Data Extraction & FinanceUpdated October 2026
Financial Statement to Validated Structured JSON
Transform complex, messy tabular financial data and earnings releases into standardized, machine-readable JSON schemas with mathematical verification.
Target Users: Financial Analysts, Fintech Developers, Data Engineers, and Accounting Teams
Supported Workflow: Automated financial document processing, SEC filing extraction, and ERP data ingestion
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System / Role Prompt
You are a certified financial data engineer and CPA-grade accounting analyst. You extract tabular financial statements with zero numerical hallucination, enforce GAAP/IFRS terminology, and ensure strict JSON schema conformity.
Assembled User Prompt (Live Preview)1965 chars
You are extracting financial statement data into a validated, structured JSON schema. ### Task Specifications - **Filing / Report Type**: Consolidated Statement of Operations / Income Statement (10-K) - **Required Data Fields**: - fiscalPeriod (e.g. "FY2025", "Q3 2025") - currency (e.g. "USD", "INR") - units (e.g. "thousands", "millions") - totalRevenue - costOfRevenue - grossProfit - researchAndDevelopmentExpense - sellingGeneralAdministrativeExpense - operatingIncome - netIncome - earningsPerShareBasic - earningsPerShareDiluted - **Policy for Missing or Not Reported Line Items**: Set value to null with an explanation in _audit.missingFields ### Raw Financial Text / Table ```text CONSOLIDATED STATEMENTS OF OPERATIONS (In millions, except share amounts) Three Months Ended September 30, 2025: Total net sales: $94,930 Cost of sales: $51,120 Gross margin: $43,810 Operating expenses: Research and development: $7,760 Selling, general and administrative: $6,540 Total operating expenses: $14,300 Operating income: $29,510 Other income/(expense), net: ($210) Income before provision for income taxes: $29,300 Provision for income taxes: $4,650 Net income: $24,650 Diluted earnings per share: $1.64 ``` ### Extraction Rules & Constraints 1. **Strict JSON Output Only**: - Output valid JSON only, without conversational preamble or markdown postscripts. 2. **Numerical Accuracy**: - Extract numerical figures as standard numbers (not strings). Preserve exact currency units (e.g. millions vs thousands as specified in the header). - If a number is negative (often in parentheses `(1,234)`), represent it as a negative float/integer (`-1234`). 3. **Reconciliation & Audit Verification**: - Verify that: `Gross Profit = Total Revenue - Cost of Goods Sold` and `Operating Income = Gross Profit - Total Operating Expenses`. - Include an `_audit` metadata object in the JSON documenting any mathematical discrepancies found in the source text.
How to Use This Prompt Effectively
- 1Select the financial statement type (e.g. 10-K, 10-Q, Balance Sheet).
- 2Paste the raw text, OCR transcript, or HTML table directly into the raw data field.
- 3Copy the output JSON into your automated ingestion pipeline or data analytics notebook.
Representative AI Output
Sample output produced when using frontier AI models with the default parameters:
```json
{
"company": "Acme Corp",
"fiscalPeriod": "Three Months Ended September 30, 2025",
"currency": "USD",
"units": "millions",
"data": {
"totalRevenue": 94930,
"costOfRevenue": 51120,
"grossProfit": 43810,
"researchAndDevelopmentExpense": 7760,
"sellingGeneralAdministrativeExpense": 6540,
"totalOperatingExpenses": 14300,
"operatingIncome": 29510,
"netIncome": 24650,
"earningsPerShareDiluted": 1.64
},
"_audit": {
"mathReconciliation": {
"grossProfitValid": true,
"operatingIncomeValid": true
},
"missingFields": []
}
}
```Pro Optimization & Edge-Case Tips
- Always prompt the model to preserve negative signs when numbers are written inside parentheses like `(210)`.
- Add an `_audit` key in your requested schema so the model self-checks its arithmetic before returning the final JSON.
- Pair this prompt with our Document AI tool for direct PDF and image table parsing.