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It's fairly well known that women receive less favorable loan terms from salespeople, on average, than men when they borrow money. One recent study into lending practices in US car dealerships recently confirmed as much. Equally, it has been found in bank lending and mortgages for many years around the world.

The academic literature suggests that salespeople may offer women worse terms in the belief they know less about the market, and so will be less capable of assessing whether they're getting a fair deal. It might also be that women are penalized for not being as assertive as men.

One increasingly pressing question is how this will be affected by artificial intelligence (AI) as it comes to play a bigger part in lending. Though banks and other lenders can be coy about the extent to which they're using machine learning and generative AI in lending, it's certainly already happening behind the scenes and is set to become much more important over the next couple of years.

You might think AI could reduce lending discrimination against women, perhaps by neutralizing the biases of sales representatives. In fact, a new study from my research group indicates that it has the potential to get worse. So why is this, and can it be avoided?

Our research looked at more than 50,000 car loans in Canada, and found yet more evidence of lending discrimination against women. In the field of credit research, the standard way of comparing loans is known as "expected utility."

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