actuaries, data scientists, and insurance professionals committed to developing and maintaining ethical, unbiased predictive models."

Description: Deaths due to non-medical causes such as drug overdoses, alcohol-related deaths, homicides, suicides and accidents are the leading cause of death for those under the age of 50 in the U.S. and is the fourth leading cause of death (after cardiovascular, cancer and COVID-19) for all ages combined in 2021. Take a deep dive with us into the mortality trends for non-medical causes of death and the impact these deaths have on different types of life insurance, including simplified issued, fully underwritten and group.

Description: Mortality improvement assumptions have typically been focused on all-cause mortality improvement. However, as evidenced in recent years, the cause of death has a large impact on mortality improvement. Join our panel of experts as they discuss mortality improvement through the lens of different causes of death. This discussion will include a review of the historical cause specific mortality improvement trends seen in the U.S. population and how this relates to the insured population. The panelists will then discuss how to use these trends to inform future mortality improvement assumptions. Key learning objectives include: - Identifying the trends in mortality improvement for select causes of death - Understanding how to adapt these for an insured population - Applying these learnings to mortality improvement assumptions

Description: This session will explore the mortality implications of reaching new markets, leveraging unique analysis that directly compares the mortality experience of the general populations and insured populations. Experts will explore how the industry can responsibility reduce the insurance gap, effectively employ digital data to assess new markets, and tackle the challenge with eyes wide open. At the conclusion of the session, attendees will be able to: •Understand differences in mortality experience between various populations – general, insured and uninsured •Articulate the challenges the industry may face in closing the insurance gap •Appreciate the role digital evidence can play in managing and accessing new marketing segments

Description: In discussing the contemporary reactions to this regulation, as well as how EU-based insurance firms adapted to the shift, this segment will invite us to question our assumptions on the role of gender-based pricing in the future of the industry. In the latter half of the presentation, we will delve into the challenges faced by LGBTQ+ individuals when accessing life, health, and auto insurance.

Description: Mortality Improvement is fundamental to setting your mortality assumptions. Creating your own Mortality Improvement assumption may seem like a Herculean task. The truth is creating a mortality improvement assumption with tools provided by the SOA, or the Continuous Mortality Investigation (CMI) make the process easy. Leaving you with the Herculean task of deciding if the assumption you created fits your product. Expect to learn about the CMI tool and the SOA's Mortality Improvement Model (MIM) tool, how you might get data to use in those tools, and what assumptions you need to make outside of data like what will the MI be in 20 or 30 years? Whether it is the general population, a segment of the general population, or certain causes of death, you will get very different answers.