De-Risking Your Decisions: How to Eliminate AI Bias in a Regulated World

Algorithmic bias poses a serious risk to financial institutions, with direct implications for fair lending, consumer protection, and ESG commitments.

Grounded in the Unbiased pillar of Feedzai’s TRUST Framework, this webinar provides practical strategies to reduce bias at every stage of the AI lifecycle. We’ll cover how proxy variables introduce risk, share a three-part approach to bias mitigation, and explain why inclusive design is essential for building fair, effective AI systems.

Key Takeaways:

• Understand why removing attributes like gender or age isn’t enough — and how AI can still infer protected characteristics through indirect signals.
• Learn Feedzai’s three-stage bias mitigation strategy:
  • Pre-processing (before training)
  • In-processing (during model training)
  • Post-processing (after deployment)
• Discover how to use tools like Aequitas Flow to run audits, detect performance gaps, and ensure fair outcomes across different demographic groups.
• Explore how diverse, inclusive teams help uncover blind spots and design AI systems that serve all populations equitably.

Register now to secure your place!