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: "A crucial importance in forecasting is to be able to distinguish cases when temporary slowdowns in health care utilization are followed by a “rebound” period of higher utilization. Come explore an analysis of a new mathematical model describing the return-of-care process. By means of simulation and case studies using the R programming language, the relationship between the visibility of these effects and the endogenous variance of the utilization time series is explored. After attending this session, you will be able to: Describe the parameters and mathematical form of the model Apply the model to real-world utilization data"

Description: This session will discuss essential theories and practical applications of deep learning for actuaries. Participants will gain insights on leveraging these cutting-edge techniques to enhance actuarial models and drive predictive accuracy.

Description: A non-technical review of two recent general insurance articles published in the SOA's North American Actuarial Journal. The articles reviewed analyze Pay-As-You-Drive Insurance and Usage-Based Insurance.

Description: We will first present a few very practical use cases of GenAI tools that could help the daily life of an actuary. Then we will demonstrate the power of these tools in coding (e.g. Cursor, but also ChatGPT) - improv style. Taking a suggestion from the audience - a publicly available dataset - we will demonstrate how you can ask questions to a large language model, which will write code and provide the insight you are looking for.

Description: The Casualty Actuarial Society, Canadian Institute of Actuaries, and the Society of Actuaries' Joint Risk Management Section and the Joint Risk Management Research Committee are pleased to make available a new report on the application of ERM. Authored by Bonnie-Jeanne MacDonald, Sim Segal, Michael Wolfson and Heidi Walsh, the report provides a novel demonstration on how ERM can be applied to serve the Canadian public by informing decision makers on the risks facing the current and future delivery of long-term care.

Description: Tree models have been found to provide a good fit to group long term disability recovery and mortality rates. This research paper provides an overview of tree models, and details how they have been used for developing these rates.

Description: A news release announcing details on the upcoming FSA evolution

Description: The aim of this research is to survey emerging data analytics techniques and discuss their evolution and growing use in the actuarial profession. Data analytics’ applications in life and non-life insurance will also be provided.

Description: The Society of Actuaries' Pension Section and Health Section Research teams originally commissioned Professor Thomas E. Getzen of Temple University to construct a resource model for the projection of long term healthcare cost trends. The Society of Actuaries continues to make annual updates to the model to ensure its usefulness and relevancy.