Description: Given the ubiquity of judgmental forecasting, it is important to understand the potential biases inherent in human judgment—the traps that can snare us—and to learn methods and best practices to avoid them. The aim of this article is to help readers with these goals.

Description: An introduction of predictive modeling techniques that are applicable to insurance industry, including generalized linear model (GLM) and classification and regression tree model(CART). Other models such as data clustering, neural network, and support vector machine (SVM), are also briefly discussed.

Description: This article provides a brief introduction to forecasting methods that are potentially relevant to actuarial work.

Description: Feature article describing how exponential technologies will affect the actuarial profession.

Description: This article summarizes a method for measuring the credibility of a prediction from a logistic generalized linear model (GLM).

Description: The winner's curse, applied to Affordable Care Act plan pricing.

Description: This article sheds light on the various ways machine learning can uncover patterns within data to add unique value and insights to businesses.

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

Description: This paper explores how health care complexity challenges us to expand our repertoire of actuarial methods—and even recast our trend driver paradigm—in order to do our jobs better and maintain our credibility.

Description: This article goes through some basic data exploration techniques to show how different approaches look.