Description: Note from the outgoing chairperson.

Description: This article summarizes the new research paper of "InsurTech: A Guide for the Actuarial Community" by Carrie Kelley and Kiki Wang. It serves as a quick read for our members to learn the latest development in the InsurTech space and explore the opportunities for actuarial practitioners

Description: Spark offers a way to get some dramatic speed and scalability advantages over the Map-reduce methodology whenever you are doing iterative data processing and particularly when you want interactive data analysis capability. Find out why “lazy execution” can be a desirable characteristic when dealing with big data.

Description: This is an Editorial describing the need for actuaries to upgrade skills or risk minimization from artificial intelligence.

Description: There is a growing amount of “off-balance sheet” talent in the US and Global workforce. This spans from consultants and contractors, to gig workers and the crowd (both curated crowd and open crowd). One such example is Uber and Lyft workers. Insurance companies and the Actuarial profession have started to experiment with platforms such as Kaggle and this will continue to grow and evolve. This article explores these new sources of talent for companies, the implications to the actuarial function, benefits and challenges of the evolving workforce.

Description: In 2007, members of the Forecasting & Futurism Section were joined by members of the Technology Section and the Marketing & Distribution Sections to conduct a Delphi study about possible developments in the life insurance industry. It was named it “Blue Ocean Strategies in Technology for Business Acquisition by the Life Insurance Industry.” The goal was to have a panel of experts—actuaries and other financial professionals from across the country—identify and debate possible new approaches to acquiring business by life insurers. Panelists were asked to answer questions about possible “Blue Ocean Strategies.” This article highlights the ideas that resulted from those discussions as well as survey results on the same subject.

Description: What do data, technology, offices, skills, and cultural perspectives all have in common? Significant transformation.