Mainstream financial services do not serve everyone in America. 63 million American adults are either unbanked or underbanked. Many rely on high-cost alternatives to the financial system, including check cashing services or pawn shop loans. But nowhere is the disparity farther reaching than access to credit. In the US, 25 million adults are considered credit invisible. This means they lack the credit history needed to establish a credit score. 67 million more Americans have a “thin” credit file: 4 accounts or fewer. When lenders lack information on borrowers, they assume the worst about them in terms of risk.
The costs of credit invisibility are enormous. Every time a credit invisible person goes to take out a loan, they must pay more in interest than someone the lenders know better. This problem follows them into the world of premiums when they seek insurance on a car, a home, or a rental unit. A subprime credit score could cause a person to pay an extra $33,000 in interest on an average 30-year mortgage compared to the prime rate. Not all subprime scores are a result of a borrower’s unworthiness as it pertains to credit. Some stem from blind spots in what credit score calculations do and don’t observe.
The demographics of the credit invisible group include populations historically underserved by the financial system. 3 quarters of the people with little to no credit history make less than $50,000 a year. Nearly half make less than $25,000 annually. The people in this group are more likely to have recently immigrated, be members of the Hispanic or African American community, or have recently lost a spouse to death or divorce. They may also be young or new to using credit.
Interest rates on credit can make the difference in someone’s financial survival. 60% of Americans could not pay an unexpected $1,000 expense with savings alone. 1 in 3 would choose to borrow money to cover the cost. People able to borrow at a lower interest rate will have an easier time paying off their debts than those at the higher rate. Considering how common it is for people to run into unexpected expenses, it’s no wonder that many Americans find themselves stuck in a difficult situation regarding debt.
How can changing the inputs in credit reports change this story? How can credit score calculators capture a more accurate snapshot of the credit invisible group? Including alternative forms of data with consumer permission could move 20 million more US consumers into scorable credit bands. Many of these Americans could potentially qualify for prime or near prime offers were the following additional factors taken into consideration. Bank transaction data, rental payment records, and telecom/utility payment information are all data types that could turn the tide if included in consumer credit scores.
Adding bank transaction data alone could increase the number of prime (or better!) consumers in America by almost 4 million. If a consumer agrees to let credit agencies see their bank transactions, they can observe how the consumer handles money firsthand. When they pay bills, how much money they leave over, and more could all be examined. Considering bank transaction data on all consumers could reduce the credit unscorable population by 50%.
Rental payment reporting is too often ignored as a potential for building credit history. Right now, many landlords perform credit checks as part of their leasing process, but rental data itself is not included on credit reports. However, mortgages on a home do appear on one’s credit score. This puts renters at a disadvantage next to homeowners in the lending market even though both groups make regular scheduled payments for their housing. 51% of consumers believe it would be helpful to have rental payment information included in credit reporters and scores.
Like rental payments, utility and telecom bills are regularly scheduled payments that indicate a consumer’s financial discipline. Furthermore, 90% of American adults have at least one utility bill in their name. 9 million consumers could become scorable using consented telecom/utility data. Over 7.5 million could move from either unscorable or subprime categories into prime or near-prime lending territory once this data source is factored in.