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Excerpted From: Winnie F. Taylor, Fintech and Race-based Inequality in the Home Mortgage and Auto Financing Markets, 33 Loyola Consumer Law Review 366 (2021) (73 Footnotes) (Full Document)
The racial gap in wealth in the United States is astonishing. A 2019 survey found that the typical White family has eight times the wealth of the typical African American family and five times the wealth of the typical Hispanic family. Unfortunately, discrimination in the home mortgage market and the lending industry has contributed greatly to the inequality of wealth gap by limiting wealth accumulation opportunities for racial minorities. The magnitude of economic loss that racial minorities experience from discrimination in mortgage lending is exemplified in a recent study by researchers at the University of California, Berkeley (the “Berkeley Study”). These researchers tested home loans for the presence of racial discrimination and estimated its levels in home mortgage credit, the largest consumer-lending market for lenders. Their findings show that fintech and traditional lenders charged otherwise equal Latinx and African American borrowers higher interest rates than White borrowers for purchase and refinanced mortgages, costing the minority borrowers $765 million yearly, for the same product.
Fintech describes a diverse group of nonbank companies that use digital technology to modernize and simplify both the provision of financial services and the customer experience in interfacing with financial services providers. Advances in electronic systems are eliminating time and space restrictions on the delivery of financial services, lowering the cost for some innovative products, and providing the incentive for newly emerging companies to offer financial products on a highly competitive basis. In short, as stated by one influential observer of financial market trends, the new digital technology unlocks new possibilities for fully frictionless transacting. By making financial transactions infinitely faster, easier, and cheaper, fintech lenders also offer new opportunities for financial inclusion and expanded access to financial services. While fintech tools have great potential to deliver a wide range of analytically grounded financial services and simplified choices that can benefit racial minorities, they also have the potential to deprive individuals and communities of color of significant wealth accumulation. Although the Berkeley Study shows that the fintech lenders discriminated forty percent less than traditional lenders in the pricing of home loans, it is important to point out that this level of racial discrimination is still intolerable. By using algorithmic mechanisms and data analytics to make their lending decisions, fintech innovations are poised to amplify the racial wealth gap. The worry is that as fintech firms continue to grow and eventually overtake the financial services industry, the racial wealth gap will become even wider given that home ownership is the primary source of wealth for most Americans. The additional concern is that fintech credit assessment tools will make it more difficult for consumers to prove race-based lending discrimination claims in the home mortgage market and beyond. The automobile financing market is especially noteworthy because unabated discrimination in this market may also have a deleterious effect on wealth accumulation of racial minorities. It is thus imperative that policymakers acknowledge and prioritize racial discrimination in fintech firms as an urgent problem requiring prompt legislative and law enforcement attention.
The Berkeley Study findings show that although fintech lenders reduced biases by removing face-to-face interactions, their lending assessment tools nevertheless produced worrisome statistical discrimination that disproportionately impacted racial minorities. To be sure, both human judgment bias and statistical discrimination impede opportunities for racial minorities to accumulate wealth and otherwise advance economically. But under current fair lending law, race-based, disparate impact discrimination claims in consumer lending are difficult to prove, if allowed to be litigated at all. And yet given the proliferation of fintech firms with their ability to produce racially disparate outcomes, statistical discrimination will eventually become the dominant form of racial discrimination that exists in American society. Faced with this potentiality, policymakers should unequivocally endorse impact theory as a necessary methodology for proving lending discrimination claims and clarify how impact proof standards can be met.
The purpose of this essay is to stimulate and add to the discussion regarding the need for lawmakers to mitigate potential racial discrimination in fintech algorithmic consumer lending. It questions whether the vast array of data included in fintech algorithms will increase proof difficulties for plaintiffs who litigate race-based, disparate impact lending discrimination claims. Furthermore, it argues that proof difficulties present the ultimate challenge to achieving racial justice in consumer credit transactions because if this challenge is not met, price inequities will likely continue to economically devastate individuals and communities of color as they navigate the fintech marketplace. The essay is not intended to provide definitive answers to the racial discrimination questions fintech lending raises. Rather, its purpose is to shed light on why it is important that legislatures and fair lending enforcement officials consider in greater depth the problem of discriminatory algorithms and their effects on racial minorities. The home mortgage and automobile loan markets are highlighted to explore the concerns raised in this essay because houses and cars are likely to be the two most expensive assets consumers will own.
The essay proceeds as follows. Part I provides a brief historical overview of how the home mortgage policies and practices of the federal government and traditional banks contributed to the current racial wealth gap.
Part II explains how traditional lenders make their credit decisions. This Part provides a backdrop for comparing traditional lender decision making with fintech credit assessment tools, which are discussed in Part III.
Part III describes algorithmic scoring systems that fintech firms use to make their lending decisions and demonstrates why policymakers must scrutinize algorithmic data inputs and the structural design of algorithms to determine if they generate racial disparities.
Part IV emphasizes why racial discrimination in fintech lending is an urgent problem that lawmakers should promptly address. This Part also analyzes how the problem of discriminatory algorithms exacerbates proof difficulties for plaintiffs who litigate racial discrimination claims based on lending disparities.
Part V explores the problem of racial inequity in automobile financing and explains why lawmakers should address concerns about discriminatory lending practices in this market with greater nuance than has characterized their efforts to date.
Part VI analyzes the problem of proving lending discrimination claims.
As Part VII concludes, this essay underscores the need for policymakers to critically examine predictive analytics and machine learning decision making with the aim of eliminating their ability to further deplete the wealth of racial minorities. Also, at the federal level, the essay urges Congress to mandate the collection of race data in the automobile finance market so that plaintiffs with race-based discrimination claims against creditors that provide auto loans can have a realistic chance of proving their claims under federal fair lending law.
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The problem of racial discrimination in a completely virtu-alized financial world has profound legal and social consequences for racial minorities. This is especially true when it comes to home and automobile purchases, the two most expensive and consequential decisions consumers make. Besides providing shelter, real property builds equity that can be used as collateral for loans for business, education, and other important purposes. Access to reliable transportation is crucial to getting to work, to the grocery store, to the doctor, to school, and to childcare. Together, homeownership and reliable transportation also enhance the ability of American consumers to accumulate and transfer enormous wealth. In the coming years, fintech's impact on the home mortgage and auto loan markets will grow exponentially. This growth should not impede the goal of achieving economic equality for racial minorities. To prevent such a catastrophe, it is incumbent upon policymakers to promptly develop approaches to effectively examine, analyze, and monitor fintech algorithmic credit assessment tools. Legislation that mandates the collection of race data in financed auto sales and states unequivocally that disparate impact claims are cognizable under the ECOA are major steps toward eliminating racial discrimination in consumer credit. Unless and until the problem of racial discrimination in lending is sufficiently addressed, the pervasiveness of race-based inequality in wealth will continue to beset people of color.
Professor of Law, Brooklyn Law School.
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