Financial regulation in the US significantly depends on a three-dimensional approach to regulatory compliance, CFTC Commissioner Kristin Johnson has said. She was speaking at the RegHub Summit in London, in a talk entitled “The Future of Finance: Enabling AI Tools to Enhance Compliance and Surveillance.”

Three dimensions of policing

First, she said, one could argue that our regulation has required entities operating in financial markets to police themselves. In other words, market participants must demonstrate a commitment to ensuring compliance with applicable regulations and reporting instances of disruption or compliance failures.

Second, US regulation imposes both formal and informal (soft law) requirements on firms operating as critical market infrastructure resources.

These entities, and in some instances, industry trade associations, have exercised market policing authority, appreciating that firms and industry have obligations to facilitate market stability, market integrity, and surveil markets for evidence of fraud and manipulation.

Third, financial market regulators play an important role in supervising markets and enforcing expectations regarding compliance.

Johnson said: “Our principles-based regulation includes a supervision framework where organizations that play a critical role in market infrastructure, such as exchanges and clearing organizations, engage in surveillance and report to the Commission on the compliance of intermediaries.” And within individual organizations, registered market participants are charged with supervising the actors who directly engage in trading, as well as actors who directly engage in customer solicitation.

“Relying on firms to engage in market surveillance and intermediaries to engage in supervision balances the costs and obligations of supervision,” she added.

Technology-driven surveillance

Increasingly advanced AI technologies, such as supervised and unsupervised machine learning algorithms, neural networks, generative AI and more recently agentic AI, have accelerated both interest in and adoption of AI for broader front office, back office, reporting, and supervision, and monitoring obligations that arise in financial markets regulation, Johnson observed. This takes us beyond where traditional machine learning has ever gone.

“I actively worked with the CFTC senior staff across all divisions to develop the Commission’s first request for comment (RFC) on the uses of AI in CFTC-regulated markets,” she said. The US Treasury and global international standard setting bodies are also seeking to better understand compliance and surveillance use cases.

And other industry groups and publications have broadened the CFTC’s understanding, she said. In the most recent Institute of International Finance (IIF) survey report, published in January 2025, compliance (including anti money laundering (AML) and trade surveillance) ranked in the top four predictive AI use cases for respondents.

“Successful integration of AI will require careful consideration by firms and the industry as well as thoughtful regulatory oversight by domestic and international regulators.”

Kristin Johnson, CFTC Commissioner

And Treasury’s report on Artificial Intelligence in Financial Markets reported that “AI is widely used for … AML/CFT and sanctions compliance, including analyzing large sets of data, detecting anomalies, flagging suspicious activities, and verifying customer identities under the Bank Secrecy Act (BSA) obligations.

Finally, a recent consultation report published by the International Organization of Securities Commissions (IOSCO) on AI in capital markets reports that IOSCO members and self-regulatory organizations (SROs) observed that market participants are using AI to enhance the effectiveness of AML and combating the financing of terrorism (CFT) measures, including to identify suspicious transactions.

“For AML compliance, customer onboarding, and due diligence, respondents observed that market participants use ML models to perform pattern recognition and anomaly detection in surveillance software. They also use NLP [natural language processing] to enhance the interpretation of unstructured data and to facilitate name screening and news analysis,” IOSCO reported.

AI and trade surveillance

The obligation to surveil one’s trades, transactions, and workforce more generally (among other things) is embedded right in CFTC rules.

CFTC Rule 38.156 and Rule 38.604 of Section 5 of the Commodity Exchange Act (CEA) set forth core principles for designated contract markets (DCMs) that require DCMs to “establish, monitor, and enforce” compliance with a DCM’s rules and to establish and enforce certain rules and procedures to ensure financial stability of transactions on the DCM.

The rules outline the core requirements related to surveillance, mandating that any designated contract market must monitor members’ compliance with the designated contract market’s minimum financial standards. This means they routinely receive and promptly review financial and related information from its members, as well as continuously monitor the positions of members and their customers

Similarly, Section 5h establishes compliance with rules and financial integrity as core principles for swap execution facilities (SEFs), and implementing rules include requirements on SEFs to maintain an automated trade surveillance system pursuant to CFTC Rule 37.203 as part of their required rule enforcement program.

These rules provide the bedrock principles of ongoing monitoring and reporting that is required, but IOSCO advocates for more partnerships to enhance these capabilities – the creation of “joint systems that can be used by multiple financial institutions to share data and intelligence to mitigate types of threats utilizing AI and other technologies.” Johnson agrees, and she said inter-governmental collaboration with other financial market regulators in the US and globally would also be quite helpful.

Parting remarks

In the context of AI, Johnson believes there is significant potential for these technologies to enhance the three-dimensional approach to regulation and compliance.

“Successful integration of AI will require careful consideration by firms and the industry as well as thoughtful regulatory oversight by domestic and international regulators,” she said. It will just round out the few hundred years of a journey to create a sound regulatory framework in the US on which the US has embarked.