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

Description: Feature article discussing model monitoring

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: Editorial for the December 2019 print edition of Predictive Analytics & Futurism newsletter describing the large number of informational resources available to PAF Section members.

Description: The author presents autoencoders in a clear manner and then goes on to show an intriguing application where an autoencoder can alert us to events out of the ordinary.

Description: The author reviews a book the debunks some of the hype we read about using quantity at the expense of quality. She also points out some unrealistic outcomes when data scientists lack business knowledge.

Description: This article describes the history and in some respects, the future of Big Data, and the tools we can use to handle it for PM and for machine learning. One such tool is Vowpal Wabbit, which sounds like something from a Bugs Bunny and Elmer Fudd cartoon (“Dwat that wabbit”), but it really is a popular approach to process a dataset of any size, as there is no need to load all the data into memory. Big data is forcing us to enhance many of our tools. So is the increased actuarial usage of stochastic-in-stochastic analyses (nested stochastic processes), which can result in unacceptably long program run times. Many of our popular computer languages are not inherently well suited for parallel computations.

Description: Contrary to what you might infer from the article title, the author provides counterpoint from some data science skeptics and suggests Big Data sometimes leads to sloppy analysis.

Description: Feature article discussing futurism and a study that contains in-depth descriptions of the Delphi and TIA methods; listings of the rationales and thought processes, the plausible future developments that could influence the values of these four economic variables and the resulting “fan of possibilities” for the values of these variables

Description: Reflection on three years on the PAF section council and where we're headed next.