Description: Summary of what the section has accomplished over the past year.

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: The article gives a brief history of the development of the Delphi method, and describes the use of the Delphi method in studies by the Society of Actuaries over the past 25 years.

Description: Jeff Sagarin is one of the most well-known figures in the sports analytics world, with his sports ratings appearing in USA Today for over 30 years. Few may know that he started his career in the actuarial world, even passing three exams before his sports ratings took off. This article explores the parallels between the challenges of developing sports rating systems and the challenges that actuaries face every day.

Description: This paper describes techniques that can be used to access any specific piece of information in Wikipedia, such as medical information.

Description: This article describes how to model variable annuities using a GPU along with some of the stumbling blocks.

Description: Reviewing a text covering multiple statistical modeling topics: e.g., generalized linear models, decision trees, clustering, using the statistical language R.

Description: Looks at free and inexpensive resources for the novice in predictive analytics, covering the data analysis theory as well as the most commonly used languages/software used in the field.

Description: This actually is a copy of an appendix of a research paper sponsored by the SOA Committee on Finance Research. You can read the entire research paper: “Lapse Modeling for the Post-Level Period—a Practical Application of Predictive Modeling” at the SOA site https://www.soa.org/Research/Research-Projects/Finance-Investment/lapse-2015-modeling-post-level/#sthash.W9lERSls.dpbs, but you can read this valuable appendix copied here in this issue to see how to build a PM step-by-step using your data and the R programming language. We thank Richard Xu, Dihui Lai, Minyu Cao, Scott Rushing, and Tim Rozar for their excellent paper and the Society of Actuaries, for the permission to reprint this portion of the paper.

Description: An introduction to creating Shiny web applications, with sample code available to reproduce the interactive application displayed in screenshots in the article.