Description: Private LTC insurers are paving the way for value-based care through working to implement care management programs that improve the lives of their policyholders before and during a claim. However, measuring the effectiveness of these new programs is a challenging task. In this article, we will explore powerful tools that can enhance traditional effectiveness studies and address some of their existing weaknesses.

Description: Increasing technology is available to create and disseminate educational resources worldwide. In response, this article advocates creation of open educational resources (OERs) that will benefit the actuarial profession with both recruitment and retention of members. Specifically, we describe OER contributions made at the University of Wisconsin-Madison and more recently through the ASTIN Academy, a working group of ASTIN, the non-life section of the International Actuarial Association. We advocate pushing boundaries and creating new ways of teaching effectively for the future. The innovative use of technology and open-source materials is a way to foster diversity, equity, and inclusion in the actuarial profession.

Description: Highlights the key takeaways from the 2021 published SOA PLT study on lapse and mortality experience of US term plans in the post level term period. This article explains the new insights in the latest study including a comparison of PLT experience between Jump to ART and Graded structures. The important variables driving PLT experience and the relationship between lapse and mortality experience are also discussed.

Description: A look back over 20 years to see how product topics of the day have changed and remained the same.

Description: The paper demonstrates that the most popular rationalization for evolving glide paths is flawed and should be discarded. The paper also demonstrates that glide paths should generally evolve for investors that endeavor to optimize outcomes and reevaluate their portfolios regularly.

Description: The article provides a high-level, non-technical, introduction to artificial neural networks (ANNs) and deep learning with an application to risk management. The method relies on typical ANN components such as nodes, activation functions, and optimization through gradient descent.

Description: This is a notice is a call of papers reflecting actuarial and insurance related themes.

Description: Mortality data and results for care home residents in England and Wales. Looking at numbers of death may indicate that there are fewer rate, but diving deep into various sub segments and looking at death rates, tells a different story.

Description: The article contains a description of the Emerging Topics Community. The focus of the article is what is a community, what makes the Emerging Topics Community special, and benefits of the Community. Included after the discussion on the community are ways to get involved and be a part of the community.

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.