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: This addresses the changing role for property-casualty actuaries as companies are looking toward actuaries to play a bigger role in moving the business forward.

Description: Read the Society of Actuaries' latest update about how health care executives view the future of predictive analytics in the health care industry.

Description: This practical session would provide a technical overview about GLM techniques and describe how GLM can be applied as a business tool in solving business problems in life insurance. The session would also focus on recent real-world case-studies across different functional areas like pricing, fraud detection, underwriting and product development.

Description: This is a case study session where the speakers will describe a project where a major health system converted its provider distinct reimbursement (i.e., separate physician IPA and hospital capitation) to an integrated reimbursement involving global capitation. The session will discuss the strategic issues considered by the parties and how they evaluated them in their decision process. This session will provide attendees an example of how to approach this type of decision.

Description: LTC insurers can proactively identify policyholders more likely to go on claim in the near future, and methods to potentially delay or prevent claims, benefiting company and customer.

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