Description: This article describes the history and in some respects, the future of Big Data, and the tools we can use to handle it for PM and for machine learning. One such tool is Vowpal Wabbit, which sounds like something from a Bugs Bunny and Elmer Fudd cartoon (“Dwat that wabbit”), but it really is a popular approach to process a dataset of any size, as there is no need to load all the data into memory. Big data is forcing us to enhance many of our tools. So is the increased actuarial usage of stochastic-in-stochastic analyses (nested stochastic processes), which can result in unacceptably long program run times. Many of our popular computer languages are not inherently well suited for parallel computations.

Description: The article introduces the concept of overfitting in predictive modeling and illustrates how it hinders our ability to predict new data well.

Description: Feature article discussing the ways artificial intelligence will influence the actuarial field.

Description: A discussion on machine learning and how it can be used for forecasting.

Description: An introduction to creating Shiny web applications, with sample code available to reproduce the interactive application displayed in screenshots in the article.

Description: Overview of regularization and least angle regression approaches.

Description: This paper describes techniques that can be used to access any specific piece of information in Wikipedia, such as medical information.

Description: A discussion on using the Cox Proportional Hazards Model in developing a predictive underwriting model that produces a mortality multiplier for each individual.

Description: Feature article describing how exponential technologies will affect the actuarial profession.

Description: This is an Editorial describing the need for actuaries to upgrade skills or risk minimization from artificial intelligence.