Description: A new wave of life insurance buyers is finally here - but are we ready? In this article, Richard De Sousa shares proprietary research about the Millenial generation, its beliefs related to life insurance, and its preferences when it comes to learning about, purchasing, and engaging with life insurance products, advisors and companies. Also explored is the foundational role that technology and wellness play in driving the kind of experience that will attract millenial buyers. After reading this article, you will better understand the characteristics of this new generation as well as the innovative companies that are targeting them, and learn about different and novel ways to better engage with customers and enhance the value of your own products and services.

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: The world is changing at an increasing pace and is disrupting everything from how one orders goods and services to how they take a taxi or Uber. Increasingly, this disruption is affecting the work of actuaries. Moreover, actuaries are being asked to provide more value-added services. Not only is this requiring actuaries to leverage exponential technologies not traditionally used in the insurance industry, but it is also impacting the types of staffing and training models utilized by actuaries. With a broader trend to alternative workforce arrangements, such as the gig economy and crowdsourcing, how will actuaries transition to this new future of working? What are the different types of off-balance sheet workers? How can companies create a strategy to deal with the hybrid workforce that involves different types of workers, cross-country borders, and other changes? This session will outline how actuaries and actuarial functions can successfully prepare themselves for this change.

Description: This article explains the importance of centralizing modeling departments. It goes further and explains the importance of making all aspects of modeling reusable. It explains the consequences of decentralization.

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: Software is shaping a world in which there is more information to measure and more risk to manage. An increasing reliance on software as infrastructure of public and private enterprise will create demand for new forms of insurance products focused on systemic failure. Machine-originated risk will create a novel market and equally new challenges for quantifying, pricing, and pooling risk.