Description: This article explores a potential alternative to the more typical regression-based specification of risk adjustment models. We demonstrate a proof of concept that a nearest-neighbors approach may hold some promise in certain applications of health-based risk adjustment.

Description: Description of the vast variety of predictive analytics topics covered by the Forecasting & Futurism section and introduction to the July 2015 issue of the newsletter.

Description: The editor of the newsletter provides a running list of articles included in the issue highlighting such topics as the applicability genetic algorithms, the power of group dynamics, judgmental forecasting, improvement in mortality and complexity science.

Description: Provides details of the 2nd forecasting competition for the best model that predicts the Civilian Unemployment Rate 'UNRATE', measured on a monthly basis, from March-end 2012 through September-end 2012.

Description: This article is about research studies that use the Delphi technique. It describes what a Delphi study is and gives a thumbnail sketch of two Delphi studies the Society of Actuaries has sponsored in the past 10 years, as well as a recently initiated Delphi study.

Description: Fuzzy logic is form of multi-valued logic that allows the creation of fuzzy rules. This article introduces the "sets" package for the R programming language for fuzzy logic.

Description: Unstructured data is often synonymous with Big Data; and the term is used and misused a lot. Richard Xu and his colleague, Dihui Lai, dispel some of the confusion about Big Data in their article “Big Data In Life Insurance—Does It Exist? If So, How Should We Handle It?” They address some of the ways to deal with the mounting challenges of capacity and speed as data scales up rapidly in size. Hadoop was once just the name of a toy elephant; but there is nothing toy-like about how it has been employed to handle very large datasets. Five exabytes supposedly represents all the words ever spoken by human beings; but according to IBM, the new SKA telescope initiative will generate over an exabyte of data every day.1 How will we cope with big data? Read Richard and Dihui’s article for some hints.

Description: December 2016 edition of Predictive Analytics & Futurism

Description: In this article, we will overview some popular tree-based models and understand how such models may be applied to the insurance industry.

Description: In An Introduction to Incremental Learning, by Qiang Wu and I describe how machine learning is a natural enhancement to predictive analytics through its many useful tools to derive meaning from a lot of otherwise unusable data such as handwriting. Again, there are formulas involved; but we have tried to keep them understandable to the actuary who isn’t already familiar with stochastic gradient descent, perceptrons, and principal component analysis. Incremental learning can help you refine the estimations you derive from more traditional actuarial methods.