Description: A review of the Bridging the Gap Series: Application of Predictive Modeling in VA/FIA Risk Management at the Equity Based Guarantees Conference in Chicago.

Description: Read the March 2017 issue of Small Talk published by Smaller Insurance Company Section. Practical information on trends that impact sections and activities.

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

Description: We highlight a new approach leveraging predictive analytics to identify high risk and rising risk opioid users for more effective screening and follow-up care.

Description: Read the Sept. 2017 issue of Small Talk published by Smaller Insurance Company Section. Practical information on trends that impact sections and activities.

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: Although rate structures where low-cost cohorts subsidize high cost cohorts may be justified from a actuarial, marketing, or legal standpoint, the subsidization creates risks which must be understood and monitored. This article presents the concept of subsidization signature to measure and interpret the effects of rate subsidization, and to assess the sustainability of rating structures and the sensitivity of business mix assumptions.

Description: This article discussed the NEAT family of neural network algorithms. NEAT automatically determines the number of hidden neurons, as well as their structure. Additionally HyperNEAT can scale to very large problem domains.

Description: Chairperson's column for the July 2016 issue of Predictive Analytics & Futurism.

Description: A discussion on artificial intelligence.