Description: The Survey of Emerging Risk has been successfully conducted in North America for 16 years, consistently providing reports that track risk managers' opinions on emerging topics transcending the current business cycle, with strategic plans extending over decades. Since 2022, the survey has been specifically introduced to the Asia-Pacific markets with local language support, aiming to gauge actuarial and risk management professionals' opinions on emerging risks in the Asian market.

Description: The Casualty Actuarial Society, the Society of Actuaries Research Institute, the Society of Actuaries Joint Risk Management, Reinsurance and Financial Reporting Sections are pleased to make available key findings from the 2022 Emerging Risks Survey, the sixteenth in the series. Conducted by Max J. Rudolph of Rudolph Financial Consulting LLC, the survey incorporated a set of Emerging Risks defined by the World Economic Forum as the basis for several of the questions. The survey also included questions related to current risk management topics.

Description: This report presents research into recent population mortality experience as it pertains to development of mortality improvement assumptions for measuring obligations of retirement programs in the United States.

Description: 2022 was a year of radical change for the annuity market as interest rates increased off historic lows. The rapid growth of RILA products stalled as FIA and MYGA products gained market share. The impacts of the higher rate environment are continuing to be realized in experience, inforce management, product design and more. Come explore the retail annuity market with a focus on the impacts of higher interest rates. Session materials will draw on experience studies, sales results, product changes, and more to examine how higher interest rates have changed the annuity market.

Description: As the medicine practice continues to evolve, join us for this webcast to receive up-to-date information about the incorporation of scientific advancements and emerging evidence into the field. The creation of innovative treatments and the focus on improving patient outcome can cause information and price shocks, which will be one of the covered topics. Expect to utilize this webcast as an introduction to precision medicine, which is a genetics-based approach to healthcare. Speakers will share their experiences in demonstrating cost-effectiveness and promoting reimbursement with this new approach.

Description: What are the recent trends in mortality? Should we expect different mortality experience in a post-COVID-19 world? Join us as we review the latest emerging trends in U.S. population mortality. By the end of this session, you will understand the impact of COVID-19 on future mortality experience. You will also understand other major causes of mortality and how they are trending.

Description: In this article, we introduce a novel machine learning-based model that analyzes and predicts policyholder behaviors at the individual policy level. Policyholder embedding representations are learned using a Recurrent Neural Network (RNN) that takes into account the sequence of historical transactions associated with a policy. Additionally, a Neural Network with a multi-head architecture is trained to predict the policyholder's next action based on the policyholder embedding and other policy attributes. The resulting model offers several advantages over traditional experience studies and assumption-setting methods, including the ability to set policy-level assumptions that improve reserve accuracy, predict multiple behaviors simultaneously while capturing the interrelationships between them, and generate policyholder embedding representations that are useful for segmentation.

Description: The partnership between the SOA Research Institute and LIMRA created Experience Studies Pro, a new, in-depth program of research and analysis.

Description: The article outlines the editorial vision of Risk Management and Insurance Review (RMIR), emphasizing the need for research that bridges theoretical innovation and real-world application in the evolving landscape of risk management and insurance. RMIR prioritizes methodologically sound work that contributes to conceptual development and offers actionable insights. The journal encourages interdisciplinary, globally diverse, and practically relevant submissions, including those addressing emerging themes like systemic catastrophe risk, behavioral interventions, algorithmic ethics, and the use of AI in insurance.

Description: CMS provides ACOs with monthly claims data for members, including their medical visits and ACO program eligibility. This data can be divided into Membership and Claims tables through the ETL process. However, when calculating PMPY at specific levels of detail using these tables, issues arise due to unrelated dimensions, leading to inaccurate and understated results. This article presents a solution to this problem by utilizing Tableau's data blending capabilities.