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: Data analytics is changing insurance industry and will fundamentally change how we run insurance business. Actuaries could and should be on top of it and lead the change. This practical session would provide a technical overview about GLM and describe how GLM can be applied as a business tool in life insurance. The session would also focus on case-studies across different functional areas like pricing, fraud detection, underwriting and product development.

Description: It has been a year since the SOA implement major changes to the ASA curriculum. This session will provide an update on the changes and in particular focus on what we have seen as schools update their VEE and UCAP/CAE submissions.

Description: Discussion of effective communication. Topics included: 1. Characteristics of an effective communicator 2. How to make a presentation or write a report

Description: Learn industry best practices including challenges faced by retirees, such as needing exposure to growth, most exposed to sequencing risk, and the need for smooth returns to avoid poor investor behavior caused by risk aversion. Other topics will include how to set investment objectives which consider the members’ real-world needs and how to build portfolios and implement risk management strategies to meet those objectives. The speaker will provide real-life examples/case studies.

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.