Document Type

Article

Publication Title

Cardozo Law Review

Volume

45

Publication Date

2024

Abstract

Algorithms in consumer finance can entrench, exacerbate, and conceal bias. This article considers the increased importance, in the age of algorithmic lending, of disparate impact analysis as a tool to combat predation and discrimination in consumer finance transactions. It explores the existing legal landscape and finds gaps in the relationship between discrimination and predatory lending doctrines. It then situates both disparate impact analysis and UDAAP doctrines within the broader context of balancing and burden-shifting rules in tort law and considers how this analysis might be tailored for the new algorithmic lending environment. We conclude that predatory discrimination permits consideration of two types of circumstantial evidence: evidence of disparate racial impact and evidence of unfair lending practices. But, more importantly, we conclude that because of the legacy of systemic racism and the non-transparency of algorithmic lending, unfair (predatory) practices are likely to have discriminatory impact. Therefore, regardless of the doctrinal basis of the complaint or enforcement action, a defendant should be prepared to justify its use of an algorithm by presenting evidence of both racial neutrality and fairness.

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