TL;DR: An OCR pipeline scans documents, extracts the data, and populates the accounting software automatically. Human review is left only for flagged exceptions, and the reconciliation cycle drops from 15 days to one.
What a long reconciliation cycle really costs
The direct cost is staff hours. The indirect cost is worse: until the books close, management decides on incomplete data. Every month, for the first few weeks, the business runs half-blind.
How the pipeline works
- Scanning and classification. The system recognizes the document type — invoice, statement, expense report — and routes it correctly.
- Data extraction. Amounts, dates, and account codes are pulled by OCR models trained on your document formats.
- Mapping to the chart of accounts. Extracted data is mapped and entered into the software, and low-confidence items are flagged.
- Human review for exceptions only. A person reviews a few flagged items in the morning instead of keying everything by hand.
Why accuracy is decisive here
In finance, speed without accuracy is worthless. That's why every extraction carries a confidence score and a link to the source document — the audit trail is cleaner than a manual process, which auditors appreciate.
FAQ
Will it work on our specific documents?
Yes. The system is trained on your formats, not a generic template — that's exactly what makes the accuracy acceptable for a finance context.
How fast does it pay off?
The math is simple: hours saved times fully-loaded hourly rate times working days. For cycles longer than three days, the gap is almost entirely manual data processing.