Description: This article introduces IT DevOps to actuaries and how it is applicable to them to improve their modeling efforts and make them more efficient.

Description: This session will explore the practical aspects of bringing models to production, maintenance and management through its entire lifespan. Topics covered will include: production considerations, versioning, documentation, peer review and monitoring the model over its lifespan.

Description: As any international traveler who has tried to plug in an electronic device knows, the human race is great at devising many different ways to accomplish the same task. Predictive modeling is no different. Data scientists can choose from a wide variety of languages to prepare data, fit models, and verify results. The Rosetta Stone, which showed writing composed in three languages side by side, was instrumental in translating unfamiliar Egyptian hieroglyphics into the more common Greek language. This presentation follows a similar approach by showing the same predictive model implemented in the following languages: R, Python, Spark, MatLab, and SAS. Participants will compare and contrast each of these languages and, by doing so, build a greater understanding of those languages less familiar to them.

Description: Briefly reviews the history of Information Technology, IT, in the life insurance business. It then talks about the emerging trends in IT management and the impact they likely will have on the work of the life insurance actuary.

Description: Feature article discussing how technology can speed up and improve the accuracy of the the underwriting process. The distinction between rules and guidelines is discussed.