Experian Report: Nearly 1 in 5 American Adults Do Not Have Conventional Credit Score

Jan 26, 2022Financial Literacy, News

New research released by Experian and Oliver Wyman found that 106 million American consumers cannot secure credit at mainstream rates because they have a subprime credit score, are unscoreable by conventional credit scores, or are considered credit invisible. Lenders could improve access to credit for nearly 50 million credit invisible and unscoreable consumers by using expanded data like rental payments, utility information, and more.

“As an industry, we can and must do better to ensure more consumers can access financial services at affordable rates,” said Greg Wright, Chief Product Officer and Executive Vice President at Experian Consumer Information Services. “While the findings show we are moving in the right direction, financial access depends on complete industry adoption of new data and insights as well as business practices that proactively address the historical gap that’s existed in serving more consumers.”

Research found that 19 percent of American adults do not have a traditional credit score, 28 million are considered credit invisible, 21 million are considered unscoreable, and 57 million have subprime credit scores. Also, credit invisibility typically affects younger consumers, with 40 percent of credit invisibilities under 25 years old.

The report found that credit invisibility more frequently impacts underserved communities, with 26 percent of Hispanic consumers and 28 percent of Black consumers invisible or unscoreable compared to 16 percent of White and Asian consumers. Also, immigrants and consumers in low-income neighborhoods are more likely to face obstacles when accessing traditional financial services.

Experian noted that lenders can expand access to credit by increasing the amount of consumers they can assess and by improving how they identify borrowers’ true credit quality, such as leveraging nontraditional credit data or expanded data. Research found that when combining machine learning and advanced analytics with expanded data sets, 96 percent of credit applicants can be scored.

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