Description: The Reinsurance Section, Product Development Section and the Committee on Life Insurance Research are pleased to present preliminary results from a company practice survey of individual life insurance accelerated underwriting. Performed by a Milliman team led by Al Klein and Karen Rudolph, the study provides perspectives from both direct life insurance companies and reinsurers. Among the areas addressed include the structure of accelerated underwriting programs, how programs are monitored, how accelerated underwritten business is performing relative to expectations and how companies are considering accelerated underwriting cohorts in the context of VM-20 assumption setting. The report recaps a presentation of the preliminary results from the 2019 Life and Annuity Symposium. The final results are expected to be available later in 2019.

Description: Supporting data file for Actuarial Weather Extremes: Rainfall Totals for Hurricane Dorian report.

Description: The Individual Life Experience Committee has completed their latest report on intercompany mortality experience by amount of insurance under standard individually underwritten issues. This includes study years 2009-2015.

Description: This report pulls together various findings on caregiving research from the 2017 Risks and Process in Retirement Survey as well as other SOA research.

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.

Description: Experience report for life insurance policies with face amounts of $1 million or higher.

Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.

Description: This report pulls together various findings on long-term care research from the 2017 Risks and Process in Retirement Survey as well as other SOA research.

Description: This report proposes a methodology to isolate crop yield improvement due to technological change and favorable and unfavorable weather.

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.