Description: A divisive confrontation over health care pricing is almost inevitable over the next few years. What will ultimately happen is a political decision, not an actuarial one—but it will have major consequences for the trend in health care costs and the divergence between public and private insurance premiums.

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

Description: This report reviews estimates of 2017 U.S. population mortality experience from the National Center for Health Statistics’ National Vital Statistics System.

Description: This report covers credit risk loss experience during the period 2003 through 2015 on non-Rule 144A private placement securities (and, with limited exceptions, some specific types of Rule 144A bonds) held by participating companies of the life insurance industry.

Description: This literature review provides insights on emerging technologies that interact with the actuarial profession within the space of microinsurance for the purpose of establishing a frame of reference for actuaries to use in their work. Furthermore, it intends to spark readers’ interest in, and create a vision for, how microinsurance and its associated technologies may impact the actuarial industry in the future.

Description: This report compares the CIA pricing method for estimating group annuity closeout pricing to methods used in the US.

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.

Description: The Modeling Section, Predictive Analytics and Futurism Section, Committee on Life Insurance Research, Product Development Section and Reinsurance Section releases a report that can help to educate actuaries on how best to implement predictive modeling into relevant areas of actuarial practice. This report includes a review of existing literature and current industry practices, as well as a comprehensive set of considerations for predictive modeling in insurance applications.

Description: The aim of this research is to survey emerging data analytics techniques and discuss their evolution and growing use in the actuarial profession. Data analytics’ applications in life and non-life insurance will also be provided.

Description: Fact sheet about the Employer Withdrawal Activity Overview: U.S. Multiemployer Pension Plans report.