Richard Golian

1995-born. Charles University alum. Head of Performance at Mixit. 10+ years in marketing and data.

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Richard Golian

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AI, Algorithmic Trading, and Systemic Risk to Financial Stability

How high-frequency algorithms, automated cyberattacks and AI market manipulation could destabilise banks and markets
Richard Golian
Richard Golian · 2 726 reads
Hi, I am Richard. On this blog I share my thoughts, not investment advice. This is not a recommendation to buy or sell securities.

It is Friday, 3:55 a.m. I lie awake in the dark, unable to shake off a troubling thought. What if what we consider technological progress is merely the prelude to massive chaos? What if we are only weeks or months away from the moment when new technologies, in the wrong hands, test the fragility of banks, stock exchanges, pension funds, and other financial institutions? What if one morning we wake up to find our savings app showing a balance of zero? What if an ATM simply tells us there is nothing in our account?

Perhaps it sounds exaggerated. To me, it does not. In fact, I believe the probability of something like this happening is alarmingly high. We trust banks to safeguard our savings. We trust markets to operate according to established rules. We trust that when we wake up, the world will continue functioning. But I am not sure there are enough reasons for such faith.

Automated Cyberattacks on Banks and Exchanges

I imagine a scenario where someone, or something, identifies a vulnerability in the global financial system. AI capable of launching complex cyberattacks faster than any human could press a key. Within seconds, banking networks could collapse. Trading platforms could become flooded with commands designed to create chaos. People would wake up to a world where their accounts might no longer exist, and markets stand paralyzed.

Algorithmic Trading, Flash Crashes, and Market Manipulation

More scenarios race through my mind. What if AI exploits algorithmic trading to engineer artificial crises? It is not far-fetched. Today’s markets are dominated by algorithms that react in milliseconds. This is high-frequency trading, and the danger is not hypothetical: the 2010 Flash Crash briefly erased close to a trillion dollars in market value within minutes before prices recovered. A single misleading report, “accidentally” published, or a few fabricated charts could trigger a market crash, causing losses in the billions and eroding the trust upon which everything rests.

Picture this: AI-generated content distributed by AI-generated influencers on social media, while algorithms powered by the same AI trade on global exchanges. We would face a force capable of manipulating the entire world while simultaneously profiting from those manipulations. Wake up!

Collapse of Digital Currencies and Blockchain Systems

Some believe that digital currencies and blockchain technology are immune to such threats. They are mistaken. AI could find ways to compromise even these systems. Coordinated attacks capable of forcing blockchain networks to manipulate transactions would destroy trust in digital assets. The world would watch as billions in value evaporate into thin air.

Can These Systemic Risks Be Defended Against?

I asked a generative AI about possible measures for prevention and defence. Its response only confirmed my own fears: the measures are simply inadequate. Honestly, I cannot currently envision how to establish something that would genuinely inspire trust, a trust that, at this moment, feels more like an illusion than reality.

If AI falls into the wrong hands, it could mark the beginning of the greatest financial crisis humanity has ever experienced. This threat is not hypothetical. It is real, growing, and potentially devastating.

Disclaimer

This article is intended for informational and educational purposes only. It does not constitute financial advice, a recommendation to buy or sell any securities, or a guarantee of future market performance. The views expressed are solely those of the author, who may also be an investor. Investing in financial markets involves risk, and each reader should make their own decisions independently and, if necessary, consult with a licensed professional.

Summary

Automated cyberattacks on banking networks faster than any human response. Market manipulation through AI-generated fake content. Coordinated attacks on systems assumed to be secure. When I asked AI about defensive strategies, it told me current safeguards are inadequate. This threat is neither hypothetical nor distant.

Common questions on this article's topic

Could AI launch cyberattacks on banks and financial institutions?
Yes. The U.S. Treasury Department has explicitly recognised AI-powered cyberattacks on financial institutions as an emerging threat. AI-enabled campaigns can compress the time from initial access to data exfiltration to roughly 25 minutes, around 100 times faster than the typical two-day median, according to Palo Alto Networks Unit 42. In the article, the scenario of banking networks collapsing within seconds is presented as a realistic possibility, not science fiction.
How could AI manipulate financial markets?
In the article, the scenario involves AI exploiting algorithmic trading, which dominates modern markets and reacts in milliseconds, by generating misleading reports or fabricated data to trigger automated sell-offs. This is consistent with documented flash crash risks: the IMF confirmed in 2024 that AI and generative AI are contributing to increased capital market volatility. A single AI-generated false signal could cascade through interconnected algorithmic systems.
Are blockchain and digital currencies safe from AI attacks?
No. In the article, this assumption is directly challenged. Over 1.4 billion dollars in crypto assets were stolen or lost through attacks in 2024 alone. AI-specific attack methods include automated phishing targeting exchange users, smart contract vulnerability scanning, and brute-force attacks on passwords and seed phrases using AI-optimised pattern recognition. The belief that blockchain is immune to such threats is described as mistaken.
Are current financial cybersecurity defences adequate?
According to major financial regulators, no. The ECB describes cybersecurity as an arms race where it is currently difficult to assess who holds the upper hand. The Financial Stability Board has identified third-party dependencies, model risk, and generative AI fraud as key vulnerabilities. The BIS Innovation Hub launched Project Raven, which uses AI to help authorities assess the cyber-security and resilience maturity of their financial systems. In the article, asking AI itself about defensive measures only confirmed these fears.
Could AI create fake financial influencers to manipulate markets?
In the article, this is described as a convergence of threats: AI-generated content distributed by AI-generated influencers on social media, while algorithms powered by the same AI trade on global exchanges. This would create a force capable of manipulating public sentiment and profiting from that manipulation simultaneously. Deloitte has projected that generative AI could drive U.S. fraud losses from 12.3 billion dollars in 2023 to 40 billion by 2027.
How likely is a major AI-driven financial crisis?
In the article, the probability is described as alarmingly high. The threat is characterised as not hypothetical but real, growing, and potentially devastating. Every component of the scenario, AI cyberattacks, algorithmic market manipulation, blockchain vulnerabilities, and inadequate defences, is already documented by financial regulators including the FSB, ECB, and BIS. The question is not whether these capabilities exist, but when and how they will be used.
What is a flash crash, and could AI cause one?
A flash crash is a very rapid and usually brief collapse in asset prices, driven by automated trading rather than human decisions. The best known example is the 2010 Flash Crash, when major U.S. indices briefly lost close to a trillion dollars in value within minutes before recovering. Because AI systems now execute a large share of trades and react in milliseconds, a single false signal can cascade through interconnected algorithms and amplify such an event. In the article, this is precisely the mechanism I describe.
What is algorithmic and high-frequency trading?
Algorithmic trading means using computer programs to place orders automatically according to predefined rules. High-frequency trading is an intensive form of it, executing very large numbers of orders in fractions of a second, and together they dominate modern equity markets. The concern in the article is that when many AI-driven algorithms react to the same signal at once, they can herd in the same direction and destabilise prices faster than any human can intervene.
What is systemic risk in the financial system?
Systemic risk is the danger that the failure of one part of the financial system spreads and threatens the stability of the whole. Regulators including the Financial Stability Board, the ECB and the Bank of England have warned that AI can increase systemic risk through model convergence, opacity and speed. In the article I argue that AI concentrates several of these vulnerabilities at once, which is why the threat to financial stability is not hypothetical.
Richard Golian

If you have any thoughts, questions, or feedback, feel free to drop me a message at mail@richardgolian.com.

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