Description: Investment Correspondent's report for the Opening session of the 2017 Annual Meeting & Exhibit in Boston, MA.

Description: In this article, we discuss the future of wearable technology in life insurance. Evidence from recent research shows that low levels of physical activity, as measured by steps per day indicate much higher mortality risk while higher levels of activity correspond with lower risk. The article shares insights of how insurers can use wearables to innovate by improving the customer journey, expanding insurability, engaging customers, promoting healthy lifestyles and improving risk assessment. Lastly, we discuss the challenges and considerations when using new data and technology to ensure success.

Description: Technology has streamlined countless processes in our daily lives, and insurance is no stranger to this transformation. Technology can make insurance simpler and more personal for consumers, and can enable actuaries to better analyze unstructured data, make good decisions, create new products, and find channels to enhance profitability, provided they can tame the flood of information pouring in from across the digital ecosystem.

Description: A look at the near future and far future of various elements of Actuarial Models as defined through ASOP 51. What is driving the complexity for inputs, calculations, and outputs. Howe will actuaries handle these challenge?

Description: This article is a brief overview of what digital health is, how it is regulated, and who some of the big unicorns are.

Description: When it comes to record linkage, the challenge is bringing together the right information from several sources. Here's how to make things match up.

Description: This article provides information on how to navigate the Internet's World Wide Web and tap into resources of interest to actuaries.

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 following case study walks through the steps of a predictive modeling exercise to illustrate one way analytics can streamline the underwriting paradigm.