At the Online Lending Policy Institute’s (OLPI) annual summit in Washington, D.C. earlier this week, the OCC’s recent decision to accept applications from non-depository financial technology firms for a special purpose national bank (SPNB) charter was the focus of considerable discussion.
The summit speakers included Grovetta Gardineer, the Senior Deputy Comptroller for Compliance and Community Affairs at the OCC. Comments made by attendees indicated that there is substantial interest in the SPNB charter but a reluctance to be the first applicant due to concerns about litigation risk and regulatory requirements. After the OCC announced its decision to accept applications, the Conference of State Bank Supervisors (CSBS) announced that it would again pursue litigation challenging the OCC’s recent decision. While the CSBS has not yet filed another lawsuit and there is speculation that it is waiting until the first SPNB charter is granted to do so, a second lawsuit challenging the OCC’s authority to issue SPNB charters was filed last month by the New York Department of Financial Services (DFS) in New York federal district court. (For an analysis of the DFS lawsuit, click here.)
In her remarks and responses to questions, Ms. Gardineer indicated that, although the Community Reinvestment Act does not apply to non-depository institutions, financial inclusion commitments from the SPNB charter applicant will be required and be subject to scrutiny by the OCC. Questions directed at Ms. Gardineer raised concerns about the application of bespoke capital, liquidity, and risk management requirements for SPNB charter applicants. And in response to questions about the charter’s implications for Federal Reserve requirements and access to Federal Reserve services, Ms. Gardineer indicated that the Federal Reserve was considering these issues and that they were the subject of ongoing discussions between the OCC and Federal Reserve.
Paul Watkins, recently named by CFPB Acting Director Mulvaney to serve as Director of the Bureau’s Office of Innovation, was also a speaker at the summit. Mr. Watkins was formerly in charge of fintech initiatives in the Arizona Attorney General’s office, and Arizona is the first state to create a “regulatory sandbox” that allows new financial technologies and products to be tested in a controlled environment with reduced regulatory risk. Mr. Watkins discussed the CFPB’s proposal to revise its Trial Disclosure Policy and suggested that the program could be used to address a broad range of issues. For example, Mr. Watkins noted that a trial disclosure could be used to address challenges faced by creditors in supplying reasons for an adverse action where a decision is made through artificial intelligence or mechanical learning. Mr. Watkins indicated that the CFPB’s no-action letter policy may also be subject to review by the Bureau. Taken together, the trial disclosure and no-action letter policies appear to be the CFPB’s tools of choice for advancing its efforts to facilitate innovation that might be unduly limited by regulatory constraints.
A third summit speaker was Maria Vullo, DFS Superintendent. Ms. Vullo expressed concern regarding the risks that “regulatory sandboxes” and trial disclosures can create for consumers where they are used for products and services actually offered in the marketplace rather than in a mock setting. She also expressed concern about the potential for alternative data used in credit decisions to serve as a proxy for prohibited characteristics and suggested that an ability to repay standard should apply to all consumer credit and not be limited to mortgages and credit cards.
Finally, Adam Maarec, Of Counsel in Ballard’s D.C. Office, participated in a panel on data, privacy, and fraud prevention policy. The panelists discussed the California Consumer Privacy Act’s potential application to financial institutions as a result of shortcomings in the exception for information “collected, processed, sold, or disclosed pursuant to” the Gramm-Leach-Bliley Act. They also discussed ways for companies to manage the tension between data minimization and artificial intelligence/machine learning priorities, the latter of which depends on the accumulation of large data sets to identify insights.