Description: A closer look at family tier factor rating assumptions, and how well they reflect actual claim cost data.

Description: A study of disability experience examines cost burden and degree of disability, and how these measures vary across different subpopulations.

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: Review of a research project, co-sponsored by the SOA, which examined 83 organizations and over 150 programs that measure the quality and efficiency of hospitals and physicians.

Description: Charles Cadman and his team may be new to Kaggle’s data science challenges, but that didn’t stop them from achieving a top-ten finish.

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: Hear from Michael Xiao about how actuaries are combining business knowledge and data science skills to excel in Kaggle competitions.