Description: Andy Rallis delivers his speech at the presidential luncheon of the SOA 2019 SOA Annual Meeting & Exhibit in Toronto.

Description: Leader interview.

Description: This article is about how times are changing and we must adapt and keep up as individuals, professionals, and companies

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: This article identifies four root causes of poor performance and four remedies to address them that every leader should know.

Description: A personal account of how humor in the workplace improved productivity.

Description: The true value of any leader is measured by how much they are able to accomplish through the work of their team. Actuaries in leadership roles are no different. But, to get the most out of your teams, leaders must first focus on building a high-performance culture. One that rewards measurable success and challenges everyone to reach farther all the time. There is no easy path to building a high-performance culture, but the benefits of a leader’s efforts will pay substantial dividends for the team, the leader, and the company. This series of articles is intended to educate leaders of large and small groups on how to build a high-performance culture and achieve outstanding results.

Description: Predictive modeling is a powerful toolset for assumption setting (mortality, lapse, etc.). The multivariate approach has its advantages in handling high-dimensional data, address correlations, and statistical significance. However, building insurance assumptions is far more than a simple modeling practice. One must take care to address how the model is applied and its business implications. This session will share the learnings from multiple projects.

Description: Notes on the IAA meeting that took place in D.C. in May

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 management hiring someone to make changes, then ignoring all suggestions.