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AI in Markets Checklist

Prompt Design for Financial Extraction

Extracting structured data from filings, transcripts, and reports is one of the highest-value finance LLM tasks and one of the easiest to get subtly wrong. This checklist governs the prompt that turns a document into structured fields.

12 ITEMSPublished May 26, 2026Live Content
By AI Fin Hub Research · AI Fin Hub Team

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Checklist Sections

Work in focused batches instead of one long wall

Section 1

Phase 1: Output contract

3 items
Use The ToolPlaygrounds

Structured Schema Validator for Finance

Paste LLM JSON output and validate against four pre-built finance schemas — research output, trade decision, risk snapshot, peer comparison — with sanity.

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Use The ToolPlaygrounds

LLM Finance Error Taxonomy

12 documented LLM-on-finance failure modes (hallucinated ticker, stale price, units, currency, off-by-100, fictional source, more). Paste output, see flags.

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Section 2

Phase 2: Grounding

3 items
Use The ToolPlaygrounds

Hallucination Detector

Paste a source document + an LLM's extraction. Every numeric claim in the output is checked against the source. Client-side. Catches silent fabrication.

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Section 3

Phase 3: Missing and ambiguous data

3 items

Section 4

Phase 4: Testing and stability

3 items
Use The ToolPlaygrounds

Prompt Injection Tester

Red-team a finance agent against 24 documented prompt-injection attacks — direct override, role confusion, indirect injection via retrieved content.

ToolOpen ->
Use The ToolPlaygrounds

Prompt Regression Tester

Run the same prompt against multiple models (Claude 4.5/4.6/4.7, GPT-5, Gemini 2.5) with your own keys. Diff outputs, score drift, catch regressions.

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Pro Tips

Small moves that make the checklist easier to finish

Units and currency are not pedantry, they are where finance extraction breaks. A revenue figure pulled as a bare number is one thousands-separator away from being wrong by a factor of a thousand.
Give the model an explicit way to say not-present. Without one, a model under pressure to fill a field will invent a plausible value, and a plausible wrong number is the hardest kind to catch.
Require a source span for every value. It turns verification from a judgment call into a lookup, and it makes the whole extraction auditable by someone who never saw the prompt.

Sources & References

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FAQPage Schema

Schema.org FAQPage: the structured-data spec that makes FAQ content machine-readable for search and LLM crawlers. When to apply, when to skip.

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Planning estimates only — not financial, tax, or investment advice.