As banks increasingly deploy artificial intelligence tools to make credit decisions, they are having to revisit an unwelcome fact about the practice of lending: Historically, it has been riddled with biases against protected characteristics , such as race, gender, and sexual orientation . It used AI to retroactively balance the data that went into developing and testing its AI-driven credit decision model by shifting the female distribution, moving the proportion of loans previously made to women to be closer to the same amount as for men with an equivalent risk profile, while retaining the relative ranking.