What a 15-day reconciliation cycle actually costs
Our firm ran a monthly reconciliation cycle that took 15 business days. That's three full working weeks where the finance team is heads-down in documents, cross-referencing entries, and manually keying data into our accounting platform.
The direct cost was staff hours. The indirect cost was worse: we couldn't close the books until day 15, which meant management had no reliable P&L for the first three weeks of every month. Decisions were made on incomplete data. Every month.
The automation approach
We worked with Neriman Halilović to build an OCR automation pipeline tailored to our specific document types — invoices, bank statements, expense reports, and internal transfers. The system:
- Scans and classifies incoming documents automatically
- Extracts structured data (amounts, dates, account codes) using trained OCR models
- Maps extracted data to our chart of accounts and pre-populates entries in the accounting software
- Flags low-confidence extractions for human review
Critically, the system was trained on our specific document formats — not a generic off-the-shelf tool. That's what made the accuracy acceptable for a finance context.
Month one results
We closed the books in one day. Not "faster" — one day. The reconciliation cycle that previously consumed 15 days of staff time now runs overnight, with human review of flagged items taking a few hours the following morning.
The accuracy rate on auto-processed documents was 97.3% in month one. That number has climbed as the system has seen more of our documents.
What a finance professional actually cares about
The pitch for AI automation often focuses on "efficiency." From where I sit, what matters is control and accuracy — not speed for its own sake.
This system gives us both. The audit trail is cleaner than our manual process because every extraction is logged with a confidence score and the source document. Auditors actually prefer it.
If your firm is running a reconciliation cycle longer than three days, the gap between where you are and where you could be is almost entirely manual data processing. That's automatable.