Fannie, Freddie to accept 'predictive' credit scores, US officials say

BY Reuters | AGENCY | 04/22/26 02:07 PM EDT

By Pete Schroeder and Douglas Gillison

WASHINGTON, April 22 (Reuters) - Housing finance giants Fannie Mae and Freddie Mac are now accepting additional credit scores that take into account rent and utility payments, a U.S. government official overseeing the agencies announced on Wednesday.

The move is aimed at boosting access to affordable mortgages, a goal of President Donald Trump's administration.

Federal Housing Finance Agency Director William Pulte said the pair, which guarantee most U.S. mortgages, will now accept mortgages assessed using the VantageScore 4.0 model, which uses advanced data and analytics to generate scores. He said they are also working to implement a similar modified score system from FICO.

Wednesday's announcement is that Fannie and Freddie are now incorporating the scores into their guarantee process. FHFA approved those models in 2022.

Similarly, Housing and Urban Development Secretary Scott Turner announced his department would consider those scores for mortgages underwritten by the Federal Housing Administration.

The officials said the expanded use of other credit score models should boost competition and potentially lower mortgage costs, allowing opportunities for potential homebuyers who otherwise would have struggled to gain an affordable mortgage.

"We are modernizing credit scoring with more predictive models, helping millions of Americans who responsibly pay rent qualify for mortgages. That's fair, it's commonsense, and it's finally delivering the benefits of competition to homebuyers nationwide," said Pulte in a statement.

The Trump administration has increased focus on housing affordability in recent months, as part of an effort to address general concern with rising prices ahead of midterm elections in November where Trump's Republican Party will defend slim majorities in both chambers of Congress.

(Reporting by Pete Schroeder and Douglas Gillison; Editing by David Gregorio)

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