Description: This project obtains ensemble simulations of surface atmospheric temperature over North America.

Description: Artificial intelligence (AI) and Machine Learning (ML) are accelerating us into the fourth industrial revolution. In the next few years technological change and innovation will be rapid. The implications of AI on the actuarial profession are real and game changing. This session will help health actuaries understand what to expect from AI, how to begin using AI, and how AI will dramatically enhance the actuarial profession in the near future.

Description: Read the February 2020 issue of Predictive Analytics and Futurism published by the Predictive Analytics and Futurism Section. Newsletter provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

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

Description: A description of the operation of an R package for experience studies. Premium patterns, lapse rates, and mortality rates can be calculated.

Description: Often actuarial practitioners are faced with working with data that is less than ideal. The data may be observed with gaps in it, a model may suggest variables that are observed at different frequencies, and sometimes predictive analytic results are very fragile to the inclusion or omission of just a few observations in the sample. Data, particularly big data, are often "messy" and something must be done about it. What is the actuary to do about these very practical matters? These types of questions are what this presentation is intended to address. Concerns on missing data, outliers, nonlinearity, mixed-frequency, cross-correlations are illustrated using real datasets in the Asia-Pacific countries. Some possible solutions to the messy data problems will be discussed.

Description: Modern actuarial work, being quite data intensive, provides many opportunities for actuaries to use the statistical skills that are part of their basic training. Furthermore, modern computing allows us to analyze vast quantities of data intensively, and each package will provide statistical 'answers' to any questions the actuary might ask of it.

Description: The CIA, CAS Institute (iCAS) and the Society of Actuaries (SOA) are joining forces once again to launch the Predictive Analytics Hack-A-Thon!

Description: Predictive analytics projects in the life insurance industry are oftentimes set up as research ideas leading to intangible or unusable results for the practicing actuary. What if you could change that? What if the research turned into development and practical use through leveraging valuable resources properly? Learn how to structure predictive analytics projects, and about the project team, so there will be actionable takeaways for the business unit. Specific areas of value for you include underwriting, experience studies, assumption-setting, and product development. Watch as presenters talk through real case studies on turning a predictive analytics project into workable solutions rather than a resource drain, an unclear goal, or a misunderstood business need, which are some of the pitfalls of a poorly planned project.