On September 24, 2021, a panel moderated by Jason Cover of Troutman Pepper LLP and consisting of Consumer Financial Protection Bureau (“CFPB”) Senior Counsel Albert Chang, Stephen Hayes of Relman Colfax PLLC, Capital One Fair Lending Assistant General Counsel, Brian Larkin, and JPMorgan Chase Head of AI Research, Manuela Veloso, explored the potential implications for fair lending, consumer protection, and other pitfalls related to digital targeted marketing in light of recent regulatory activity and private litigation.
The panel defined “digital targeted marketing” as a form of marketing by which advertisements are disseminated through a variety of online platforms including web services, paid searches, banners, and social media using sophisticated data analytics that effectively preselect a precise target audience. This can occur through ”self-selecting” programs, which allow the advertiser to choose participant criteria using a platform’s pre-existing categories and attributes, or through “look alike programs,” which use the advertiser’s existing customer data to find similar potential customers, generally using machine learning that identifies predictive attributes.
Advertisers conducting digital targeted marketing may use both internally sourced data or data purchased from companies involved in the gathering or storing of large amounts of data for analytic use. Advertisers often use artificial intelligence and machine learning to sift through data to identify patterns, connections, and likely outcomes. The outcomes can be predictive and allow accurate identification of interested and qualified consumers. However, the use of certain attributes—despite being highly predictive—may implicate fair lending laws intentionally or unintentionally by directly or indirectly excluding consumers on prohibited bases. Panelists highlighted that the advantages of machine learning in these areas can eliminate human bias, and that the risks that surround this area are similar to those in the space of pre-screened offers and traditional targeted marketing.
The panel identified certain regulatory activity and litigation against Facebook as illustrative of the fair lending risks that may be applicable to consumer finance platforms. Notably, the panel indicated that this ongoing regulatory activity and litigation are based on a number of different theories of discrimination, and that while some have been settled, there have been pervasive issues of standing and many actions have not reached decisions on the merits. Examples of Facebook’s regulatory activity and litigation in this area include:
- A Washington State Attorney General (“AG”) investigation into digital targeted marketing practices. Of note, the AG alleged that Facebook allowed advertisers to exclude particular ethnic groups from certain advertisements and provided tools allowing advertisers to exclude members of protected classes.
- An alliance of consumer groups brought suit alleging discriminatory practices that resulted in a $5 million settlement that also required changes to Facebook’s “look alike” campaigns impacting housing, employment, and credit products.
- A Department of Housing and Urban Development Charge of Discrimination in violation of the Fair Housing Act; specifically alleging that Facebook allowed housing advertisers to use prohibited bases to target audiences, and that ad-delivery algorithms were independently discriminatory.
- A civil suit in California’s Northern District alleging violations of the Fair Housing Act, Equal Credit Opportunity Act, and the California Fair Lending Laws.