Description: "Risk adjustment is an important aspect of establishing appropriate capitation rates. When a set of services is carved out for specific management under a sub-capitation, establishing appropriate adjustments for varying levels of underlying risk is more complicated. Dive into analytical and operational challenges and resolutions as presenters share more about developing a risk adjustment model specific to the carve-out of behavioral health services through a real-life case study. You will further explore a definition of the use case, availability of historical data sets, selection of the modeling approach, learnings from the iterative modeling process, and the potential application of the results. After attending this session, you will be able to: Understand why a behavioral health specific-risk adjustment model has business value Understand the unique challenges related to developing risk adjustment on member and cost subsegments Understand the impact of trade-offs between model complexity and interpretability in the context of implementation Increase awareness of data nuances and requirements unique to this type of project Describe analytic techniques that can be investigated for use in projects of similar business objectives"

Description: Ways of closing the mortality protection gap, by leveraging some of the new technology, data and analytics to reduce the friction in the buying process.

Description: The artcle looks at the most important features necessary to conduct a meaningful quantitative analysis. The article also discusses how predictive analytics should be used as a tactic to anwer question and not an end in of itself.

Description: After a decade of traditional actuarial work in health care, David Sotelo was seeking a new kind of opportunity to make an impact. He found it at Collective Health, where he works with a team of actuaries and data scientists that use analytics to streamline health insurance.

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: As M2M are exponentially increasing, we will soon see reinventing of whole business models and customer relationships.

Description: To explore the main drivers of the growing force of Chinese Life Insurance Industry.

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

Description: Feature article discussing the usefulness of Lorenz and Lift curves.