When AI Gets It Wrong, the Consequences Aren't Small.
Risk:
A hallucinated number cascades through projections and misleads investors.
Risk:
A fabricated citation ends professional careers.
Risk:
An unverified computation restates earnings.
Spreadsheet & Arithmetic Crisis
Almost 90% of business spreadsheets contain errors. When LLMs perform arithmetic probabilistically, they introduce numerical hallucinations that cascade through financial projections—derailing fundraising and misleading investors.
A $6.2 billion JPMorgan trading loss was historically attributed to a spreadsheet error. Standard LLMs magnify this risk across runs.
Citation Sanctions Crisis
AI hallucination cases in legal filings are scaling globally. Courts are sanctioning attorneys weekly for submitting fabricated precedents, false legal reasoning, or unverified quotes generated by autonomous agents.
Sanctions range from $5,000 to $31,000 per incident, alongside suspension and disbarment. Under ABA Formal Opinion 512 (2024), verification is a minimum competence obligation under Rule 1.1.
Restatement & Compliance Crisis
The average market cap impact of a financial restatement exceeds half a billion dollars. Yet, zero production financial MCP servers exist—every enterprise currently using Claude or GPT models for financial analysis remains highly exposed.
SEC AI disclosure guidance (2024) creates immediate regulatory urgency for verifiable, auditable financial computation streams.
Separation of Concerns: Reason vs. Compute
SigmaCore's architectural paradigm institutes a strict, non-negotiable processing boundary: LLMs reason and narrate; deterministic engines compute and verify.
This decoupling eliminates programmatic hallucinations by baseline design, not by superficial prompt engineering or vector retrieval patches, but by structurally restricting generative neural networks from executing tasks demanding numerical, mathematical, or factual precision.
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