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: The author presents autoencoders in a clear manner and then goes on to show an intriguing application where an autoencoder can alert us to events out of the ordinary.

Description: To expand our understanding of the theory of behavioral economics and its application to life and health insurance policyholder and annuitant behavior, the Society of Actuaries' Committee on Knowledge Extension Research, Committee on Life Insurance Research and the Financial Reporting Section issued a call for papers, inviting actuaries, academics, economists, psychologists, sociologists, researchers and other professionals to explore this topic from a variety of perspectives.

Description: Contrary to what you might infer from the article title, the author provides counterpoint from some data science skeptics and suggests Big Data sometimes leads to sloppy analysis.

Description: How actuaries can become comfortable accessing, integrating and building complex data sets from big and broad sources of information to study the value of multidimensional drivers of change.

Description: Read the February 2020 issue of Predictive Analytics and Futurism published by the Predictive Analytics and Futurism Section. Newsletter provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

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: Much of the work performed by disability insurance actuaries depends on the availability of accurate and detailed data, which is not always as simple as it sounds. Explore a variety of data challenges faced by disability actuaries, along with potential solutions. Potential topics include finding relevant data, the impact of poor data on valuation work, the impact of new privacy rules, and the potential bias in the data used to develop predictive models.

Description: This report provides actuaries and other professionals working with risk, data and analytics or program evaluation in the health care space with considerations and frameworks related to the use of determinants of health (DOH) in data and actuarial work streams. Such frameworks can leverage new data sources to enrich health care data analysis to move beyond traditional data elements, such as age, gender, zip code or health diagnosis.

Description: Predictive analytics techniques help actuaries and their companies make better decisions in managing their business.