USA LAW AND PRACTICE Contributed by: Margo H.K. Tank, Michael Fluhr, Era Anagnosti, Kristin Boggiano, David Stier, Liz S. M. Caires, Adam Dubin, Emily Honsa Hicks, Kathleen Birrane and Chezelle McDade, DLA Piper LLP
DLA Piper One Atlantic Center 1201 West Peachtree Street, Suite 2900 Atlanta, GA 30309-3449 USA Tel: 404-784-6021 Email: trina.bazarte@us.dlapiper.com Web: www.dlapiper.com
1. Fintech Market 1.1 Evolution of the Fintech Market Artificial Intelligence
ers must provide specific, accurate adverse action reasons even when using complex AI models. At the federal level, a number of Executive Orders (EOs) that bear on AI have been issued. However, importantly, in December 2025, President Trump issued another EO entitled “Ensuring a national policy framework for arti - ficial intelligence” that directs the US Attorney General to establish a task force to challenge state regulation of AI deemed burdensome. CFPB’s De-Regulation Posture The Consumer Financial Protection Bureau’s (CFPB) posture can be characterised by a significant shift toward de-regulation, and a return to formal rulemak - ing processes, while operating amidst staff reduc - tions, congressional scrutiny, and funding uncertainty. CFPB withdrew over 60 guidance documents, policy statements, and advisory opinions in 2025. As fed - eral enforcement activity recedes, state regulators will increasingly look to fill that void, and in some cases, already have. One such example is the Trump admin - istration’s CFPB retraction of an Interpretive Rule that former Director Rohit Chopra issued under the Biden administration that asserted that “digital user accounts” that permit consumers to access credit in the course of a retail purchase, such as Buy Now, Pay Later (BNPL) products, are “credit cards” under TILA, subjecting the “card issuer” (eg, BNPL provider, bank partner-originated BNPL credit, payment processor) to certain additional disclosure and substantive obli - gations. New York quickly acted to fill the void with a “BNPL Act” of its own, which represents one of the first of potentially many attempts by states to step into the perceived void left by the change in administration at CFPB.
Exponential advances in AI, particularly large language models (LLMs)/generative AI, have led to similarly exponential industry enthusiasm towards adoption of the technology. AI models are already widely used in fintech products and services. Common deploy - ments include identity verification and fraud detec - tion, underwriting and pricing (eg, credit scoring with alternative data), customer service (eg, LLM-powered chats), collections optimisation (eg, predictive models pick optimal outreach timing/channel and tailor loan repayment plans to maximise recovery), and market - ing, amongst other uses. These are the most prevalent deployments today because they generally show a clear ROI and tend to fit rigorous, documented risk management for models and data systems aligned with prudential standards used by regulated banks. Moving forward, we anticipate fintech providers to expand their use of AI in the areas of vendor and third-party risk-screening, compliance drafting and surveillance, investment portfolio advice, and in-app guidance (eg, “co-pilots”). Adoption and expansion of AI is accelerating primarily because ROI and the technologies have improved, but it is also due in small part to regulators offering clearer guardrails in some areas. While guidance is far from comprehensive, regulators have generally advised that banking, consumer protection, AML/BSA, priva - cy, and securities rules apply regardless of whether a decision is made by a human or AI. For example, for credit products, regulators have reiterated that lend -
961 CHAMBERS.COM
Powered by FlippingBook