Description: The SOA provides information about the actuarial career path in health care and predictive analytics. Throughout 2016, we will share more about actuaries who are tackling some of the industry's biggest challenges and hear from top employers in healthcare analytics.

Description: Third article in a series on how to use predictive analytics to improve the development of long-term care projection assumptions.

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: 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: 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: Career changes typically follow a major milestone—a promotion, a job offer, a new degree, maybe a cross-country move. For Patrick Getzen, exposure to some new perspectives ignited a shift.

Description: Carol McCall led three teams – predictive analytics, health economics and outcomes research, and personalized medicine. The “river running through them” was that they all leveraged data. Her predictive analytics team eventually built a broad portfolio of models with some of them having a significant impact on Humana’s top and bottom lines.

Description: Even the best algorithms are only effective if they are trained on appropriate data. This article discusses common pitfalls in creating a training data set.