The Social Structure of Mortgage Discrimination

In the decade leading up to the U.S. housing crisis, black and Latino borrowers disproportionately received high-cost, high-risk mortgages—a lending disparity well documented by prior quantitative studies. We analyze qualitative data from actors in the lending industry to identify the social structure though which this mortgage discrimination took place. Our data consist of 220 depositions, declarations, and related exhibits submitted by borrowers, loan originators, investment banks, and others in fair lending cases. Our analyses reveal specific mechanisms through which loan originators identified and gained the trust of black and Latino borrowers in order to place them into higher-cost, higher-risk loans than similarly situated white borrowers. Loan originators sought out lists of individuals already borrowing money to buy consumer goods in predominantly black and Latino neighborhoods to find potential borrowers, and exploited intermediaries within local social networks, such as community or religious leaders, to gain those borrowers’ trust.

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Racial disparities in wealth are currently at their widest levels in decades. According to the Federal Reserve (2014), the wealth of the median white household stood at $141,900 in 2013, 13 times greater than that of the median black household ($11,000) and ten times that of the median Latino household ($13,700). These gaps in wealth by race are less a product of income disparities than of differential access to good homes in high quality neighborhoods, which in turn produces racial differences in homeownership rates, home values, and the accumulation of home equity, the principal source of wealth for most American families (Oliver and Shapiro, 1995). Historically, these disparities have been driven by multiple forms of discrimination, both public and private, including white mob violence against African-Americans trying to move into formerly all-white neighborhoods, municipal segregation ordinances prohibiting residence by blacks on predominantly white blocks, racially restrictive covenants barring the future sale of a property to non-whites. One of the many forms of neighborhood-based racial discrimination that contributed to current disparities is the legacy of redlining—the denial of credit to non-white residential areas (Rothstein 2017). More recently, the rise of new lending practices that specifically target nonwhite neighborhoods for risky, high cost financial services have further widened racial disparities in home equity and wealth (Hyra et al., 2013; Lipsitz and Oliver 2010; Renuart, 2004; Ross and Yinger, 2002; Squires, 1992).

Numerous quantitative studies have found that black and Latino borrowers over the past decade were frequently charged more for mortgage loans than similarly situated white borrowers (e.g. Bayer, Ferreira, and Ross, 2015; Been, Ellen, and Madar, 2009; Bocian et al., 2011; Courchane, 2007; Rugh, Albright, and Massey, 2015). Even after controlling for credit scores, loan to value ratios, the existence of subordinate liens, and housing and debt expenses relative to individual income, Bayer, Ferreira, and Ross (2015) found that black and Latino borrowers in all of the seven metropolitan areas they studied were significantly more likely to receive a high-cost loan than others. These results held for both low- and high-risk borrowers and regardless of age. Rugh, Albright, and Massey (2015) similarly found that black borrowers in Baltimore overall ended up paying five percent more for their mortgages than white borrowers, again controlling for credit scores and other background characteristics.

Although quantitative evidence consistently demonstrates disparities in loan costs, the specific individual-level mechanisms through which discriminatory lending occurs remains largely unexplored. We do not know, for example, how the employees of bank and non-bank lenders identified black and Latino borrowers to target for high cost loans and how they gained those borrowers’ trust. Here we follow Hedstrom and Swedberg’s (2004, 1) call for the formulation of midrange models to explicate the “social mechanisms that generate and explain observed associations between events.” Specifically, we draw upon qualitative data obtained from declarations and depositions offered by borrowers, mortgage originators, and bank employees in recent civil rights cases to identify the processes through which loan originators steered black and Latino borrowers into riskier, higher-cost loans than similarly situated white borrowers.

We begin by situating our analysis in the context of the historical link between residential segregation, mortgage lending, and the dispossession of minority wealth. We then describe the qualitative data upon which we base our analysis and then draw upon these data to identify three salient aspects of the social context of the lending that emerged with the spread of mortgage securitization during the 1980s and 1990s: (1) the vertical segmentation of organizations in the lending industry; (2) the horizontal segmentation between prime and sub-prime lenders; and (3) the targeting of neighborhoods by race and the use of social networks and trusted intermediaries within racially segregated communities to cultivate and exploit borrowers’ trust. We conclude by explaining how these features of the mortgage lending industry contributed to the racialized extraction of wealth from individuals and communities of color in the wake of the housing bust (see Rugh et al., 2015).Racial Segregation and Reverse Redlining

In the course of the 20^th century, racial residential segregation was established and perpetuated through a combination of public and private actions that made racial residential segregation a characteristic feature of urban America by mid-century (Massey and Denton 1993). Together, the spatial segregation of African Americans through real estate discrimination and the systematic disinvestment in black neighborhoods through lending discrimination made it exceedingly difficult for African American families to acquire homes and accumulate wealth during the long, postwar economic boom (Killewald, 2013; Kuebler and Rugh, 2013; Lipsitz and Oliver, 2010; Sharp and Hall, 2014). Today many of the nation’s largest historically segregated black neighborhoods, such as those in the South Bronx and South Central Los Angeles, remain severely disadvantaged and have become majority-Latino, making Latinos also vulnerable to the adverse consequences of segregated spaces (Tienda and Fuentes, 2014; Rugh, 2015; Steil, De la Roca, and Ellen, 2015).

Federal legislative changes in the 1980s and 1990s such as the Depository Institutions Deregulation and Monetary Control Act (1980), the Alternative Mortgage Transaction Parity Act (1982), the Secondary Mortgage Market Enhancement Act (1984), the Financial Institutions Reform, Recovery and Enforcement Act (1989), and the Federal Housing Enterprises Safety and Soundness Act (1992) facilitated the growth of a secondary mortgage market and contributed to a shift from direct lending by banks that held loans in their own portfolios towards the origination of loans by brokers, bankers, or non-bank lenders who then sold the loans to investment firms that, in turn, bundled them together to back bonds for sale to investors, in a process known as securitization. For securitized loans, profits for loan originators depended not so much on long-term home values or the borrower’s likelihood of default but on short term revenues from points, fees, origination charges, and especially the size of the gap between the prevailing interest rate index and the rate paid by borrowers, commonly known as the “yield spread” (Jacobson, 2010; McLean and Nocera 2010; Unger, 2008).

In this context, predominantly black and Latino communities shifted from being objects of economic exclusion to targets for financial exploitation by intermediaries seeking to expand the pool of loans available for securitization (Squires, 2005). After being denied credit for years these communities represented an untapped market with established home equity and ample room for increased homeownership populated by borrowers with little financial experience (Botein, 2013). The persistence of high levels of racial segregation combined with structural changes in the lending industry thus facilitated the development of a structurally segmented mortgage market that offered separate and unequal loan products to disadvantaged borrowers located in black and Latino neighborhoods, particularly large numbers of high-cost, subprime loans (Apgar and Calder, 2005; Hwang, Hankinson, and Brown, 2015; Engel and McCoy, 2002; Hyra et al., 2013; Rugh and Massey, 2010; Steil, 2011; Williams, Nesiba, and McConnell, 2005).

Roughly two-thirds of subprime loans in the early 2000s were made not to new home purchasers but to individuals who already owned their homes and were refinancing them (Mayer, Pence, and Sherlund 2009). During the 1990s up to one out of every three borrowers given subprime or high-cost loans were, in fact, eligible for prime loans (Mahoney and Zorn, 1996). By 2006, 62 percent of subprime borrowers actually qualified for prime loans (Brooks and Simon, 2007). Of home purchase loans made in 2006, roughly one out of every two loans made to African American (53 percent) and Latino (46 percent) borrowers were high-cost, compared to fewer than one out of five loans made to white borrowers (18 percent) (Been, Ellen, and Madar 2009). Similarly, for refinance loans made in 2006, 52 percent of black refinance borrowers and 39 percent of Latino refinance borrowers received high-cost loans compared to only 26 percent of white borrowers (Been, Ellen, and Madar 2009). Even after controlling for available loan and household characteristics, such as income, black home purchase borrowers were more than twice as likely to receive a subprime loan as white borrowers and the likelihood of receiving a subprime loan actually increased with household income, calling into question claims that subprime loans were given to riskier borrowers (Faber 2013). The systematic channeling of otherwise qualified minority borrowers into subprime mortgages carrying high costs and risks was one form of reverse redlining (Squires, 2005).¹

Data and Methods

Although quantitative studies can estimate the size of racial disparities in high-cost, high risk lending, qualitative analysis is required to identify the ways in which loan originators targeted black and Latino borrowers and succeeded in convincing them to enter into disadvantageous contracts that put their homes and wealth at risk. Policies that led to a disproportionately negative impact on non-white borrowers could have been put in place intentionally to harm borrowers on the basis of race, they could have been implemented without racial animus but nevertheless with knowledge that they would have a disproportionate negative effect on non-white borrowers, or they could have been established without any knowledge that they would have a different impact on white borrowers as compared to non-white borrowers. Regardless of the intent or knowledge, there is a pressing need to understand how policies with such consistently discriminatory effects were put into place across multiple actors in the home finance industry.

Our data come from depositions and declarations made by borrowers, mortgage brokers, loan officers, credit managers, due diligence employees, investment bankers, and others involved in subprime lending and securitization during the housing boom of the 2000s. We obtained these statements from documents publicly filed in cases brought to federal court alleging violations of fair housing and fair lending laws.

We began by seeking to identify the universe of cases alleging violations of the Fair Housing Act and the Equal Credit Opportunity Act over the past decade. Table 1 presents a list of lawsuits filed since 2006 against financial institutions for alleged reverse redlining. Suits have been filed in a range of regions against a wide variety of institutions, ranging from small local banks, such as Southport Bank in Kenosha, WI, to large financial corporations headquartered in financial centers, such as Bank of America in Charlotte, Wells Fargo in San Francisco, and J.P Morgan Chase in New York. Over 60 percent of these cases resulted in a settlement, however, leaving little in the public record aside from the alleged violations and the terms of the consent decree or settlement. Of the remaining cases, 18 percent were dismissed early in the litigation process and likewise left a sparse public record. One case went to trial, resulting in a guilty verdict against the defendants, and just over 20 percent of the cases were still ongoing at this writing.

Table 1

Fair lending cases filed by plaintiffs alleging reverse redlining discrimination in violation of FHA and ECOA 2007–2017.

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Of the cases that did not settle and which survived a preliminary motion to dismiss to produce fuller public records, we selected four cases using an inductive strategy that deliberately sampled on the dependent variable. We chose cases in which discrimination was well documented, thereby enabling us more readily to identify the processes by which the lending discrimination was effected during the housing boom. In making our selections, we also endeavored to capture geographic and social variation among the parties and others who offered sworn testimony in the various cases.