Auto-match rate
Shows how much matching work the agent carries.
An AI agent for bank reconciliation is software that matches bank and payment records to ledger entries and vendor statements, explains differences and monitors the sync between systems.
Bank lines, payments and ledger entries are collected.
The agent pairs payments with entries and statement items.
Unmatched items are listed with likely reasons.
It checks that postings reached the ERP as expected.
The accountant clears or explains each break.
A reconciliation record is prepared for sign-off.
The bank reconciliation agent matches bank statements and payment records to ledger entries and compares vendor statements with payables. It also watches the ERP sync logs for failures. For records that do not pair up, it works out the likely cause, such as timing, a missing entry or a sync gap.
Accountants receive proposed matches, a list of breaks with suggested reasons and a draft summary of the period. They accept matches and make any adjusting entries, controllers sign off, and IT fixes sync faults. The agent changes no ledger entries. It logs each proposed match and open break so the reconciliation record is traceable.
Each task below is something the agent prepares, checks, drafts or routes, with a person keeping the decision.
It pairs bank and payment records with ledger entries using amounts, dates and references.
It compares supplier statements with your payables records and lists missing or differing items.
Each unmatched item comes with likely causes, such as timing, fees or a missing entry.
It watches transfers between systems, such as NetSuite, and reports failures or gaps.
It compiles matched and open items in a form ready for review and sign-off.
It reads bank statements, payment records, ledger entries, vendor statements and ERP sync logs.
It decides which records likely belong together, which items remain unmatched and what probably explains them.
It records proposed matches, lists breaks and drafts the summary. Accountants accept matches and make any adjusting entries.
Matches payments to ledger entries.
Compares supplier statements with payables.
Watches data flowing between systems and reports failures.
Bring a small sample and watch Flo work through it.
| Aspect | By hand | With the agent |
|---|---|---|
| Matching | Lines are ticked off across several files. | Matches are proposed across bank, payments and ledger. |
| Breaks | Differences are hunted at month end. | Breaks are listed with likely causes as they appear. |
| Vendor statements | Compared to AP balances in spreadsheets. | Statement items are compared with ledger entries. |
| Sync issues | Missing postings are noticed late. | Sync gaps are flagged between the AP system and ERP. |
| Close evidence | Support is gathered for auditors manually. | A record shows each match, break and who cleared it. |
| If | Then | Who decides |
|---|---|---|
| A bank line matches one payment exactly | It proposes the match with the evidence | Accountant |
| One bank line covers several invoices | It suggests the grouping and shows the sum | Accountant |
| A payment has no bank line after the expected time | It lists it as unpresented or failed | AP clerk |
| A vendor statement shows an item the ledger lacks | It flags a possible missing invoice | AP clerk |
| A posting is missing in the ERP | It flags the sync gap with the document reference | Finance systems owner |
| A break stays open past the period | It carries it forward with an age and owner | Controller |
Payments cleared in the next period are tagged as timing. The accountant confirms before they are carried over.
Small differences are grouped and described. The accountant decides on the correct posting.
The agent shows both lines and the likely cause. A person decides whether to raise it with the bank.
Disputed items are marked, not cleared. AP resolves them with the vendor before adjusting records.
Talk it through with the team. We will map it to your steps and show where a person stays in control.
Start with a single account with clean, regular payments.
The accountant confirms each proposal and notes where it is wrong.
Include vendor statement comparison and sync checks on the same account.
Extend to more accounts and entities, keeping sign-off with the controller.
Shows how much matching work the agent carries.
Open breaks = [n] unmatched items at period end, by ageTracks what is left to investigate.
Sync failures = [n] failed or missing transfers in [period]Indicates the reliability of the connection between systems.
Quick answers to what people ask most about AI agent for bank reconciliation.
Book a demoIt is an agent that matches payments and statements to ledger entries, explains differences and monitors system syncs, so accountants review exceptions rather than every line.
No. It proposes matches and lists breaks. Accountants decide on adjustments and post them under your controls.
Yes. It compares a supplier statement with your payables records and lists missing, duplicate or differing items.
It watches transfers between systems and reports records that did not arrive or arrived with differences, so they can be fixed before close.
An AI purchase request agent is software that takes in employee requests to buy something, completes the missing details, checks them against spend policy and existing contracts, and routes them to the right approvers.
→An AI request triage agent is software that sorts incoming procurement requests by urgency, risk and type, so the right request reaches the right person first.
→An AI purchase order agent is software that drafts purchase orders from approved requests, checks them against budget and contract terms, and tracks what happens afterwards, from supplier confirmation to receipt.
→An invoice processing AI agent is software that captures supplier invoices from email and portals, extracts their data, matches them to vendors and purchase orders, validates tax and totals, and routes exceptions.
→Bring a small sample of real items. We will show what Flo handles on its own and where it hands over to your team.