Description: The COVID-19 pandemic will have a lasting impression on all forms of life, annuity, and A&H insurance. Individual and group disability insurance are no exception. Examine how U.S. group and individual disability insurers have been impacted by the pandemic and how they are preparing for an uncertain future. Oliver Wyman will team up with experts from the insurance industry to discuss insights on the impact of COVID-19 on disability insurance, including results from Oliver Wyman’s 2022 industry survey. Learn about the past, current, and future expected impacts of COVID-19 on: - Claim experience (including mortality, incidence, recovery and SSDI offsets) - Reserving - Scenario testing - Insurer operations (e.g., claims adjudication, recertification) - Sales and persistency By attending this session, you will be able to: - Understand how disability insurers have been impacted by the pandemic across multiple facets. - Identify where and how U.S. disability insurance carriers are adapting to the new and evolving environment. - Discover how carriers see disability insurance evolving as the COVID-19 pandemic continues.

Description: In summer 2021, the SOA Research Institute’s Mortality and Longevity Strategic Research Program sponsored a webcast examining individual life and group life emerging mortality in a COVID-19 world. Since then, Delta and Omicron coronavirus variants have fueled waves of the virus in the U.S., boosting the total number of COVID-19 deaths since the beginning of the pandemic to near the 1 million mark. Hear an update and insights into how the life insured population is faring during COVID-19 by discussing the findings from two recent SOA Research Institute initiatives. LIMRA, Reinsurance Group of America (RGA), the Society of Actuaries (SOA) and TAI have collaborated to analyze the impact of COVID-19 on the individual life insurance industry’s mortality experience. Additionally, the SOA Research Institute has surveyed insurers to gather a high-level view of U.S. Group Term Life Insurance mortality results during the COVID-19 pandemic, comparing them to pre-pandemic mortality levels. The Group Term Life industry mortality results will be presented with monthly data through March 2022.

Description: This research will provide detailed insights into the risk factors that drive private pension plan mortality experience. The private pension plan mortality experience collected for this research will be aggregated, de-identified, and made available for further analysis. In addition, mortality tables based on this private pension plan experience will be developed for use in the valuation and risk management of private pension plans.

Description: Brief discussion on recent published experience studies and RFPs.

Description: ACA risk adjustment is intended to "bridge the gap" between allowed rates and actuarial rates. If risk adjustment methodology is not bridging that gap & becomes an additional input to pricing formulae, it is not serving its intended purpose.

Description: View the Actual and Expected Relative Mortality Ratios.

Description: The South African life insurance industry contains the largest life insurance market in Africa, it is highly sophisticated and highly regulated. In the years 2020 and2021, the industry suffered significant mortality losses due toCovid-19. What can we learn from this experience in South Africa?

Description: View the 2020 & 2021 Ratio of Actual to Expected Relative Mortality Ratios.

Description: Learn more about the predictive modeling that was applied to industry data for the lapse and mortality experience in the post-level term period. Novel approaches were taken to model the shock lapse, subsequent lapse, and mortality experience. Observe a demonstration of the Tableau tool, which was built to allow users to analyze data on their own.

Description: Regression to the mean (RTTM) is inflating your health care intervention evaluations if you are not carefully managing it's omnipresent and significant impact RTTM is the statistical phenomenon which arises when comparing sequential data points when an initial observation is extreme or an outlier, and states that with no other intervention, future observations will be closer to the average. Members who had high costs last year will, on average, have lower costs this year, even in the absence of any intervention or clinical program, simply by 'regressing' to the mean. This means that if your clinical programs are simply targeting members who had adverse medical experience last year, you’re targeting the wrong people. And if your savings methodologies are simply last year’s costs minus this year’s costs, the savings are inflated. By attending this session, you will be able to identify situations where RTTM will be a significant factor, how to eliminate it's impact when performing retrospective evaluations, how to identify prospects for clinical intervention with RTTM in mind, and more.