Description: This article discusses techniques used to create risk scores to help determine appropriate primary care panel sizes for a provider organization.

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 how insurance companies are deploying insurance technologies.

Description: Why Actuaries Should Welcome Automation

Description: This article explains how to create more maintainable models using abstractions by relating it to option, machine learning and machine intelligence models.

Description: Each month in the media we learn of another set of jobs being automated into oblivion or replaced by disruptive technologies. We see taxi drivers replaced by Uber and Lyft now, and soon by self-driving cars. An Oxford University study of 702 occupations showed insurance underwriters in 698th place, with a 99% probability of computerization. They were safer for obsolescence by automation than only four occupations such as hand sewers and telemarketers.

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

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 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: The PA Symposium will be an immersive experience benefiting entry level actuaries through senior managers, and PA newbies through advanced practitioners.