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

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: 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: As M2M are exponentially increasing, we will soon see reinventing of whole business models and customer relationships.

Description: Even the best algorithms are only effective if they are trained on appropriate data. This article discusses common pitfalls in creating a training data set.

Description: Interview with John Houston, Advanced Analytics and Predictive Modeling practice leader at Deloitte.

Description: Possible usage of tools that can automate time consuming processes, and lead to a different team structure and organization for predictive analytics team.

Description: The purpose of this paper is to define a predictive model, based on known system attributes, for assessing risk associated with information systems.