Financial Statement Extraction
Balance sheet, P&L, cash flow — parsed from PDF into numbers that reconcile, with the footnotes attached.
Financial statement extraction is the structuring of company financials from documents — balance sheets, income statements, cash flow statements, and their footnotes, arriving as audited PDFs, scanned filings, and management accounts in every format a finance team can produce — into normalized data for credit analysis, underwriting, valuation, and monitoring. It is the automation of "spreading," the analyst ritual of re-keying statements into standard templates, which consumes junior hours at every bank, insurer, and fund that assesses counterparties.
The task is table extraction hardened by accounting structure. Statements are hierarchical tables — line items nested under subtotals, multi-period columns, comparatives restated — where indentation carries meaning and sign conventions vary (parentheses, minus signs, CR notation). Normalization maps each company's idiosyncratic line labels onto a standard chart ("Trade and other receivables," "Accounts receivable, net" → one concept), units and currencies resolve (thousands versus millions, stated where you'd expect and sometimes only in a header footnote), and the arithmetic is the built-in ground truth: assets equal liabilities plus equity, subtotals sum, cash flows tie to balance movements — validation that catches extraction errors and, occasionally, the document's own. Footnotes are the expert tier: the lease commitments, contingencies, and accounting-policy details that change what the headline numbers mean, increasingly extracted by language models into linked context rather than left behind.
Downstream, extracted statements feed the machinery of financial assessment: ratio computation and covenant testing, credit models and rating inputs, peer benchmarking, portfolio monitoring that ingests statements as they arrive rather than quarters later. Provenance discipline runs throughout — every number linked to its statement, page, and cell — because analysts and auditors alike will ask, and because the extracted dataset is only as defensible as its trail back to the audited page.
Ten banks, ten layouts, one question: what actually happened in this account?
The leverage ratio buried in section 7.2 — extracted, structured, and monitored before it's breached.
Rows, columns, and the relationships between them — the structure that flat text extraction always destroys.
Proof Perimeter runs document AI inside your own perimeter — with a provenance record on every field.
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