Description: This report examines historical U.S. motor vehicle accident mortality experience by age, gender, region, and other factors.

Description: This report illustrates employer group commercial health care costs and trends from 2013 – 2017.

Description: In this report, we will try to provide an in-depth review of current Machine Learning and Deep Learning models and will explain how those models works and their possible applications in the actuarial field. The recent studies and successes from the industry will also be discussed. We intend to bring more actuaries onboard about those technologies and start to think about how to bring them into our daily work.

Description: The popular press plays an important role in public perception regarding automated vehicles. In contrast to the excitement generated two to three years ago, we are now in a period of “reverse hype” with most articles focused on the slow pace of development and concerns regarding possible negative impacts on traffic congestion and growth of suburbs. To help describe current trends and highlight differences between the cars we see on the street today and driverless vehicles, this report relies on three market-related definitions; safe, self-driving and driverless.

Description: Report summarizing the results of the 2019 PBITT UL with Secondary Guarantees Survey.

Description: The Product Development Section, the Financial Reporting Section, the Modeling Section and the Committee on Life Insurance Research are pleased to present new research on modeling and forecasting cause-of-death mortality. Authored by a Milliman team led by Alexandre Boumezoued, the report develops a framework for forecasting cause specific death rates. Included also is a Cause of Deaths Forecasting Tool and a user guide for the tool.