Financial services runs on documents that demand both speed and accuracy: identity documents for KYC, income statements and asset disclosures for loan applications, and regulatory filings that auditors will scrutinize years later. DocumentIQ handles the extraction with confidence scores on every field, a feedback loop that creates an auditable correction history, and Excel exports formatted for compliance reporting.
Onboarding new clients requires extracting and verifying data from passports, utility bills, corporate registrations, and beneficial ownership documents — each in different formats and from different jurisdictions.
Loan officers manually pull income figures, employment details, asset values, and liability amounts from tax returns, bank statements, and pay stubs. The process is slow and introduces errors that delay underwriting.
Compliance teams must extract specific data points from regulatory filings, annual reports, and disclosure documents — often under tight deadlines and across hundreds of entities.
Every extracted value must be traceable back to its source document and page. Manual processes lack the systematic traceability that auditors and regulators require.
Extract data from PDFs, scanned documents, and Word files in a single project. Handle the format variety inherent in client-submitted documentation without separate pipelines per document type.
Every extracted value includes a confidence score from the LLM. Route low-confidence extractions to human review automatically, and focus reviewer time where it matters most.
When a reviewer corrects an extracted value, the original value, correction, reviewer identity, and timestamp are all recorded. This creates the auditable correction history regulators expect.
Export extracted data with confidence scores, page references, and feedback status in structured Excel files ready for compliance reporting, regulatory submission, or integration with downstream systems.
Extract structured data from supplier invoices, purchase orders, and receipts at scale. Cut AP cycle time, eliminate transcription errors, and pay on the right terms.
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