Description: In order for an organization to benefit from artificial intelligence/machine learning (AI/ML) models, it requires the involvement of different business areas. During this webcast, professionals from data analytics, audit and risk areas will address challenges and provide solutions for working together to develop, implement, use and risk manage AI/ML tools. Throughout the discussion, the presenters will discuss: • Defining and exploring the challenges and objectives between data scientists, domain experts and control functions • Risk management – model risks and other risks • End-to-end model validation • Model performance vs. interpretability/understandability trade-offs • What to audit – auditor’s challenge and solutions

Description: An introductory article describing how Bayesian statistics has evolved over the past 20 years and why it offers the actuarial discipline powerful tools to better understand and manage risk. Compared with traditional (frequentist) and black-box (machine learning) approaches, Bayesian analysis provides explainable models focused on distributions of estimates instad of simply point estimates.

Description: An introductory article describing how Bayesian statistics has evolved over the past 20 years and why it offers the actuarial discipline powerful tools to better understand and manage risk. Compared with traditional (frequentist) and black-box (machine learning) approaches, Bayesian analysis provides explainable models focused on distributions of estimates instad of simply point estimates.