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

Description: The article focuses on the use of predictive analytics in the development of experience studies, pros and cons of using predictive analytics versus traditional techniques, and the implications for setting assumptions and improving profitability.

Description: The editorial explores opportunities for the actuarial profession that can be achieved through innovation.

Description: Actuaries can serve an important role by exploring modeling and data analysis techniques to discover predictive patterns and relationships.

Description: Highlights some interesting facts about the quantity pi and about the properties of circles, taken from a recent exhibit of the scientific discoveries from ancient India.

Description: Big data and machine learning have been making headlines across industries everywhere, how will it impact the world of actuarial science?

Description: A discussion on supervised learning--the class of machine learning where a model is trained to produce a specific result for a given input.

Description: Actuaries have the opportunity to transform to a new role that utilizes predictive analytics and new data sources such as epigenetics, to better humankind.

Description: This article discussed the NEAT family of neural network algorithms. NEAT automatically determines the number of hidden neurons, as well as their structure. Additionally HyperNEAT can scale to very large problem domains.

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.