Description: The article summarizes some of the key changes in modeling, assumptions, underwriting, and design for long term care combo products over the past 30+ years. The objective is to inspire an innovative spirit that adapts to changing market needs, for example, dealing with long COVID

Description: The direct and indirect effects of the pandemic have impacted many actuaries’ work since the spring of 2020. This article addresses three considerations actuaries should account for when using risk evaluation models which are focused on projecting remote, highly unlikely losses: model effectiveness, asset risk, and insurance (mortality and mortality) risk.

Description: In the wake of the pandemic, much of the insurance industry is now endeavoring to find sustainable, longer-term solutions among many forced innovations – and to ensure that temporary adaptations add value beyond mere change.

Description: Python has become the fastest-growing major programming language in the world. It has surged in popularity over the last decade, following the development of its industry-leading capabilities in data science, machine learning and artificial intelligence, and it is now one of the most globally popular and widely used languages. In this article, I discuss some of the reasons for its popularity and explain why many actuaries and insurers have started using Python.

Description: This article identifies why insurance innovations take so much effort and digs deeper into the underlying causes. It shows and explains the importance of taking an efficient, tactical, and intentional approach when innovating to avoid over-building and over-investing.

Description: Mental health, suppoting policyholders

Description: Article reviews the data a year into the unwinding of continuous coverage provisions in Medicaid, the impact on enrollment counts, how capitation rates have been adjusted, and compares those results to what has been modeled with the SOA Mediciad Unwinding model.

Description: The article describes the nature of actuarial research conducted at the Goldenson Center at the University of Connecticut. One of the research projects to create a National Retirement Sustainability Index is analyzed in detail. It demonstrates how the work we do at the Goldenson Center is both an art and a science while satisfying the following research criteria we adhere to at the Goldenson Center:  >The problem has to come from industry  >The solution has to add value to what is currently done in practice  >The solution has to be implementable

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: Regression to the mean is a phenomenon that arises when comparing sequential data points. It states that when an initial observation is extreme or an outlier, future observations will be closer to the average. Health care actuaries need to understand and be able to mitigate the effects of regression to the mean to avoid misapplying predictive models or misstating measurements of historical effects.