American families are drowning in more than $88 billion in medical debt. Unpaid medical bills weigh on their credit reports, making it harder to buy a house, rent an apartment or secure a job.
These moves will make the credit rating system more fair by eliminating debts that disproportionately affect low-income and minority groups. “As an industry, we remain committed to helping drive fair and affordable access to credit for all consumers,” the credit bureau CEOs boasted.
This is just the latest chapter in a long history of politicians and activists trying to make the nation’s private credit reporting system more equitable by eliminating evaluation categories — such as race and gender — that explicitly reproduce inequality in American society. Yet, while beneficial, past efforts to make credit reporting gender- and race-blind reveal that so long as government benefits are tied to creditworthiness, and structural inequality pervades the economy, Americans’ ability to do everything from buying a car to getting a job to renting a home will remain unequal.
Credit has always been central to American capitalism, and gaining access to it necessarily relies on credit information. At first, such information tended to be local — rumors circulating in a community about someone’s reputation. As the U.S. economy expanded across the continent in the 19th century, however, merchants and manufacturers increasingly needed to know whether their far-off trading partners were creditworthy.
Enter firms like R.G. Dun & Co., which developed nationwide commercial surveillance networks. Company agents, often small-town lawyers, reported on the reputations and personal habits of local businesspeople. At its New York City office, Dun & Co. distilled the financial identities of tens-of-thousands of Americans — their capacity, their capital and their character — into ledger entries in big, leather-bound volumes.
The explosion of mass consumer credit at the turn of the 20th century encouraged the growth of local credit bureaus. In the same way Dun & Co. built nationwide credit files on businesses and businesspeople, these local firms inhaled, compiled and sold credit information on individual households. They inferred the ability and willingness of individuals to pay their debts from repayment histories. But they also relied on identifying categories, such as occupation, gender, race and national origin, as well as “markers of personal character,” including religion, marital bliss or discord, alcoholism and “sloth.”
This highly subjective system depended upon applicants meeting with credit managers, whose individual judgments determined whether the applicant got a loan or not.
These credit reports were also secret. That left consumers scrambling to conform to opaque and highly subjective expectations. Not surprisingly, the process reproduced racial, gender and class inequalities. White male borrowers topped the credit hierarchy.
During the New Deal, policymakers sought to encourage credit spending to lift the nation out of the Great Depression. To do so, they introduced federal credit programs, notably low-cost, government-backed mortgages from the newly created Federal Housing Administration. These mortgages enabled homeownership to become the foundation for household wealth building in the postwar era.
Crucially, however, policymakers built a credit welfare state that channeled public benefits through private lenders. Only creditworthy households could access these loans and the same private credit reporting agencies — with their inherent biases and prejudices — made these determinations even though the benefits flowed from the government.
This solidified the reporting agencies’ role as gatekeepers, now with the power to set Americans on the course of wealth and prosperity with a government-backed mortgage — or to dash their hopes.
Over the ensuing decades, White households overwhelmingly benefited, and continue to benefit, as federal credit policy expanded to include not only farm loans and mortgages, but also small business and student loans. As the recent White House announcement explains, the federal government became, “one of the largest actors in consumer credit markets.”
Meanwhile, biases in credit reporting ensured that many groups of Americans were excluded from participation.
In one sense, the inclusion of race and gender as factors in determining creditworthiness represented the prejudices of credit professionals. Yet deeper structural factors also made these categories objective and rational reflections of credit risk in the decades after World War II. Compared to White households, Black families lacked wealth and secure employment. Women’s employment was more vulnerable to family interruptions, and they faced fewer job opportunities and lower pay than men (even when performing the same roles). These factors, shaped by racist and sexist labor markets, meant that biased categories carried predictive power.
“Credit decisions that privileged men over women and whites over African Americans were a reflection of real structural inequalities in American society,” historian Josh Lauer writes. These real structural inequalities, in turn, made it riskier to lend to Black and female borrowers — exactly what the credit reporting agencies aimed to determine.
Two trends converged to strike racial and gender categories from consumer credit scoring.
First, the social movements of the 1960s and 1970s agitated to make the individual credit market more friendly to consumers. Consumer groups demanded access to credit files, as well as the right to fix credit and billing errors. Their advocacy prodded Congress into passing the Fair Credit Reporting Act (1970) and Fair Credit Billing Act (1974).
Women’s and civil rights groups also sought to eliminate racial, gender and other biased categories from consideration by credit granters. Led primarily by upper-class women who despised being treated like “dead beats,” these groups secured the Equal Credit Opportunity Act (1974) and amendments to it (1976) that barred discrimination against any credit applicant, “on the basis of race, color, religion, national origin, sex or marital status, or age.”
Their crusade to challenge the old norms of subjective, invasive credit judgments based on deeply personal information received a boost from new computing technology, which offered an alternative for weighing creditworthiness: statistical scoring systems that emphasized a limited set of “relevant” economic and demographic data. Credit scoring promised to eliminate the individual prejudices of credit managers, in favor of a fairer, “unbiased” evaluation.
But the hopes surrounding the Equal Credit Opportunity Act and the move to “objective” analysis proved overly optimistic. While categories like race and gender no longer directly factored into decisions, they still played a role indirectly through variables like occupation, length of employment or whether one rented their home.
In other words, because the U.S. socio-economic structure remained racist and gendered, someone’s race and gender still drove their access to credit, now indirectly via other scoring metrics. The appearance of fairness then did not mean the system was actually fair. Although efforts to weed out the most pernicious secondary variables, like Zip codes, succeeded in later years, minority Americans still have lower credit scores because racial biases persist in educational systems and labor markets.
Eliminating medical debt from credit scores could be a similar achievement. Low income and minority groups disproportionately bear the burden of medical debt. The new measures will mean that the consequences of their exclusion from high-quality insurance plans and certain areas of employment will no longer compound through the credit scoring system. Many households will see their credit scores go up.
Yet, the reality remains that credit access can never be fair if the underlying economic structures have built in biases. So long as government benefits depend on individual credit, and as long as structural inequalities mar the American economy, deep inequalities will affect who gets a mortgage, a small business loan, what rates they pay on car loans and more.