Algorithmic Bias, Financial Inclusion, and Gender

Artificial intelligence and machine learning are changing financial services offerings to customers across the globe. Historically, women have been the victims of unconscious bias in lending decisions. Algorithm-enabled credit decisions have the potential to create a level playing field for female customers worldwide—but only if we find and mitigate biases emerging through technology inputs and processes.

This report is part thought experiment and part primer, exploring the promises and pitfalls of using digital tools to open up new credit to women individuals and entrepreneurs. It explores two key questions:

1. Where does gender-based bias originate?
2. How do we mitigate such biases in the emerging digital credit space?