Description: The COVID-19 pandemic helped accelerate many changes in the Health Care system that were already taking place. The major disruptions to the way providers operated was quite evident with shifting of focus away from elective services to create capacity for treating COVID-19. However, even before the pandemic, providers were adapting to changes in their environments.

Description: The CIA, CAS Institute (iCAS) and the Society of Actuaries (SOA) are joining forces once again to launch the Predictive Analytics Hack-A-Thon!

Description: Generally accepted accounting practices (GAAP) reporting frameworks are more involved than ever before. From disclosures, to assumption changes, to interest rate movements, uncovering the drivers of income emergence can prove hard to do, and even trickier to communicate. This session will revisit how the updated standards create layers of complexity and offer ways to side step these obstacles to generate useful earnings analysis by various drivers.

Description: This session will explore governance considerations for insurance carriers leveraging machine learning models. During the session, panelists will share insights on the evolving predictive model and AI regulatory landscape, as well as techniques for developing or enhancing AI governance frameworks that comply with emerging regulatory guidance.

Description: The Society of Actuaries released research in 2007, performed by Jim Toole, that develops a model for a U.S. individual life insurance company to consider its potential liability exposure as a result of a pandemic. Sponsored by the Mortality and Longevity Strategic Research Program Steering Committee, this paper updates several model assumptions including mortality in light of COVID-19.

Description: Actuaries historically modeled new launches in pharmaceuticals by anticipating the expected change to the market basket. This became more complicated with the recent launches of gene and cell therapies as they address rare diseases. Rare conditions have low total member volume to study and some do not currently have a diagnosis code to identify them within claims data. Addressing this modeling challenge has been growing more important in the recent years with the number of therapies launching. What has the health care industry, and more specifically health care, done to enhance modeling and how should this be altered for the future? Additionally, historic modeling has sometimes incorporated a level of direct medical treatment cost offsets where studies have shown lower treatment costs are achievable. Can gene and cell financial modeling include cost offsets as well? And if so, what are suggested precautions or limitations to this effort?

Description: Cover a variety of topics centered around the unsupervised learning technique called 'clustering'. The presenters will take you through a wide array of topics that range from 'What is Clustering?' to 'How can I use this technique to solve problems I didn't even know existed?' In the health care industry, everyone is looking for an edge in reducing total spend-cluster analysis finds the unambiguous in an ambiguous framework of results.

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: This is a study to perform a mortality analysis of the 1898-1902 birth cohort.

Description: This e-course describes social insurance programs, their operation and the current issues they are facing.