Description: This video from Ben Keslowitz explains the concept of reinsurance, which is a financial arrangement where insurance companies transfer portions of their risk portfolios to other parties, known as reinsurers. This helps insurers manage large or catastrophic claims and optimize their risk components. The video also covers different types of reinsurance, such as proportional liability reinsurance, non-proportional reinsurance, and quota share coinsurance, each serving different purposes in risk management. Additionally, it discusses the reasons insurers might choose to reinsure their business, including liability risk mitigation, investment risk transfer, and entering new markets.

Description: A literature review was performed on mortality improvement, socioeconomic differences in mortality and their links to specific causes of death, and methods for analysis. It highlighted the fact that socioeconomic status (e.g., income and education) is closely linked to differences in mortality and that the longevity gap between socioeconomic groups is growing over time. It also informed the selection of key variables and the need to view mortality improvement as a complex interaction between specific causes of death.

Description: This report models and forecasts future mortality improvements in China, by geographical regions, as well as by causes of death. Deaths and population exposures data provided by the Chinese Center for Disease Control and Prevention was used for the period 2004–2019.

Description: Gain a high-level understanding on how long-duration targeted improvement (LDTI) impacts insurance products and earnings. Explore highlights on secondary impacts to companies due to additional complexity of LDTI, such as a need for a source of earnings analysis. Then dive into the details and hear an explanation on how earnings emergence differs for each type of life and annuity product impacted by LDTI. Finally, discuss the impact -to-earnings volatility under LDTI for each product type. Close the session by connecting how the investor story changes with all the impacts discussed during the session.You should walk away with a good understanding of LDTI earnings emergence, which is a topic that has very limited thought leadership available today.

Description: The session will highlight trends in recent industry mortality and lapse studies that have been conducted, including areas where individual companies typically have limited data. The sources of data feature SOA studies as well as other industry studies conducted by consultants and/or reinsurers. Gain an understanding of current drivers of mortality and lapse experience for life insurance evidenced in industry studies, and an understanding of available data to supplement experience in areas where you may have limited internal experience.

Description: This paper applies the research in Prospect Theory of Kahneman and Tversky to explain why sales of annuities lag sales of life insurance products. The author theorizes that life insurance is easier to sell because customers perceive themselves to be in the domain of losses, while potential annuity customers perceive themselves to be in the domain of gains. Kahneman and Tversky showed us that people are mostly risk averse in the domain of gains and risk seeking in the domain of losses. Purchase of an annuity or life product is a risky investment. Customers will find it easier to take the risk in the life insurance domain of losses than the annuity domain of gains. The author then proposes a hybrid life annuity product that might address both mortality and longevity risk in one product that would allow both products to be more competitive than stand-alone products.

Description: This report summarizes industry mortality experience for the period 2009 - 2016. This report is updated on a mostly annual basis and based on information aggregated from industry VM-51 submissions

Description: LIMRA, Reinsurance Group of America (RGA), the Society of Actuaries (SOA), and TAI have collaborated on an ongoing effort to analyze the impact of COVID-19 on the individual life insurance industry’s mortality experience and share the emerging results with the insurance industry and the public. The Individual Life COVID-19 Project Work Group (Work Group) was formed as a collaboration of LIMRA, RGA, the SOA, and TAI to design, implement, and create the study and to produce and distribute a variety of analyses. This report is the fifth public release from this collaboration and contains the results of a cause of death analysis focused on how the rates of death for various causes were impacted throughout the pandemic period through the first quarter of 2021.

Description: Behavioral economics research has shown that small details can have a large impact on how a person behaves. As life insurance continues its evolution into the digital domain, life insurers now have an almost infinite number of ways to tweak their product offering, positioning, and delivery to the end consumer. Behavioral science is becoming increasingly more important to optimize these product design decisions and improve outcomes for both insurers and their customers. Discover a brief overview of key behavioral economic concepts and dive into two SOA research projects that are exploring how behavioral economic techniques can be used in different parts of the life insurance value chain. First, you'll start before a policy is even sold, by exploring how behavioral economics, through techniques such as the messenger effect, can be used to increase consumers' comprehension of policies and life insurance's value. Second, you'll look at how underwriting question design can impact applicant behavior and lead to higher quality application data. At the conclusion, you'll enjoy having a better understanding of how behavioral economic techniques can be applied in a life insurance context.

Description: Discover a modernization journey within finance, actuarial investment and risk domains. Expect to learn about the world we are striving for - an event-based, self-service, automated environment that centers around a cloud-based data lake with proper data quality and governance and provides visual, on-demand solutions for reporting and analysis. We will educate the audience on the technology used to obtain this vision and the approach (including our team structures and project management ideologies) we have taken thus far to start moving there.