Description: This article discusses an upcoming SOA/CAS sponsored project regarding the Modeling of Economic Series Coordinated with Interest Rate Scenarios.

Description: The author notes: ‘as actuaries familiar with computers are thoroughly aware, the Halo notation the century-old life contingencies system we all learned as students has to be “linearized” strung out in a straight line for computer programming.’ This article describes a linearized notation that the author has used successfully for several years, for programming use only.

Description: 2016 marks the 60th anniversary of the Canadian Reinsurance Conference. This one day industry meeting hosting delegates from North America and beyond will be held in Toronto on April 13, 2016 under the theme "ReDefining Leadership".

Description: Interest in blockchain is high among insurers and reinsurers. While it’s not universally useful the technology does merit continued closer investigation.

Description: This article looks at an extensive integrated collection of financial mathematical modeling packages available in R, a language and environment for statistical computing.

Description: The purpose of this article is to provide an overview of soft computing applications in actuarial science. Soft computing refers to modes of computing in which precision is traded for tractability, robustness and ease of implementation.

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

Description: A look into how machine learning models implement classification and regression at a deeper level. Covers topics such as multi-regression, softmax, and ROC charts.

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.