What Is Inside AI Bank Reconciliation
The service is a working part of your close, not a report. Here is what it matches on, what it clears on its own, what it hands your team, and how it writes back to your ledger.
From a raw statement to a reconciled ledger
It matches the way a good accountant would
Every bank line is weighed against your ledger on amount, value date, reference or narration, and the pattern of how a payer usually appears. A match is not a single exact string, so short bank descriptions and inconsistent names still find their entry.
- Amount, date, reference and pattern weighed together.
- Reads messy narrations instead of failing on them.
- Tuned on your own history, not a generic rule set.
The easy volume clears, the rest is a quick confirm
Confident matches are cleared without anyone opening them. Likely matches are grouped into a short confirm queue, so your team approves the ones that look right in a couple of clicks instead of hunting for them across the statement.
- High-confidence pairs cleared automatically.
- Likely matches grouped for a fast confirm.
- A short queue in place of a full statement.
Only the real problems reach a person
Anything that does not fit is labelled with why it was flagged: a missing entry, a duplicate, an unmatched fee, an amount that is off. A person resolves those, and every cleared and confirmed match is written back to your ledger so the books stay in one place.
- Exceptions labelled with the reason.
- A person owns the cases that need judgement.
- Matched entries written back to your ledger.
Everything the service delivers
Four-signal matching
Amount, value date, reference and payer pattern weighed together for every bank line.
Automatic clearing
Confident matches cleared on their own, so no one reopens the routine lines.
Confirm queue
Likely matches grouped for a quick approval, ranked so the closest sit on top.
Exception list
Only the real problems, each labelled with why it was flagged for a person.
Ledger write-back
Cleared and confirmed matches posted back to your ERP or accounting ledger.
Model-agnostic build
Runs on the models that suit your accuracy and hosting rules, swappable later.
See These Features on Your Own Statement
Book a free consultation. We will run a recent statement against your ledger and show you what the AI clears, what it groups to confirm, and what it flags.
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