In a recent development, Gary Gensler, the chairperson of the U.S. Securities and Exchange Commission (SEC), shed light on the SEC’s innovative approach toward enhancing its surveillance mechanisms.
Gensler’s Disclosure: The AI Advantage
During a Senate oversight hearing on September 12, Gensler confirmed that the SEC is harnessing the power of artificial intelligence (AI) to scrutinize the financial sector, with a particular focus on identifying fraudulent and manipulative activities. While Gensler had earlier hinted at the potential integration of AI technologies in a speech at the National Press Club on July 17, the specifics of its deployment remained under wraps until this revelation.
SEC’s Vision for AI: A Glimpse into the Future
Senator Catherine Cortez Masto’s inquiry into the SEC’s envisaged application of AI elicited a forthright response from Gensler. He elucidated: “Indeed, we’re tapping into AI for market surveillance and specific enforcement initiatives. We’re keen on spotting market patterns. This technological embrace is also a driving factor behind our appeal to Congress for an augmented funding in 2024, as we aim to further bolster our tech resources for next-gen solutions.”
A Surprise Revelation?
While the SEC’s adoption of AI tools as part of its operational framework isn’t particularly shocking, the absence of an official public statement on this topic does raise eyebrows. That said, one must consider that apart from the cybersecurity incident reporting mandate introduced by President Biden in 2022, there are no explicit legal directives mandating U.S. agencies to disclose their internal technological adoptions.
Delving Deeper: The Nature of AI Utilized
The exact type of AI being harnessed by the SEC remains shrouded in mystery. However, given the SEC’s multiple analytical reports highlighting the utilization of AI and algorithm-driven trading by financial market participants, it’s plausible that they might be employing advanced machine learning systems. These systems are adept at analyzing vast data troves to pinpoint deviations.
