The Rise of AI in Trading: Can the Sell Side Use It?

In the penultimate article in this series, Disruption Banking looked at some of the fears around using machines to execute buy-side trades in financial services. Buy-siders said they liked the idea of using AI to help them make financial purchases, but felt they didn’t know enough about it.

Meanwhile, on the sell side – think stockbrokers or big banks that need to flog things like securities to make money – a similarly cautionary note has been struck. It too relates to a lack of clarity around AI, though the concerns raised have been slightly different.

In today’s final instalment of our series on the rise of AI in trading that began with Python, we take a look at the how the sell side has been faring.

Murky data?

At the Sell-Side Leaders Forum hosted by Bloomberg in New York last year, “murkiness around data” was flagged as a concern.

“AI models are built on volumes and volumes of data,” Dan Bosman of TD Securities told the Bloomberg conference. “It begs the question: who owns all the data these models are being trained on, how confident are you in your data, and importantly, who owns and is accountable for what the model spits out?”

Sell-siders are in deep, with the technology just too good to refuse. “Most on the sell-side have already used artificial intelligence and machine learning models […] to process volumes of data and generate insights,” Bosman adds.

“But the reality is today’s AI models have introduced new complexities [and] aren’t necessarily as transparent, so it’s a challenge to get governance teams to understand how the model is trained and how it works.”

Fears Echoed

A December 2024 article published by Butterworths Journal of International Banking and Law cited by law firm Sidley echoed previous fears raised by the IMF of AI-provoked market volatility.

Unfortunately for sell-side AI enthusiasts, the Fund is not alone in its criticisms. “One of the primary concerns surrounding widespread adoption of advanced AI models in securities trading and investment management is their potential to undermine market stability,” says Butterworths.

Who are Butterworths, we hear you ask? Fair point, but it namechecks the Bank of England (BoE), the European Central Bank (ECB), the US Securities and Exchange Commission (SEC), and the International Organization of Securities Commissions (IOSCO) as high-profile voices expressing concern.

SEC Boss not Keen

The then SEC chair Gary Gensler, known as a crypto skeptic, has also raised an eyebrow at the use of new technologies in financial services. Back in 2020, he warned that AI’s “insatiable demand for data could lead to a convergence on a small number of dominant data providers and AI-as-a-Service companies.”

If that sounds like too much power being concentrated into too few hands, that’s precisely what Gensler was driving at. If five years ago seems like a long time in tech, it’s worth bearing in mind that his concerns are shared by the far more recent Butterworths article.

It says: “This concentration could in turn create a ‘monoculture’ in the financial system, where market participants draw from the same data and employ similar models, ultimately leading them to reach similar conclusions and investment strategies.”

Herd mentality is seldom viewed as a good thing. Although given that fundamentals of banking such as investor confidence are rooted in it, perhaps that’s an unfair criticism.

AI(ssets) Distorted?

However, a more serious problem is the impact AI could have on said herd mentality. The ECB has not been slow to warn about what it sees as the technology’s potential to distort asset prices. In May 2024 it released a financial stability review that put the machine firmly in its sights.

“The interpretation of information [by AI] may become more uniform if increasingly similar models with the same embedded challenges and biases are widely used to understand financial market dynamics,” says the ECB. “As a result, AI may make market participants’ conclusions systematically biased, leading to distorted asset prices, increased correlation, herding behaviour or bubbles.”

But the Perks are So Good!

This presents a problem for high-tech sell-siders, because AI does offer them tangible benefits. In an article singing its praises published towards the end of 2023, Nasdaq said traders had been all too keen to use it to analyze market data, build portfolios, and even generate investment ideas.

“The use of AI in trading has been gaining traction within the industry due to its ability to analyze vast amounts of data quickly and accurately, allowing it to identify patterns faster than humans could ever hope to,” it says.

Wall Street was at the forefront of this bull rush towards AI. Between 2017 and 2021, 94% of AI-related patents were filed by the five big players in investment banking – JP Morgan, Goldman Sachs, CitiGroup, Bank of America, and Morgan Stanley – according to analysis by Bettermarkets published in April 2025.

“As AI technologies are refined and new ones are developed, AI advocates highlight the potential benefits, including greater efficiency in financial services, lower costs, and better financial outcomes for clients,” it adds.

The ‘Ayes’ Have it – or Do They?

That rosy outlook notwithstanding, even the ‘yea-sayers’ have some reservations about the headlong rush towards AI sell-side trading.

“AI applications in finance also present serious risks to markets and financial stability by exacerbating existing channels of instability and creating new ones,” adds Bettermarkets.  “They are also powerful tools for investor exploitation, fraud, and other illegal conduct.”

And with the “regulatory landscape still evolving,” as the Sell-Side Leaders Forum put it, more needs to be done to protect consumers. “Companies will need to learn and listen before diving head-first into AI,” it cautions.

“AI’s growth trajectory and penetration into all corners of the financial industry demands a new approach to regulation, one that effectively incorporates agile and forward-looking regulatory frameworks and a focus on consumer protection, ethics, transparency, accountability, and financial stability,” adds Bettermarkets.

As Always, the Future is Unwritten

Any such misgivings will likely do little to arrest what can only be described as a growth industry. To recap figures quoted at the beginning of this series, the global AI market in financial services is expected to reach north of $190 billion by 2030. Bettermarkets goes further still, claiming experts put the figure at $400 billion by 2027.

But such wildly competing claims only serve to underscore one of the key concerns raised by the doubters: volatility. The old maxim “if something seems too good to be true then it probably is” has rarely seemed more applicable than it does with regards to the outlook for AI in financial trading.

One thing is for sure. The purveyors of AI financial services, such as Palantir and NVIDIA – and those who invest in their stocks – look set to make a lot of money. Whether those who use such services to make trades stand to gain or lose in the long run is another matter entirely.

#AI #FinancialServices #CapitalMarkets #MachineLearning #fintech

Author: Damien Black

The editorial team at #DisruptionBanking has taken all precautions to ensure that no persons or organizations have been adversely affected or offered any sort of financial advice in this article. This article is most definitely not financial advice.

See Also:

The Rise of AI in Trading: Buy Side Keen but Cautious | Disruption Banking

Python: the First Language of Finance? | Disruption Banking

The Rise of AI in Trading: Policing Risk | Disruption Banking

Machine Learning and the Stock Market | Disruption Banking