Description: As technology changes the insurance landscape, it is essential that companies adapt quickly while staying focused on customer needs. This presentation will show how Agile and Design Thinking methodologies can help business and technology teams quickly test new ideas and optimize value delivery.

Description: Actuaries play pivotal roles in insurance companies, consulting firms, and throughout the industry. With the ongoing accounting and regulatory changes, process and system modernization, and the rapidly changing environment, actuaries frequently find themselves working in multidisciplinary projects with non-actuarial teams. In order to take on broader leadership roles, actuaries are often times expected to partner with and/or lead non-actuarial personnel. How can actuaries work most effectively with non-actuaries? A panel of industry leaders across different disciplines will share their perspectives on actuaries working with and building effective relationships with non-actuarial colleagues. The panelists will cover how actuaries add value in a non-actuarial world, what aspects actuaries can focus on to be more effective across disciplines, and incorporate success stories as well as lessons learned.

Description: James Glickman delivers his general session speech at the SOA 2019 SOA Annual Meeting & Exhibit in Toronto.

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

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: 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.