The news: TransUnion has introduced new pricing for credit scoring for mortgage borrowers, undercutting the pricing of FICO’s new mortgage credit scoring model: FICO charges resellers $10 per score, while TransUnion charges $4.

The war: FICO scores have long been deeply embedded in credit scoring for a wide variety of consumer lending products. FICO is so entrenched that it’s been accused of being an illegal monopoly. In 2006, the main credit bureaus—TransUnion, Experian and Equifax—unveiled VantageScore to compete with FICO.

There’s clearly no love lost between FICO and the bureaus. After FICO announced two weeks ago that it would cut out the credit bureaus from part of the credit scoring process in mortgage origination, TransUnion responded with a sharp rebuke, saying that its “tactics fly in the face” of consumer benefits. FICO fired back by accusing VantageScore of being “a de facto monopoly.” 

The trend: TransUnion’s score incorporates traditional consumer credit data and alternative data (e.g., rent and utility payments) to fill in blanks about consumers who have few credit accounts or a limited credit history. This group includes young consumers, consumers who exclusively use cash or debit cards, and recent immigrants who haven’t established themselves.

For example, younger consumers  often don’t understand what factors into their credit scores, are more wary of debt relative to their elders, and use forms of credit that haven’t traditionally been scored. Among consumers under 35, 42.8 million (48%) are buy-now-pay-later (BNPL) users, according to our forecast. (Note: Some BNPL providers have declined to provide credit data to the bureaus).

Our take: The market for consumer credit data and how it’s packaged is hotly contested, and the government has helped facilitate competition. In addition, the fintech Plaid, a newcomer to credit reporting, just introduced a cash flow–based scoring model. 

This competition is good for consumers, because it creates more ways for them to access credit. And it should also be good for data buyers, including banks, because it will mitigate prices and encourage the development of more sophisticated scoring models and data products.

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