Description: Describes actuarial approaches used to quantify the benefit to employers of implementing financial wellness programs for their employees.

Description: The presenters will explore policyholder experience data for long-term products, risks of over-fitting data in developing behavioral models, and ways to mitigate these risks and develop a sustainable and coherent framework to translate complex policyholder behavior experience data to behavioral models using company- and industry-level data. At the conclusion of the session, attendees will be able to: - Identify key drivers of policyholder behavior for long-term product - Understand the risks of over-fitting data and a false sense of precision in developing behavioral mode - Understand techniques that can be used to mitigate these risk

Description: A concise overview of Generative Adversarial Networks.

Description: This session will review limited fluctuation credibility, and how to apply that approach to a GLM. Alternative credibility approaches through the lens of ASOP 25 will also be discussed.

Description: The aim of this project is to present proposals for Variable Uninsured Life Annuities—or “Value annuities.” The report and the accompanying models illustrate how Value annuities work.

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: Feature article describing how exponential technologies will affect the actuarial profession.

Description: A discussion on using the Cox Proportional Hazards Model in developing a predictive underwriting model that produces a mortality multiplier for each individual.

Description: Read the August 2020 issue of Predictive Analytics and Futurism published by the Predictive Analytics and Futurism Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Contrary to what you might infer from the article title, the author provides counterpoint from some data science skeptics and suggests Big Data sometimes leads to sloppy analysis.