Description: It comes as no surprise that there has been a great deal of activity by regulators in trying to understand the evolution of UW and the use of data. CO, WA, DC, CA, and on and on. But, where are we now? What is the latest activity? What are the technical issues that need to be considered? What testing protocols should carriers be preparing? How do you know what to look for with respect to fairness concerns? How do you prepare your company to test and if necessary defend your data practices? Join this panel discussion, where they will bring varying perspectives from some of the industry's leading voices on this topic.

Description: SOA predictive analytics certificate program provides strong theoretical background and practical, hands-on experience that can be applied to decision making

Description: This article discusses how to handle semisupervised data. This type of data might have a large number of observations, yet a small number of labels.

Description: You’ve built or updated a predictive model. Is it any good? How can you interpret and understand its predictions? How does it compare to alternative models? This session will look at traditional and non-traditional ways of validating predictive models, with examples from case studies.

Description: This article describes methodologies for detection and deterrence of Medicare fraud. It also describes the validation of PRIDIT for fraud detection in Medicare.

Description: Many life and health insurers are beginning to use Predictive Analytics (PA) for a variety of purposes. This article addresses the unique challenges and potential disruption PA brings to the risk manager, as well as the opportunities.

Description: Data needed to run the Hack-a-Thon that was held at the 2019 PAS.

Description: Highlights of two 2018 health events organized by the Colombian Association of Actuaries and sponsored by the Colombian Government. Seminar on Risk Adjustment and Predictive Modeling in Health. Seminar on Risk Management for the Health Insurers

Description: Collaborative filtering models drive recommendations provided by Netflix and Amazon. This article uses the same models to explore patients’ medical conditions.

Description: Defines Accelerated Underwriting programs as a transformational trend, and outlines a process for evaluating mortality implications of such programs.