Description: The presenters will dig into the little rider that most actuaries don't spend much time thinking about. A regulator, a direct writer and a consultant will discuss their thoughts on this rider and point out areas where actuaries should focus before deeming it insignificant. Topics will include the current study underway to update the industry experience study (most recently done in 1952), underwriting considerations, interactions with other riders, benefit designs, unique issues on UL policies, tax implications and reserving considerations

Description: The presenters will explore the current state of the North American mortality baseline and long-term improvement assumptions and determine what we can learn from the UK's approach. They will share research done by the Society of Actuaries and other organizations to describe how to build a better model, plus show the impact socio-economics and other factors have on longevity expectations. The presenters will offer suggestions for how U.S. and Canadian pension plan and insurance actuaries--and the industry itself--can best use this research to develop a better model for the risk management of pension plans and group annuities

Description: This report details the method taken to develop the aggregate databases 2000-2016 Long-Term Care Intercompany Experience Study. It contains definitions for each of the data elements in these databases. It should serve as a user guide for anyone working with the aggregated databases.

Description: 2009 - 2016 ILEC Mortality Report Appendices

Description: This report is a technical paper on a Predictive Analytics Framework and Reusable Workflow for Experience Analysis in actuarial studies. It covers data analysis, machine learning models, methodologies, and model interpretation techniques.

Description: This report provides a resource guide for asset-liability management practitioners, including methodology reviews, a survey of ALM practices, and guidance for applying ALM questions to real-world situations.

Description: This is the 2010 SOA Committee on Life Insurance Company Expenses request for data expense study worksheet for universal life

Description: We highlight a new approach leveraging predictive analytics to identify high risk and rising risk opioid users for more effective screening and follow-up care.

Description: Actuaries can empower their understanding of policyholder behavior with third party data. Modeling policyholder behavior should start from developing knowledge of who they are, instead of actuaries assuming what a rational behavior should be.

Description: Summary of industry practices on assumption governance, trend, challenges, and opportunities.