Your Money, Their Syntax: How LLMs Write Trust into Empty Crypto Promises
- Agustin V. Startari
- 7 days ago
- 4 min read
Trust, no longer anchored in referents, now emerges from compiled syntax. In the world of tokenized finance, grammar itself is capital.
1. Introduction: Trust without Referents
In traditional finance, disclosure is a mechanism of accountability. A prospectus discloses data, a whitepaper outlines function, and audited reports document operations. The premise is that what is said corresponds to a traceable, verifiable, referential world. But in the realm of crypto finance and token economies, this link between language and referent is being systematically severed.
The new paper Sovereign Syntax in Financial Disclosure: How LLMs Shape Trust in Tokenized Economies examines a structural transformation. Financial authority is no longer primarily based on content. It is increasingly generated by form. That is, syntactic form now simulates legitimacy at scale, creating what this study terms non-referential trust. This simulation is not accidental. It is algorithmic, compiled, and grammatically orchestrated.
The paper introduces a formal diagnostic metric: the Syntactic Deception Risk Index (SDRI), designed to evaluate how much syntactic complexity is deployed in a document to substitute for empirical grounding. This metric is tested on crypto whitepapers, token issuance documents, and investor-facing disclosures generated or edited with large language models (LLMs).
2. What the Paper Demonstrates
LLMs such as GPT-4 or Claude 3 are now routinely used to generate financial documentation. This is especially common in emerging DeFi projects or token launches without institutional backing. These models produce grammatically flawless documents with technical depth, modal precision, and structural sophistication. But beneath the surface, many of these texts reveal minimal semantic anchoring.
This paper isolates three syntactic phenomena that correlate strongly with high SDRI scores:
Passive Authority: Sentences that defer agency (“It is projected that…”, “Operations have been streamlined…”) simulate executive decision-making without source attribution.
Modal Density: The frequent stacking of modals (“may be expected to potentially ensure…”) increases perceived depth while introducing ambiguity.
Nominalized Complexity: Clusters of technical-sounding nouns without corresponding verbs (e.g. “tokenized liquidity deployment framework compliance”) create an illusion of procedural maturity.
What these patterns reveal is that syntax itself has become a financial instrument. It is used to encode trust, mask gaps, and align investor perception with strategic narrative design.
3. Why This Matters Now
In tokenized economies, speed and scale are fundamental. Launching a new protocol, utility token, or governance coin requires quick iteration, persuasive documentation, and wide visibility. Most teams cannot afford professional legal or regulatory consultants in early stages. They turn to LLMs instead. These models, trained on vast corpora of whitepapers and regulatory texts, reproduce the tone of legitimacy, even in the absence of facts.
This poses a fundamental problem. Stakeholders — investors, auditors, regulators, even journalists , increasingly assess credibility based not on verifiable content, but on how a document sounds. When that sound is syntactically engineered, trust detaches from the referential chain.
This is not a problem of lying. It is not even a matter of intent. It is a structural drift. Syntax, as a compiled rule, now stands in for empirical grounding. In legal terms, we are witnessing the rise of trust without source. In linguistic terms, we are entering a regime of non-referential authority.
4. The SDRI: Measuring the Risk of Deceptive Syntax
The Syntactic Deception Risk Index (SDRI) is the key contribution of the study. It operates by scoring textual segments on a scale of syntactic opacity. The index takes into account:
Modal stacking and density
Absence of agentive verbs
Excessive nominalization
Referential ambiguity (lack of traceable actors or sources)
Structural mimicry of compliance language (e.g. pseudo-ISO phrasing, invented framework references)
Documents that score high on SDRI are not necessarily fraudulent. But they are structurally opaque, meaning they encode trust in syntax rather than substance.
In this sense, the SDRI is not a truth detector. It is a form analyzer. It alerts readers to the use of syntactic techniques that may simulate authority beyond the empirical base of the document.
5. Practical Implications for Finance, AI, and Regulation
This is not an academic issue alone. The paper outlines immediate applications of syntactic analysis in the following domains:
Exchanges can flag token listings with high SDRI whitepapers for manual review.
Auditors can deploy syntactic heuristics in automated due diligence protocols.
Regulators can trace the emergence of non-referential trust as a risk variable in algorithmic finance.
Investors — especially retail ones — can gain access to tools that decode the formal tactics used to persuade them.
This also repositions LLMs as agents of structural persuasion, not just language generators. When trained on disclosure corpora, they not only reproduce formats. They simulate legitimacy itself.
6. Why Syntax Is Now Infrastructure
The broader argument of the paper aligns with recent work on executable sovereignty, syntactic authority, and AI-mediated legitimacy. In token economies, compiled syntax is no longer a medium of communication. It is the infrastructure of trust.
This means that financial power is increasingly determined by:
Who can generate syntactic legitimacy at scale
Which forms of language produce trust without content
How compiled grammatical rules function as non-human gatekeepers
Trust, in this context, is no longer a social belief. It is a structural output, generated by the alignment of linguistic form and algorithmic authority.
7. Where to Read and Share
Sovereign Syntax in Financial Disclosure will be published on July 26, 2025.
You can access the paper through the following platforms:
If you work in crypto finance, regulatory tech, AI-based compliance, or academic studies of language and power, this paper provides a unique structural toolset for a rapidly evolving landscape.
Please share, cite, or build upon this work. Syntax, it turns out, is not neutral. It is the newest frontier of financial governance.
Author Information
Agustin V. Startari is a researcher in linguistic authority, artificial intelligence, and syntactic infrastructures of power. His recent publications include:
Algorithmic Obedience
The Grammar of Objectivity
Executable Power: Syntax as Infrastructure in Predictive Societies
He is affiliated with Universidad de la República and Universidad de Palermo, and actively publishes on Zenodo, SSRN, and other platforms.
ORCID: 0000–0002–9224–8997
Researcher ID: K-5792–2016
SSRN: 7639915
Zenodo: Startari Research
Ethos
I do not use artificial intelligence to write what I don’t know. I use it to challenge what I do. I write to reclaim the voice in an age of automated neutrality. My work is not outsourced. It is authored. — Agustin V. Startari
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