From affordability assessments to collections strategies, bias (even unintentional) can exclude underrepresented groups. This data-driven session reveals where bias creeps into credit processes and how to mitigate it through policy, tech, and training.

Key Takeaways:

• Real examples of bias in credit scoring, pricing, and collections.
• Tools & frameworks to audit decision-making for fairness (e.g., blind underwriting).
• How to train teams to recognise and interrupt bias in real time.

Impact: Reduce compliance risk and expand market reach by designing fairer products/services.