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Artificial Intelligence has significantly impacted the financial sector in recent years, offering a variety of tools for analyzing trends and optimizing investment strategies. As the technology evolves, investment platforms are likely to become more and more reliant on AI models. According to Securities and Exchange Commission Chief Gary Gensler, this could create significant issues for the stock market.
The Herding Effect
In a recent discussion as part of The Messenger AI Summit, Gensler advised against relying too heavily on generative AI in the financial sector. He pointed out the problems that may arise if many financial firms use only a couple of specific AI models for their trades and financial decisions.
Gensler explained that because creating these large AI models is a complex process, it is likely that multiple firms will use just a few models. In particular, smaller asset managers may not have the resources to develop their own models and will instead end up relying on models made by others.
Once the industry gets to the point where many firms follow the same guidance and make the same decisions, Gensler warned that a “herding effect [could] drive us off an inadvertent cliff.” If AI predictions lead too many firms to sell at the same time, the market could nosedive.
Ongoing Concerns
This is not the first time that Gensler has made this prediction. In 2020, he co-wrote a research paper titled “Deep Learning and Financial Stability,” outlining how deep learning could lead to uniformity in the market.
According to the paper, deep learning, a subset of Artificial Intelligence, brought a significant shift from traditional methods of financial analysis. It introduced unprecedented predictive capabilities, offering enhanced efficiency, greater financial inclusion, and improved risk management.
However, Gensler and co-author Lily Bailey noted the potential challenges that would come with the widespread adoption of deep learning and AI. They predicted that increased uniformity, interconnectivity, and regulatory gaps would emerge over time. They outlined the ways that these changes could introduce fragility into the financial system and pose risks to the broader economy.
An important takeaway of their research was the idea that current regulatory frameworks in the financial sector, established in an earlier era of data analytics technology, would not be ready to address the systemic risks associated with the widespread adoption of deep learning in finance. We are seeing the results of this regulatory gap now, as the SEC scrambles to set up rules to govern AI.
The right policy tools could help mitigate the systemic risks posed by the widespread use of AI in the financial industry. However, agreeing on what those tools are is a challenge that governments around the world are still working on.
Mixed Opinions
Expert opinions on the likely effect of AI on the stock market are mixed. While many different scenarios that could lead to a financial crash have been imagined, there is little hard evidence yet to support them because the technology is still new.
Richard Gardner, CEO of fintech firm Modulus, shared his concerns about over-reliance on AI in an interview with AI Business. "In terms of finance, if there's one AI operator that stands out above the rest – an industry standard that most firms use – then if that system is breached, or if there are innate flaws within its programming, there could be widespread implications that eventually create a domino-like catastrophe," he explained.
On the other hand, proponents of financial AI point to the long-standing presence of predictive technologies in the industry. "Much of the public stock market is already dictated by incredibly sophisticated hedge funds that use incredibly complex systems that rely on AI and machine learning models to inform their trading strategies," argued Vince Lynch, CEO and founder at IV.AI, in a separate interview. In other words, finance professionals have been taking advantage of the benefits provided by AI for some time now.
Conclusion
There is no doubt that evolving AI technologies will continue to have a significant effect on the finance industry, among others, but experts are divided on the form that impact will take. The path forward requires a delicate balance — harnessing the benefits of AI while safeguarding against unintended consequences that could disrupt financial markets. As more evidence emerges, regulators will need to adapt the frameworks that govern the use of AI. For investors, it is advisable to watch the market carefully as new technologies and new regulations emerge.
Sources
SSRN: Deep Learning and Financial Stability
This article was originally published in Certainty News.
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