What is financial statement data extraction?
Financial statement data extraction is the automated reading of balance sheets, income statements and cash flow statements into structured records, with every figure still attached to its row label, its reporting period, its currency and its unit scale.
Reading the numbers is the easy part. Every figure sits where a row crosses a column inside a reporting period, and anything that loses one of those three hands back a number that looks completely reasonable and is completely wrong. That is the error that survives review and lands in the board pack. A general-purpose chatbot makes it with more confidence than anything else in the building: 2025 evaluations put language models wrong on 13.8% of financial data tasks, and none of the wrong ones look wrong.
Parseur extracts deterministically instead. Same statement in, same figures out, every run.
How to extract data from financial statements with AI?
Three steps from PDF to spreadsheet. No template to build, no rules to write.
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1. Send in your statements
Parseur gives you an email address. Forward statements to it as they land, or drop in a whole quarter at once.
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2. AI reads every line
The Vision AI engine extracts each line item with its period, unit scale and sign attached.
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3. Export to your stack
Fields land in QuickBooks, Excel, Google Sheets or your own database, ready to tie out.
On a financial statement, the wrong number always looks right
GAAP and IFRS standardize the accounting. Nothing standardizes the document. A statement arrives as a PDF laid out for a human eye, and four things break any tool that reads it as plain text.
The first is column selection. Current quarter, prior quarter, year to date, a prior-year comparative and sometimes budget all sit on the same row, so pulling the right line from the wrong column returns a figure that passes every sanity check you have. Most dangerous error of the set, and the least visible.
The second is scale and sign. "$ in thousands" in a header, parentheses for negatives, trailing minus signs, contra accounts, cash-flow conventions. Miss one and you are not off by a rounding error, you are off by a factor of a thousand, or pointing the wrong way.
Then there is naming. One company reports Revenue, the next Net Sales, the next Turnover. Three documents, one concept, and a mapping that has to be auditable rather than guessed.
And structure. Balance sheets and cash flow statements run across pages, with headers that repeat, shift or vanish. Plain OCR reads the characters and loses the grid that made them mean anything.
This is also why reasoning-heavy approaches struggle at volume. Standard parsing takes roughly 1 to 2 seconds per page while agentic extraction can take 8 to 40 seconds per page. Fine for a handful of documents. A bottleneck for a quarterly close.
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What fields can Parseur extract from financial statements?
These are the fields most finance teams pull off a balance sheet and P&L. Rename them, drop them, add the ones your own template needs.
Every value comes back with the document it came from, so a reviewer can trace a figure instead of trusting it. Anything missing or in the wrong shape is flagged before it reaches your model, not after.
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Sample value
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Text (multi-lines)
Company Name
The name of the company.
Rocket Lab USA INC.
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Date
Fiscal Year Ending
The end date of the fiscal year.
2023-12-31
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Number
Turnover Revenue
The total revenue generated by the company.
244,592,000
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Number
Cost of Sales
The direct costs associated with the production of goods.
193,183,000
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Number
Gross Profit
The difference between revenue and cost of sales.
51,409,000
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Number
Operating Expenses
The costs incurred in the day-to-day operations of the business.
229,327,000
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Number
Net Profit Before Tax
The profit before tax deductions.
-178,921,000
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Number
Tax Expense
The amount of tax paid by the company.
3,650,000
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Number
Net Profit After Tax
The profit after tax deductions.
-182,571,000
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Number
Total Assets
The total assets owned by the company.
941,211,000
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Number
Total Liabilities
The total liabilities owed by the company.
386,667,000
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Number
Total Equity
The total equity of the company.
554,544,000
Why choose Parseur for financial statement OCR?
Built for the person who has to sign off on the numbers.
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Same document, same numbers
Every run returns the same figures. Nothing is inferred, recalculated or filled in from context, so a total you did not send is a total you do not get back.
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Built to survive quarter-end
Thousands of statements in one batch, seconds a document rather than minutes. That is the difference between a close that lands inside its window and one that eats the weekend.
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Errors start at the keyboard
88% of professionals report errors in document-derived data, and 6 or more hours a week go into fixing them. Take out the retyping step and most of those errors are never made.
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Your numbers stay yours
Statements carry salaries, margins and figures nobody outside the deal should see. Parseur is GDPR compliant, your documents are never used to train an AI model, and the security policy puts both in writing.
Tested many of this kind and I must admit this one is delivering the data with an outstanding accuracy.
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