IWD 2022: Breaking the Bias with Data Science

When I was a kid, women often found it harder to get credit than men. A lot of lenders just didn’t think women were good credit risks. On International Women’s Day today, I’d like to share about how FICO broke that bias with data science.

When Bill Fair and Earl Isaac started selling data-driven credit scoring models in the late 1950s, it was a new concept for lenders. Prior to that, credit decisions were made by loan officers, nearly all of whom were men. Throughout the 1960s and ‘70s, the company convinced lender after lender that credit scoring was a better way to make decisions, for the lender and the borrower.

Credit scoring systematically replaced hunches with calculations, and took bias literally out of the equation. Credit scoring looks at facts. Men and women get the same treatment – based only on hard data.

That’s not rocket science – it’s just good data science.

I was on the team that launched the FICO® Score — a particular kind of credit scoring model, based on credit bureau data — back in the 1980s. The FICO® Score doesn’t include gender. You can see what is included on our myFICO site.

In fact, the average FICO® Score for women is around the same as the average FICO® Score for men.

How has something this simple helped women prosper? It has helped more women get credit, and not just in the United States. FICO credit scoring systems are used in countries worldwide, and some 30 countries worldwide use versions of the FICO® Score based on local data.

In this video, you can hear from Alejandro Cardini, head of Product at Círculo de Crédito, about how the FICO Extended Score has helped them extend credit to millions more Mexicans. And Michelle Beetar from our South Africa operation talks about the benefits of credit scoring there.

As I say in the video, FICO doesn’t just aim to build the best credit scores. Our mission is to build the fairest credit scores.

That’s how we at FICO #breakthebias with data science.