Wall Street’s AI Arms Race: Why Main Street Could Pay the Price

What Happened

On March 27, 2025, the U.S. Securities and Exchange Commission (SEC) hosted a roundtable in Washington, D.C., focused on artificial intelligence (AI) in the financial industry. The gathering featured regulators, tech leaders, and financial executives all wrestling with one central question: Can Wall Street be trusted to deploy powerful AI tools responsibly without firm guardrails?

The roundtable made it clear that AI is already deeply embedded in the way financial firms operate. Banks are using machine learning to detect fraud, credit decisions are becoming increasingly automated, and investment managers are relying more on algorithms to time trades and build custom portfolios.

While the technology has advanced at a rapid pace, the rules overseeing it have not kept up. SEC Chair Gary Gensler didn’t mince words when he warned of 'regulatory arbitrage,' where firms race ahead with AI adoption in areas that haven’t yet been scrutinized, simply because they can.

Financial companies and investment firms, ever eager to stay competitive, have touted AI's efficiency and scalability. However, behind the scenes, many of these models are operating as opaque systems, or 'black boxes' that can't be fully explained, even by their creators. This raises concerns when these tools are making financial decisions with real-life consequences attached.

Why It Matters

The roundtable emphasized the SEC's growing concern that AI could be the next big systemic risk in the financial world. Some have drawn parallels to the 2008 financial crisis, and there are some striking similarities. 

Back then, complex financial products like mortgage-backed securities and derivatives were poorly understood by the public and underregulated by the government. When the system finally cracked, the average American bore the brunt of the collapse.

Now, substitute synthetic CDOs for synthetic intelligence. AI is becoming increasingly difficult to untangle, and the decisions around it carry just as much financial weight. For example, when an AI model makes a recommendation, it can be next to impossible to determine the reasoning behind it.

If something goes wrong, there doesn't currently seem to be a clear path for accountability. The error could be attributed to everything from a glitch in the algorithm to a flaw in the data, or even just good old-fashioned human error.

AI systems can only be as good as the data they are trained on, and that data can reflect historical biases. This is hardly hypothetical, as there's already evidence that some AI credit-scoring models have unfairly penalized minority applicants. Without strong oversight, biased or flawed AI could quietly entrench discrimination in lending, insurance, and investing.

How It Affects You

AI is increasingly becoming a part of our everyday lives, and that includes shaping decisions that impact your finances. For example, say you apply for a mortgage and an AI system denies it based on patterns that it can't explain.

Maybe your retirement account is invested using an algorithm optimized for firm profits, instead of your long-term goals. Or maybe a high-frequency trading AI triggers a flash crash that wipes out thousands from your 401(k) in milliseconds.

Even so-called 'robo-advisors,' which are marketed as low-cost tools for retail investors, can use AI to steer clients into products that aren’t in their best interest. Without the proper regulation of these tools, users may end up paying hidden fees or even taking on far more risk than they realize. As things currently stand, when AI is wrong, there's no human face to challenge or appeal to, much less hold accountable. There's just a faceless system that shrugs.

A lack of transparency and accountability with these AI systems could widen the gap between Wall Street and Main Street. The roundtable was a step in the right direction, but it's going to take a lot more. Americans are facing a growing urgency as regulators are lagging far behind the rapid technological advancements being made in the field of AI.

This raises the risk that the next financial crisis could stem not just from human greed, but also from algorithms designed to exacerbate it. While firms race ahead to harness AI's potential, the ability of the SEC and the broader public to keep pace remains uncertain.