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. The presenters in this session present a flexible framework that highlights key considerations in bias evaluation that can be adjusted to suit your process.

Description: The presenters in this classic session will explore protection and accumulation products as well discuss the current state of the hybrid Life/LTC market. They will also examine the latest trends and the challenges to innovation and highlight key factors impacting the product actuary including the impact of technology, regulation and competitive environment.