Description: Editorial for the May 2019 issue of Predictive Analytics & Futurism newsletter.

Description: History of Big Data, and approaches to cope with it. The author suggests that actuaries have been using similar methods for a long time; but need to get up to speed on the newer terms and variations.

Description: Summary of the first annual predictive analytics (PA) symposium specifically targeted to help actuaries get into PA & to take it to the next level of expertise.

Description: Editorial Introduction to the issue.

Description: In An Introduction to Incremental Learning, by Qiang Wu and I describe how machine learning is a natural enhancement to predictive analytics through its many useful tools to derive meaning from a lot of otherwise unusable data such as handwriting. Again, there are formulas involved; but we have tried to keep them understandable to the actuary who isn’t already familiar with stochastic gradient descent, perceptrons, and principal component analysis. Incremental learning can help you refine the estimations you derive from more traditional actuarial methods.

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: Actuaries provide special subject matter expertise to question (or validate) the results of data analytics models. Other quants often cannot do this.

Description: Editorial for the December 2019 print edition of Predictive Analytics & Futurism newsletter describing the large number of informational resources available to PAF Section members.