Description: An autobiographical journey from actuarial student to data scientist.

Description: A discussion on the starting point of building a predictive model.

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: 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: The Delphi Method is discussed in detail. The method attempts to filter out the consensus bias that can result from societal forces by employing a technique whereby an anonymous collection of opinions is used, supplemented by feedback loops that can be used to influence outcomes.

Description: A discussion on how the look of charts and graphs can affect comprehension of data.

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.