In the penultimate article in this series, Confusion Bank looked into some of the horrors surrounding the use of machines to carry out buy-side transactions in financial services. Buy-Siders said he liked the idea of using AI to help with financial purchases, but he felt he didn't know enough about it.
On the other hand, on the selling side, consider a large bank that needs to whip things like stockbrokers and securities to make a big money. Equally careful is being paid. The concerns raised are slightly different, but it is also related to the lack of clarity around AI.
In the final article in today's series on the rise of AI in trading that began in Python, we'll see how the sales side is moving forward.
Ambiguous data?
Last year, the “Murkiness Aursion Data” was flagged as a concern at the Seller Leader Forum hosted by Bloomberg in New York.
“AI models are built on volumes and volume data,' Dan Bossman Of TD Securities, he spoke to the Bloomberg Conference. “Questions ask. Who is responsible for all the data these models are trained, how confident you are in your data, and, importantly, what the models spit out?”
Cellsiders are deep and technology is too good to reject. “Most of the sell side already uses artificial intelligence and machine learning models. […] Bossman adds.
“But the reality is that today's AI models have introduced new complexities. [and] It's not always transparent, so understanding how the model is trained and how it works in a governance team is a challenge. ”
The fear echoed
An article published in December 2024 Butterworths Journal of International Banking and Law Sidley, cited by the law firm, reiterated the previous horrors raised by the IMF of AI-inducing market volatility.
Unfortunately, for sell-side AI enthusiasts, the fund is not alone in criticism. “One of the key concerns surrounding the widespread adoption of advanced AI models in securities trading and investment management is the possibility of undermining market stability,” says Butterworths.
Who is it? Butterworthdo we hear you ask? Although it is a fairpoint, it has named the Bank of England (BOE), the European Central Bank (ECB), the US Securities and Exchange Commission (SEC), and the International Securities Commission (IOSCO) as well-known voices expressing concern.
Sec Boss is not enthusiastic
SEC chair at the time Gary Genslerknown as a crypto skeptic, raised eyebrows through the use of new technologies in financial services. In 2020, he warned that AI's “insatiable demand for data could lead to the convergence of a small number of dominant data providers and AI-As-A-Service companies.”
If it sounds like too much force is concentrated in the hands of too little, then that's exactly what Gensler was driving. If it seems like a long time of high tech five years ago, it's worth keeping in mind that his concerns are shared much more recent concerns Butterworth article.
It says: “This concentration could create a “monoculture” in the financial system. Market participants will draw from the same data and adopt a similar model, eventually reaching similar conclusions and investment strategies.. ”
The herd mentality is rarely considered a good thing. It is probably an unfair criticism given that banking fundamentals such as investor trust are rooted in it.
Is AI (SSEST) distorted?
However, a more serious problem is the impact of AI on the way the herds think above. The ECB is not too late to warn about what is considered a potential technology that distorts asset prices. In May 2024, we released a financial stability review that clearly shows the machine.
“Interpretation of information [by AI] Increasingly similar models with the same built-in challenges and biases can be more uniform when used widely to understand financial market dynamicsThe ECB says. ”As a result, AI systematically biases market participants' conclusions, which can lead to distorted asset prices, correlations, herd behavior, or air bubbles.”
But the perks are very good!
This presents the problem to high-tech ciders as AI offers specific benefits. In a complimentary article released towards the end of 2023, NASDAQ said that traders were keen to use it to analyze market data, build portfolios and generate investment ideas.
“The use of AI in trading has gained traction within the industry thanks to its ability to quickly and accurately analyze huge amounts of data, allowing humans to identify patterns faster than humans would like.“I say it.
Wall Street was heading towards AI at the forefront of this bull rush. Bettermarkets' analysis issued in April 2025, 94% of AI-related patents were submitted by JP Morgan, Goldman Sachs, Citigroup, Bank of America, Morgan Stanley (JP Morgan, Goldman Sachs, Citigroup, Bank of America, Morgan Stanley).
“As AI technology refines and new technologies are developed, AI advocates highlight potential benefits, including improving financial services efficiency, reducing costs, and improving client financial outcomes.“Add.
Does “ayes” have that?
Despite its rosy outlook, even “Yes” have some reservations about a head-on rush towards AI sell-side deals.
“Financial AI applications pose serious risks to market and financial stability by exacerbating existing instability channels and creating new ones“Add a better market.” ”It is also a powerful tool for investor exploitation, fraud and other illegal activities.. ”
and”The regulatory environment is still evolving“As the sellside leader forum said, more needs to be done to protect consumers.”Companies need to learn and listen before heading towards AI,” that warns.
“AI's growth trajectory and penetration into all corners of the financial industry requires a new approach to regulation. It effectively incorporates an agile, future-looking regulatory framework and focuses on consumer protection, ethics, transparency, accountability and financial stability.add a better market.
As always, the future is not written
Such anxiety will do little to arrest what can only be explained as a growth industry. To summarise the numbers quoted at the beginning of this series, the global AI market for financial services is expected to reach $190 billion north by 2030.
However, such fierce and competing claims only help highlight one of the important concerns raised by the suspicious people: volatility. “If something seems too good, perhaps,” the old saying didn't seem to be more applicable than with regard to the AI outlook in financial transactions.
One thing is certain. Providers of AI financial services such as Palantir and Nvidia, as well as those who invest in stocks, are set up to make a lot of money. Whether or not a person using such services is winning or losing in the long term is a whole other matter.
#ai #financialservices #capitalmarkets #machinelearning #fintech
Author: Damien Black
The #DisuptionBanking editorial team takes all precautions in this article to ensure that people or organizations are not being affected or provided financial advice. This article is definitely not financial advice.
reference:
The rise of AI in trading: buy sharp but careful aspects | Confusing banking
Python: Finance's primary language? |Confused Banking
The rise of AI in trading: Policing risks | Confusion banking
Machine Learning and Stock Markets | Confusing Banking
