Description: In the insurance industry, machine learning models are increasingly used to make decisions that affect people's lives. In order to ensure that models are fair, they should be audited for bias. There are no hard and fast rules for bias audit; metrics that can be used to evaluate fairness vary depending on the context in which the model is deployed. In this session, we present a flexible framework that highlights key considerations in bias evaluation that can be adjusted to suit your process. In this session, we will learn about different metrics to assess fairness, discuss open source tools that can be used for bias audit, and walk through a case study.

Description: A compilation of reader responses is presented to a real life situation posed involving a management, leadership, or other business decision. This issue’s case study involved a very new actuarial manager trying to deal with a disruptive employee.

Description: July 2019 issue of Small Talk by the Smaller Insurance Company Section. Practical information for actuaries, trends that impact section, and section activities.

Description: A list of the lessons the author learned through his own failure(s). The intent is to help readers avoid making the same mistakes and reflect on how far they've come.

Description: The August/September 2014 edition of The Actuary magazine—the Society of Actuaries’ flagship publication.

Description: Summary of recent SOA-sponsored research on Enterprise Risk Management practices as applied to health insurers, self-insured plans, and health finance professionals.

Description: Discusses the peer-review process as it relates to articles submitted for TAXING TIMES.

Description: The February/March 2016 edition of The Actuary magazine—the Society of Actuaries’ flagship publication.

Description: Email blast process and email preference setting description.

Description: In this article, we aim to outline the advantages of smaller programs and gather opinions on the challenges these programs face in their efforts to emphasize these strengths. For our purposes, we define small actuarial programs as those with a relatively low student enrollment count. The following are three key advantages of small programs, which are similar to those of small colleges:(a) Enhanced benefits from small class size; (b) Adaptable curriculum; (c) Increased opportunities for each student. A variety of similar other issues are also discussed with recommendations, challenges, and invitations for further dialogue.