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Gary Gensler confirms SEC’s use of AI for financial surveillance

The chair’s comments came in response to a query from Sen. Catherine Cortez Masto during a Senate oversight hearing.

United States Securities and Exchange Commission (SEC) Chair Gary Gensler testified on Sept. 12 in a Senate oversight hearing that his agency was currently using artificial intelligence (AI) technologies to monitor the financial sector for signs of fraud and manipulation. 

Gensler gave a public speech before the National Press Club on July 17 wherein he laid out the case for integrating AI technologies into the SEC’s surveillance scheme, but until now, the agency’s explicit use of the tech hadn’t been made public knowledge.

When asked by Sen. Catherine Cortez Masto how he envisioned the SEC using AI, Gensler responded:

“So, we already do. In some market surveillance and enforcement actions. To look for patterns in the market. … It’s one of the reasons why we’ve asked Congress for greater funding this year, in 2024, to help build up our technology budget for the emerging technologies.”

While it shouldn’t come as a surprise to note that the SEC is utilizing AI technologies during the normal course of its operations, it is somewhat surprising that the agency hasn’t issued a formal, public declaration detailing its use.

However, it is worth noting that aside from the requirement to report cybersecurity incidents signed into law by President Biden in March of 2022, there don’t appear to be any legal requirements in the U.S. for agencies to publicly report the internal use of new technologies.

Related: How artificial intelligence can impact supply chains and logistics

Based on the description given by Gensler, it’s unclear exactly what form of AI the agency is using. However, the SEC has filed numerous analysis reports on the use of AI and algorithmic trading by actors within financial markets.

It would make sense for the agency to similarly employ machine learning algorithms capable of parsing large amounts of information for anomalous data.



via cointelgraph.com

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