in pictures

1936 risk assessment map of Philadelphia, used by the FHA in lending decisions


A significant factor in historic housing segregation, the practice of redlining dominated lending practices from the 1930s until the passage of the 1974 Equal Credit Opportunity Act (Massey & Denton, 1998)⁠. The New Deal-era Federal Housing Authority (FHA) was required by law to classify neighborhoods according to financial risk, and to use these metrics as criteria in the processing of mortgage applications, resulting in a racially stratified redistribution of wealth. With the arrival of Levittowns and white flight, a pro-segregation culture began to manifest within FHA publications, which endorsed racial homogeneity at the neighborhood level (Loewen, 2006)⁠. The federal government’s efforts to increase home ownership rates has been described as “one of the greatest mass-based opportunities for wealth accumulation in American history,” but, to the extent that the federal government purposefully tried to maintain the property values of white neighborhoods at the expense of people of color, this opportunity was denied to people of color, and is thought to be a major component in the historic racial wealth gap (Oliver & Shapiro, 2006, p. 18)⁠.


Symbol to declare compliance with fairness in lending laws

While the racial wealth gap and housing segregation would continue to persist, this lending paradigm was shattered following the Civil Rights Era. As political momentum increased for the eradication of both de jure discrimination and the remaining New Deal and Great Society scale social spending programs, the federal government implemented the Equal Credit Opportunity Act of 1974, as well as the Community Reinvestment Act of 1977, which explicitly prohibited redlining and similarly overt racial discrimination in lending practices. While allegations of redlining practices would continue, a distinction between process-based discrimination (in which lending decisions are made according to overtly discriminatory criteria) and outcome-based discrimination (which focuses on the disparate impact caused by lending decisions) ultimately characterized the academic conversation (Ross & Yinger, 2003)⁠. While Ross & Yinger (2003) used these terms to describe the mortgage market, the same concepts could easily be applied to the explosion of consumer credit which would come in the following decade.

First National of Nebraska building; defendant in National Bank of Minneapolis v. First of Omaha Service Corp. (1978). Photo by JonClee86, CC BY-SA 3.0

The following year after the passage of the Community Reinvestment Act, Marquette National Bank of Minneapolis v. First of Omaha Service Corp. (1978) reached the Supreme Court. The plaintiff, Marquette National Bank, alleged that First of Omaha Service was violating state usury laws by offering consumer credit to customers across the country, regulated only by Nebraska’s liberal usury laws. In a unanimous decision, the Supreme Court upheld this practice as legal, effectively legalizing usury nationwide, and “allowing lenders to price in the cost of loans to riskier borrowers” (Trumbull, 2012)⁠. This decision paved the way to a massive increase in consumer debt, as access to credit was, nominally, democratized – however, as the Federal Reserve Board was soliciting testimony on the implementation of the Equal Credit Opportunity Act, the infantile consumer reporting industry made it clear that credit access would be anything but democratic. In their pursuit of quantifying risk, bankers demanded the right to consider marital status, usage of birth control, or whether or not a newlywed took her husband’s surname (Williams, 2004)⁠. While these criteria didn’t all make it through the federal rulemaking process, shockingly, scoring by zip code did, allowing “banks to surreptitiously continue to score race, class, and national origin, using zip codes as their proxy” (Williams, 2004, p. 16)⁠.

Data source: Costly Credit: African Americans and Latinos in Debt, (Silvia & Epstein, 2005)

Data source: Costly Credit: African Americans and Latinos in Debt, (Silvia & Epstein, 2005)











As access to consumer credit demonstrably rose over the coming decades, the scope of the consumer reporting industry’s scoring project increased dramatically, which is now estimated to score consumers, on average, once every calendar week (Thomas, 2000)⁠. These scores are thought to be “far better predictors of outcomes than broad measures of educational attainment or racial classification,” and, yet, despite their individualized sense of objectivity, assertions of outcome-based discrimination persist (Fourcade & Healy, 2013, p. 570)⁠. Instead of overt classist or racist discrimination, it is argued, these credit scoring metrics serve as methods of classification, used by gatekeepers to guard access to material goods – a Foucaultian “dividing practice in which the ‘bad’ are separated from the ‘good’, the criminal from the law-abiding citizen, the mentally ill from the normal” (Burton, 2012, p. 114; Fourcade & Healy, 2013)⁠.


Check cashing stores, like this one in Atlantic City, serve underbanked customers. Photo by Chris Goldberg, CC BY-NC 2.0


Graffiti present on a Bank of America window. Photo by kozemchuk, CC BY 2.0

Yet, despite this rhetoric, academics still argue that the financial system has resulted in a discriminatory disparate impact. Failure to qualify for credit, it is asserted, pushes consumers into a relatively expensive credit market of last resort, where marginalized and underbanked customers are required to pay predatory fees for access to financial services (Carruthers & Kim, 2011; Fourcade & Healy, 2013)⁠. Similarly, access to mortgages, which is now largely governed by credit ratings, is described as a “dual mortgage market,” where individuals without access to credit are required to take on so-called subprime mortgages in order to purchase a home (Immergluck & Wiles, 1999)⁠. Not surprisingly, the dual mortgage market’s impact has been to exacerbate wealth loss in communities of color, via a mechanism not all that different from historic redlining (Rugh & Massey, 2010)⁠.

Man sleeping on public bench, Atlanta, GA. Photo by Adam Hermann.

Despite these developments, the individualized nature of credit scoring complicates collective action. Increasingly, financial responsibility is equated with personal morality, and financial irresponsibility is stigmatized (Graeber, 2011; Pathak, 2014)⁠. Furthermore, the consumer reporting industry has expanded to offer “thousands of ‘consumer scores,’” expanding both the scope of their surveillance, and the responsibilities of the typical consumer significantly, through the application of these credit scoring strategies in non-financialized domains (Pasquale, 2015, p. 33)⁠. While some political organization exists, such as Occupy Wall Street’s Strike Debt movement, scoring metrics and questionable lending practices persist, and increasingly capture scores of young people via the growing student debt bubble (Draut, 2006; Strike Debt, 2014; Williams, 2004)⁠.

Occupy Wall Street (2011). Uncredited.


Burton, D. (2012). Credit scoring, risk, and consumer lendingscapes in emerging markets. Environment and Planning A, 44, 111–124.

Carruthers, B. G., & Kim, J.-C. (2011). The Sociology of Finance. Annual Review of Sociology, 37(1), 239–259.

Draut, T. (2006). Strapped: Why America’s 20- and 30-Somethings Can’t Get Ahead. New York: Anchor Books.

Fourcade, M., & Healy, K. (2013). Classification situations: Life-chances in the neoliberal era. Accounting, Organizations and Society, 38(8), 559–572.

Graeber, D. (2011). Debt: The First 5,000 Years. Brooklyn: Melville House Publishing.

Immergluck, D., & Wiles, M. (1999). Two Steps Back: The Dual Mortgage Market, Predatory Lending and the Undoing of Community Development. Chicago: The Woodstock Institute.

Loewen, J. W. (2006). Sundown Towns: A Hidden Dimension of American Racism. New York: Simon & Schuster.

Massey, D. S., & Denton, N. A. (1998). American Apartheid: Segregation and the Making of the Underclass. Cambridge: Harvard University Press.

Oliver, M. L., & Shapiro, T. M. (2006). Black Wealth / White Wealth: A New Perspective on Racial Inequality (2nd ed.). New York: Routledge.

Pasquale, F. (2015). The Black Box Society. Cambridge: Harvard University Press.

Pathak, P. (2014). Ethopolitics and the financial citizen. The Sociological Review, 62(1), 90–116.

Ross, S. L., & Yinger, J. (2003). The Color of Credit: Mortgage Discrimination, Research Methodology, and Fair-Lending Enforcement. Cambridge: The MIT Press.

Rugh, J., & Massey, D. (2010). Racial Segregation and the American Foreclosure Crisis. American Sociological Review, 75(5), 629–651.

Silvia, J., & Epstein, R. (2005). Costly Credit: African Americans and Latinos in Debt (Borrowing to Make Ends Meet Briefing Papers No. 5). Baltimore: The Annie E. Casey Foundation. Retrieved from

Strike Debt. (2014). The Debt Resisters’ Operations Manual. Oakland: PM Press.

Thomas, L. C. (2000). A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers. International Journal of Forecasting, 16(2), 149–172.

Trumbull, G. (2012). Credit Access and Social Welfare: The Rise of Consumer Lending in the United States and France. Politics & Society, 40(1), 9–34.

Williams, B. (2004). Debt for Sale. Philadelphia: University of Pennsylvania Press.



in brief

In brief

Can one meaningfully quantify class? This, according to Fourcade & Healy (2013)⁠, is what has occurred in contemporary liberal states – except, instead of being used by social scientists, who would love to use these metrics “were they not trade secrets” (Fourcade & Healy, 2013, p. 570)⁠, it is, rather, employed by the financial industry in order to control access to credit, and the broader financial system (and, as is the trend within neoliberalism, this market logic is increasingly applied to non-market situations in individuals’ lives). Credit scoring, a nominally nonracial and nongendered project, evidently encapsulates more predictive information about an individual’s performance in a market economy than the whole of social scientific research, yet, as social science research indicates, traditional cleavages in regards to life outcomes still persist, which pivot on such axes of oppression as race and gender. The intersection of these seemingly contradictory conclusions is where Fourcade & Healy (2013) theorize, trying to decipher the nature of stratification in a financialized world.

The algorithms that control these metrics, it is argued, are unique in that, by design, they delineate access to material resources on an individuated basis, instead of upon the basis of such group classifications as race, class, and gender. However, these algorithms don’t produce class, but, rather, classifications, which are used as criteria by gatekeepers who govern access to resources. The less access an individual has, the more they are forced to rely upon substandard financial products such as payday loans and subprime mortgages, creating a feedback loop between the classification metric and market performance. No longer burdened by overtly discriminatory criteria, the financial industry, as well as broader society, is able to shroud this classification scheme in the language of morality, encouraging consumers to volunteer the self-surveillance of their own consumption patterns, as only those individuals with enough so-called financial literacy are deemed worthy of upward mobility. Yet, as Fourcade & Healy (2013)⁠ assert, these consumption patterns are more frequently determined by market position than moralistic thriftiness, as the poor are forced to pay higher proportions of lenders’ financing costs than their wealthy counterparts, in a sort-of self-fulfilling prophecy of financial proletariatization.

Fourcade, M., & Healy, K. (2013). Classification situations: Life-chances in the neoliberal era. Accounting, Organizations and Society, 38(8), 559–572.

Privacy Statement