Description: The author recounts his experience as a keynote speaker at the Actuarial Research Conference and provides advice to young actuaries to present complex subjects in an understandable manner.

Description: Each month in the media we learn of another set of jobs being automated into oblivion or replaced by disruptive technologies. We see taxi drivers replaced by Uber and Lyft now, and soon by self-driving cars. An Oxford University study of 702 occupations showed insurance underwriters in 698th place, with a 99% probability of computerization. They were safer for obsolescence by automation than only four occupations such as hand sewers and telemarketers.

Description: Editorial Introduction to the issue.

Description: The editor of the newsletter provides a running list of articles included in the issue highlighting such topics as the applicability genetic algorithms, the power of group dynamics, judgmental forecasting, improvement in mortality and complexity science.

Description: Second article in a series on effective writing: focuses on writing for Chinese readers if English; and on writing for English readers if Chinese.

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: Neural Networks are no longer limited to classification and regression solutions to numeric problems. CNNs add the ability to classify images, and GANs can create new images. Learn how these capabilities can provide competitive advantages to early adopters, how they work, and how to implement them.

Description: Actuaries of the future have to embrace the ideas and technologies that lie ahead.

Description: Provides a simplified explanation of the modeling and statistical terms currently in use by the profession, and provides a list of publications worth reading in regards to complexity science plus a list of free software.

Description: This abstract describes a presentation that introduces new methods such as Experimental Mathematics, Genetic Algorithms, Predictive Modeling, Deterministic Chaos, Fractal Geometry, Behavioral Economics, Cellular Automata and other topics in Complexity Sciences.