Description: Feature article discussing futurism and a study that contains in-depth descriptions of the Delphi and TIA methods; listings of the rationales and thought processes, the plausible future developments that could influence the values of these four economic variables and the resulting “fan of possibilities” for the values of these variables

Description: 2021 ImpACT Conference - Session 6B: A Courtroom Case: Data Democratization to Drive Analytics? 10.27.21 Recording

Description: Following her first 100 days as the CMS Administrator, Chiquita Brooks-LaSure released her six strategic pillars for the agency. The Center for Medicaid and CHIP Services (CMCS) followed these pillars and laid out their priorities for states under the Biden-Harris administration. With these priorities established, recent 1115 submissions from several large states, including California, Massachusetts and New Jersey, may give insight to how CMS will operationalize their vision under this program authority. This session will include presentation from state policy staff who have led recent 1115 waiver proposals.

Description: Learn more about the predictive modeling that was applied to industry data for the lapse and mortality experience in the post-level term period. Novel approaches were taken to model the shock lapse, subsequent lapse, and mortality experience. Observe a demonstration of the Tableau tool, which was built to allow users to analyze data on their own.

Description: Are Accelerated Underwriting (AU) programs performing as expected? As mortality experience will (hopefully) be slow to emerge, it is pivotal that we look at alternative methods of monitoring early performance. From random hold outs, to post-issue APS's, and post-issue prescription profiles, explore popular monitoring techniques and lessons learned so far. Focus on confusion matrices that provide an early indication of mortality slippage relative to fluid-based underwriting decisions. Finally, explore statistical methods to determine what constitutes credibility and identify opportunities to think about mortality slippage more robustly.

Description: Data is everywhere. Health care generates as much as 30% of the world’s data, and new technologies are changing how life insurers analyze consumer information. Actuaries are business-savvy problem solvers. They understand how to leverage the latest technologies and techniques to turn data into actionable insights and solutions for businesses and can communicate those findings to multiple audiences. SOA-credentialed actuaries use predictive analytics to inform organizational and business strategies, with efforts such as identifying chronic conditions in their early stage or determining stress levels through sweat patterns.

Description: Reflection on three years on the PAF section council and where we're headed next.

Description: An introduction of predictive modeling techniques that are applicable to insurance industry, including generalized linear model (GLM) and classification and regression tree model(CART). Other models such as data clustering, neural network, and support vector machine (SVM), are also briefly discussed.

Description: A discussion on using the Cox Proportional Hazards Model in developing a predictive underwriting model that produces a mortality multiplier for each individual.

Description: A discussion about how many models can address the over fitting issues caused by too many variables by regularization, variable selection is still meaningful.