Rental dates can enhance the predictability of the credit score mannequin by 10% or extra

Combining information about a consumer's rental payments with traditional credit data made it easier to predict their repayment ability than standard performance indicators alone, TransUnion found in a new study.

The study, which analyzed how well 1 million consumers paid their debts in 2019 using rental data provided by TransUnion in late 2018, found that including rental data can forecast credit models by at least 10% for new 90- plus days of default on various types of consumer finance products including mortgages, credit cards, auto and personal loans. This is significant because, aside from the experience during the 2020 pandemic when long-term forbearance was allowed, service providers generally view consumers who are in arrears by more than 90 days as arrears.

The results of the new TransUnion study could boost recent efforts by two major government-affiliated mortgage investors to promote the reporting and use of rental payment information in lending. Fannie Mae, one of the two state-sponsored companies that are buying up a significant portion of the home loans they make in the United States, has begun experimenting with using rental data on single-family homes. The other, Freddie Mac, worked with a business partner to encourage multi-family borrowers and tenants to participate in reporting.

While other studies have shown that including rental data can give newer versions of consumer credit scores a boost, potentially increasing borrowers' ability to get loans at lower interest rates, the latest research is focusing more on the results for mortgage service providers and lenders .

“In the past we did the analysis from the consumer's point of view, or how rental data in a credit report affects the score. The groundbreaking thing about this analysis is the fact that it examines the lender's perspective, ”Maitri Johnson, Vice President, Tenant and Employment Screening at TransUnion, said in an interview.

The divergence in predictability cases that took rental payment history into account came into play especially for borrowers who lacked traditional credit history or who had lower valuations, Johnson said. This is in line with Fannie's goal of expanding the range of lower-income borrowers eligible for home ownership loans through his rental data initiative.

"The TransUnion results support Fannie Mae's belief that if someone pays rent consistently, the chances are they can also consistently pay their mortgage," said Steve Holden, vice president of single family home analysis at Fannie Mae, in a press release. "This … demonstrates the potential of leveraging technology and data to responsibly remove long-standing barriers to access to credit while helping consumers receive a fairer and broader credit rating."

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