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 discusses the use of parametric distributions to model health care cost.

Description: Third article in a series on how to use predictive analytics to improve the development of long-term care projection assumptions.

Description: The artcle looks at the most important features necessary to conduct a meaningful quantitative analysis. The article also discusses how predictive analytics should be used as a tactic to anwer question and not an end in of itself.

Description: A discussion on using the Cox Proportional Hazards Model in developing a predictive underwriting model that produces a mortality multiplier for each individual.

Description: A discussion about how many models can address the over fitting issues caused by too many variables by regularization, variable selection is still meaningful.

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

Description: This article discusses ethical issues that have arise with advancements in Data Science. Through examples of these issues address actuarial professionalism.

Description: Reflection on three years on the PAF section council and where we're headed next.

Description: The author presents autoencoders in a clear manner and then goes on to show an intriguing application where an autoencoder can alert us to events out of the ordinary.