Description: The author discusses the use of genetic algorithms as they apply to actuaries, specifically the application of characteristics and their potential to solve life insurance asset and liability management problems. He also highlights various ways genetic algorithms can be used to solve a variety of actuarial problems.

Description: A significant fraction of insurance risk is characterized by the tail of the claims distribution, where we have much less data to model probabilities accurately. Ignoring the tails can lead to underpricing of tail risk and mispricing. Estimation of the tails can be complex due to a bias-variance tradeoff--the further out we go into the tail the more accurately we can model the extreme tail (lower bias) but the less data we have (increased variance). The statistical tools of Extreme Value Theory can be leveraged to more accurately estimate both the incidence and the severity of extreme events given that they occur. using the Generalized Pareto Distribution.

Description: A description of Data Science best practice tools and how they can apply to general actuarial work.

Description: The article is about how current advancements in AI can both help and potentially replace actuaries. We focus on three types of AI as defined by Numenta.org: Classic AI, Machine Learning, and Machine Intelligence. We present how Machine Learning and Machine Intelligence can affect actuarial analysts and actuaries alike. We then show how Machine Intelligence can be used to help regulators possibly construct a system or model that dynamically learns the behavior of insurance companies to predict failing insurance companies.

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

Description: Given the limits of classical actuarial modeling and forecasting techniques, this newsletter contains articles discussing several ways to supplement your toolset.

Description: The author explains how he used judgmental forecasting techniques to develop a dynamic lapse assumption. He defines the techniques and provides readers with a step-by-step process.

Description: This article gives a brief overview of ways to extend clustering analysis beyond basic methods such a k-means

Description: Feature article providing a brief introduction to Cython.

Description: The Possible Role of Convolutional Neural Networks in Mortality Risk Protection