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: 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.

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: The author discusses the two-part presentation on complexity science tools at the SOA Annual Meeting October 2010. He explains that presentations went back to basics with explanations about the difference between modeling tools used to employ deterministic methods for classical actuarial models.

Description: Introduction to the topics of the issue; and anecdote regarding the value classical versus newer techniques.

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 and issue introduction

Description: Discusses how 'insignificant' changes in assumptions can have very significant affects.

Description: The authors take a deeper look at the long-standing motto of the Society of Actuaries, from John Ruskin, “The work of science is to substitute facts for appearances and demonstrations for impressions.”

Description: This abstract describes a presentation that gives an in-depth look at genetic algorithms - what they are, why they are important for actuaries, when to use them, and how to create them.