Description: Discover the impact of COVID-19 on member costs post diagnosis and the future of mortality in this Emerging Long Term COVID-19 Trends webcast. This webcast will be split up into Health and Life portions. During the Health portion of this webcasts, you will learn more about the impact on risk scores due to recent findings. Enjoy this discussion and further dive into the emerging COVID-19 trends that may affect how you conduct business practices. At the Life portion, the SOA Research Institute assembled a panel of mortality experts who will express opinions on the effects of the U.S. mortality rate for general, insured and pension populations in the short-term.

Description: In order for an organization to benefit from artificial intelligence/machine learning (AI/ML) models, it requires the involvement of different business areas. During this webcast, professionals from data analytics, audit and risk areas will address challenges and provide solutions for working together to develop, implement, use and risk manage AI/ML tools. Throughout the discussion, the presenters will discuss: • Defining and exploring the challenges and objectives between data scientists, domain experts and control functions • Risk management – model risks and other risks • End-to-end model validation • Model performance vs. interpretability/understandability trade-offs • What to audit – auditor’s challenge and solutions

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: As actuaries in health care, we spend most of our time focused on reviewing claims, enrollment and clinical data. That information is captured while patients are in health care facilities. Yet most people spend only a small fraction of their time in these facilities. This article explores what types of data are available to actuaries the provide a more holistic view of the member so that a members physical and emotional needs, the social determinants of health can be taken into consideration along with their clinical needs. Two uses cases are presented so actuaries can see how these types of analyses can be leveraged to improve clinical, operational, and financial performance of risk bearing health entities. Understanding the customer (member) not just the patient enables actuaries to provide new insights and values to our stakeholders across a wide range of business and risk applications.

Description: The Life Meeting, is the result of combining the Life & Annuity Symposium (LAS) and the Valuation Actuarial Symposium (ValAct). The Life Meeting will offer sessions specific to pricing and valuation as well as sessions on emerging issues relevant to both groups. These common themes include InsurTech, diversity, accounting change and the current economic environment.

Description: This year’s Life Meeting was unable to take place in person as planned in New York City. We are looking forward to the Life Meeting returning to New York City in 2024!

Description: An introductory article describing how Bayesian statistics has evolved over the past 20 years and why it offers the actuarial discipline powerful tools to better understand and manage risk. Compared with traditional (frequentist) and black-box (machine learning) approaches, Bayesian analysis provides explainable models focused on distributions of estimates instad of simply point estimates.

Description: Discover the key components of value-based care (VBC) contracts and their impact on provider credibility. Learn about benchmarks, measurement period results, and the unique challenges providers face in managing insurance risk. Gain insights into reducing costs and aligning financial incentives in the US healthcare market.

Description: An introductory article describing how Bayesian statistics has evolved over the past 20 years and why it offers the actuarial discipline powerful tools to better understand and manage risk. Compared with traditional (frequentist) and black-box (machine learning) approaches, Bayesian analysis provides explainable models focused on distributions of estimates instad of simply point estimates.

Description: We compare two predictive analytics methods - GLM and GBM in terms of predictiveness vs. interpretability.