Description: A data format for mortality tables along with applications.

Description: This is the user guide for the forecasting tool for the project Modeling and Forecasting Cause-of-Death Mortality by Socioeconomic Factors.

Description: Feature article describing what author thinks it will take for a life insurance company to be successful in the year 2020.

Description: Article presents issues for postretirement medical on models, data and the frail elderly. From Health Section News, December 2000, Issue No. 39.

Description: The American Academy of Actuaries and the Society of Actuaries have joined resources to maintain this Economic Scenario Generators Excel Workbook tool for use in regulatory reserve and capital calculations. Please see the SOA website research pages for further information on this tool and how to use it.

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: 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: Guidance and a model for actuaries to use when performing their professional services related to Medicaid (Title XIX) and Children’s Health Insurance Program (CHIP or Title XXI) managed care capitation rate setting.