Description: The post COVID-19 period exhibited a fast-changing capital market with higher interest rates, uncertain monetary policies, and revaluation of asset classes. At the same time, regulators introduced changes to reward better risk management, such as the scenario-based approach for reserving under Bermuda regulatory framework. For life reinsurers, while new opportunities arising from these changes, challenges also exist to be able to adjust reinsurance portfolios and ALM strategies appropriately. A holistic modeling framework can assist companies better position themselves in front of these challenges and other potential future unknowns. In particular, a well-designed stochastic and dynamic modeling framework enables the quantifications of such probabilities and potential impacts.

Description: This report is presented in the form of a Tableau dashboard and is the sixth public release from this report series and contains the results of an excess mortality analysis for the fourth quarter of 2021. Data from 30 companies representing approximately 69% of the industry’s face amount inforce were included in the analyses in this report. A total of 3.2 million death claims from individual life policies from 2015 through December 31, 2021 make up the basis of the analyses. The report also compares the experience under COVID-19 of the insured population versus the general population.

Description: At this session, experts will provide an overview of current statutory valuation issues pertaining to life and annuity products. The focus is on activities of the American Academy of Actuaries relative to principle-based approaches, but other matters will be covered, including the status of the NAIC valuation manual, life risk-based capital, developments at the NAIC affecting life insurance companies, and practice issues for appointed actuaries.

Description: Authored by a MIB Solutions team of Tom Rhodes, Stuart Klugman, Marianne Purushotham and Stacy Gill, the report summarizes the results of a study on the application and adoption of credibility theory within the life insurance and annuity industry. In addition to the report, numerical examples related to the application of credibility to company mortality and lapse data are provided in the four Excel files. This excel spreadsheet is a numerical example relating to the application of Credibility for mortality - Limited Fluctuation Method. Please see the SOA website research section for the full report on Credibity Theory Practices.

Description: Human longevity is one of the great success stories of the past century, and there is growing consensus that there are further gains to come. What will these future gains look like, where will they come from and how likely are they to happen. Furthermore, how do we as actuaries deal with the uncertainty when trying to predict future long-term mortality improvements more than 20 years into the future. This is one of the most important assumptions on the balance sheet that insurers and reinsurers make, so it is important to have a strong perspective on it. Our presentation will give attendees a view into some of the core components of how to assess long-term mortality improvements by looking at the cyclical nature across different countries of life expectancy. It will also deep dive into the different drivers of life expectancy over the past cycle driven largely by improved diagnosis and treatment of cardiovascular disease (CVD) and cessation of smoking, which ended in about 2010. It will then discuss how population mortality improvement has slowed and plateaued in many major countries.

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.

Description: This report details the 2025 HMI and FMI scale recommendations for individual life insurance mortality valuation under AG38 and VM20 using insured population data.