Description: The Society of Actuaries’ Committee on Finance Research is pleased to make available a research report that develops a framework for applying deep learning and reinforcement learning techniques to optimal dynamic strategic asset allocation for Liability Driven Investment (LDI).

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

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: This report describes the results of the latest intercompany study of mortality experience under Structured Settlement annuities.

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

Description: This research report introduces Delta Boosting as a new member of the boosting family.

Description: This report concerns optimal new business written premium mix at the firm and state levels under varying competitive conditions.

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