Before we embark on tokenizing U.S. equities, it's crucial to have compliance systems that understand context rather than merely adhering to checklists. Investor Michael Burry has raised concerns, and so should we, argues Chamarajnagar.
By Dr. Ravishankar Chamarajnagar|Edited by Betsy FarberUpdated Jun 23, 2026, 2:08 p.m. Published Jun 23, 2026, 2:01 p.m. 5 min readMake preferred on ShareShare this articleCopy linkX (Twitter)LinkedInFacebookEmailMake preferred on U.S. SEC headquarters in Washington (Jesse Hamilton/CoinDesk)Having spent two decades developing systems that transitioned from reactive to cognitive—first at VMware focusing on mobile device security and now in compliance for digital asset markets—I recognize that mere rule-following does not equate to disaster prevention. Consequently, when the SEC postponed its initiative to permit tokenized U.S. stocks last week, my immediate response was one of relief, not annoyance. Investor Michael Burry, who famously predicted the 2008 financial crisis, promptly cautioned that this initiative could lead to systemic risks. He is correct, though not for the reasons commonly assumed.
The core issue lies not in the concept of tokenization itself but in the fact that we are on the verge of tokenizing some of the world’s most liquid markets using outdated compliance systems that are ill-equipped for real-time operations. Presently, there exists a one to two-day delay between the execution of a trade and its complete settlement. As we advance towards real-time execution, it is imperative that we implement compliance frameworks capable of assessing trades instantaneously, particularly those involving tokenized U.S. equities.
Recent events have illustrated that fraud often occurs prior to these transactions.
Consider the Lazarus Group's manipulation of Tornado Cash and the Ronin Bridge. Were any sanctioned wallets detected? No. Were any prohibited tokens found? All clear. Was protocol compliance flawless? Absolutely.
Yet, a staggering $600 million was lost through wallet-hopping across various jurisdictions, evading the grasp of earlier systems that lacked contextual understanding.
FTX adhered to regulations until customer funds were mixed improperly. The oracle for Mango Markets was compromised while remaining compliant with protocols.
Fraud transpired in the context, rather than through the code itself.
As a CEO in digital asset markets, I have observed how tokenization has revolutionized global financial centers. Real estate in Dubai has been tokenized via a special-purpose vehicle in the Cayman Islands, sold through a platform in Singapore, funded by global DeFi liquidity, and purchased by investors from around the world. Every jurisdiction's regulations were adhered to, every wallet was verified, and every token was compliant.
However, can we ensure the security of such transactions for a retail investor in Ohio? They are left uncertain. Perhaps an institutional compliance team could ascertain this. Yet, the most troubling aspect is the inability to even pose this question to current systems. They merely check boxes; they lack critical thinking.
What Cognitive Compliance Entails
The transition from paper-based markets to AI-assisted compliance took a decade. The leap from AI-assisted to cognitive compliance must occur within the next 24 months, or tokenized equities may become the largest target for financial attacks in history.
To safeguard retail investors and markets, the following is essential:
1. Multi-source Regulatory Intelligence:
We need more than static sanctions lists; we require real-time updates on enforcement actions, geopolitical developments, and regulatory guidance. By the time OFAC adds a sanctioned entity, the funds have already moved. Systems must be proactive rather than reactive.
2. Relationship Graph Context:
It’s not enough to analyze a wallet; we must investigate the owner, custodian, exchange connections, asset holdings, and jurisdictional influence—essentially the entire entity graph. Relying on a single data point is merely compliance theater. Retail investors lack the capability to construct these graphs; the system must do this.
3. Behavioral and Pattern Intelligence:
Systems should be able to identify sudden transaction surges, new jurisdictions, altered thresholds, and rapid asset accumulation, even when these actions are not illegal. This is crucial for detecting manipulation before retail investors suffer losses.
4. Adaptive Risk Scoring:
Static regulations cannot keep pace with T+0 settlement and continuous markets. Risk scores need to be adjusted in real-time according to global events and threats, not merely afterward.
My confidence in this capability stems from my experiences of having witnessed it three times.
At VMware, endpoint management evolved from basic device tracking to a cognitive security infrastructure. We began with mobile devices, then expanded to tablets, and finally included IoT devices—sensors, wearables, industrial tools, and medical apparatus. Each new device brought unique attack vectors and integration challenges.
The systems that thrived were not those that simply added rules for each device type; they became cognitive. They learned to comprehend the environment rather than merely enforce compliance. For instance, if a hospital sensor suddenly began communicating with external servers, the rules might permit it, but the context would indicate a security breach.
A similar transformation occurred in cloud infrastructure. AWS and Azure moved away from treating every workload as a generic compute task and began to understand what those workloads actually did, including the AI models they executed, their integration needs, and the security measures required. Cloud platforms now anticipate resource demands and identify unusual behaviors not because someone wrote additional rules, but because systems gained contextual intelligence.
Identity management followed this same trajectory. Certificate lifecycle management progressed from mere expiration date tracking to a deeper understanding of machine identities: servers, devices, non-human entities, and AI agents. The focus shifted from "is this certificate valid?" to "does this identity's activity pattern align with its intended purpose?"
The consistent trend is the evolution of systems from rule-checking to contextual understanding, from reactive to predictive, and from AI-assisted to cognitive.
Compliance represents the final crucial component necessary for this evolution, and we are running out of time.
The Timeframe is Short
If the U.S. wishes to retain its status as the epicenter of global finance, we must cease viewing tokenization as a foregone conclusion and begin treating compliance readiness as an urgent priority.
We have a window of 12-24 months to develop systems capable of assimilating regulatory intelligence from multiple sources simultaneously, mapping comprehensive entity-relationship graphs in milliseconds, identifying behavioral anomalies across jurisdictions, and dynamically adjusting risk models to reflect actual conditions.
Without these functionalities, we cannot safeguard retail investors who lack the means for forensic compliance teams.
Elements of this framework currently exist within pattern recognition systems, transaction monitoring tools, and risk management engines. However, no one has yet integrated them into a cohesive cognitive compliance structure.
The technology is available. The question is not can we achieve this, but will we do so before the next crisis hits.
The alternative? We might tokenize U.S. equities using compliance infrastructure from 2019, leaving retail investors exposed and making the downfall of FTX appear minor in comparison.
Regulations will always lag behind innovation; that’s a characteristic of democratic systems. However, technology need not follow the same pattern.
We can construct compliance systems that surpass the rules they enforce—systems that grasp context, identify patterns, and think beyond mere checkboxes. Such systems would protect the investors who need it most, not just those capable of hiring compliance teams.
Michael Burry foresaw the 2008 crisis because he scrutinized the system, not just the regulations. The rules indicated that subprime mortgage bonds were rated AAA. The system revealed their toxicity.
Tokenized securities devoid of cognitive compliance could lead to our next subprime crisis.
The SEC has granted us additional time. We must not squander it.
SECNote: The views expressed in this column are those of the author and do not necessarily reflect those of CoinDesk, Inc. or its owners and affiliates.
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CEX Volumes Drop to Lowest Since September 2024 as RWA Perps Hit Record High
CEX Volumes Drop to Lowest Since September 2024 as RWA Perps Hit Record High
In May, combined exchange volumes fell 3.45% to $4.41T; the lowest since September 2024. RWA perpetual futures volumes rose 10.4% against the trend, hitting a new all-time high.
By CoinDesk ResearchJun 15, 2026In May, combined exchange volumes fell 3.45% to $4.41T; the lowest since September 2024. RWA perpetual futures volumes rose 10.4% against the trend, hitting a new all-time high.
Why it matters:
In May, combined exchange volumes fell 3.45% to $4.41T; the lowest since September 2024. RWA perpetual futures volumes rose 10.4% against the trend, hitting a new all-time high.
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