AI for finance
AI for finance teams: invoices, collections, close and reporting
AI helps a finance team by reading every invoice, statement and remittance the moment it arrives, matching it against the ledger, and handing people only the exceptions. Native builds those agents inside the ERP you already run, with a controller approving anything that posts. At Iyuno, invoice processing went from days to minutes at 99.9% field-level accuracy.
Featuring insights fromShaun Devan · Founder & CEOUpdated · 4 min read
Where AI has an impact in finance
Invoice extraction
Every vendor invoice read whatever its layout, with each field tied back to its place on the page.
Three-way matching
Invoices checked against the purchase order and goods receipt, with mismatches queued and explained.
GL coding
Lines coded to accounts and cost centres from vendor history and policy, for a person to confirm.
Cash application
Incoming payments matched to open invoices from bank data and remittance emails.
Bank reconciliation
Statement lines matched overnight, so the morning starts with breaks rather than raw data.
Close checklist
Supporting schedules prepared and each task's status tracked, with blockers named early.
Flux commentary
Variance explanations drafted from the ledger detail for the controller to edit.
Collections
Dunning emails drafted from the aging report and sent once someone approves them.
Where a finance team's time actually goes
Most finance hours are spent moving data between documents and the ledger. Invoices arrive as PDFs in a dozen layouts, bank and card statements need matching line by line, customers pay without a remittance, and the close waits on a handful of reconciliations nobody can start until the last statement lands.
None of that needs judgement until something fails to match. Agents take the reading, keying and matching, and your accountants work the breaks, the accruals and the questions the CFO asks.
| Work | Agents | Finance team |
|---|---|---|
| Vendor invoices | Read every field, match to PO and receipt, code to the GL | Approve payment runs and clear exceptions |
| Customer payments | Apply cash from remittances and bank feeds | Resolve short pays and disputes |
| Bank and account reconciliation | Match transactions and list the unmatched with likely causes | Investigate and sign off |
| Month-end close | Prepare schedules, flux commentary drafts and the checklist status | Book adjustments and own the numbers |
| Management reporting | Assemble the pack and answer ad hoc questions from the ledger | Interpret and present |
Where to start
- Accounts payable intake. One monitored inbox, every invoice read and matched before anyone opens it. It is high volume, rule bound and easy to check.
- Cash application. Payments matched to open invoices from bank data and remittance emails, with the unclear ones queued for a person.
- Reconciliations that hold up the close. Agents run the matching overnight so the team starts the day with a short list of breaks.
- Collections follow-up. Reminder emails drafted from the aging report in your own tone, sent after someone approves the batch.
Controls stay where auditors expect them
Agents prepare and propose; they do not post journals or release payments on their own. Segregation of duties is kept, approval limits stay in your ERP, and every field an agent extracts carries the page it came from, so a reviewer can check the source in one click.
Agents work inside NetSuite, Sage Intacct, Microsoft Dynamics, SAP or QuickBooks through their APIs, and read from your bank feeds and AP inbox. The code, data and credentials are in your accounts. See how we handle security.
What an engagement looks like
We sit with AP, AR and the close team for the first two weeks and trace a month of documents through the ledger. That shows where the hours go and which workflow has the most impact. The first agent is in production within weeks, usually on invoices. Within months the department closes with agents on every recurring task, and your team is trained to run and extend them.
How to measure it
- Invoice cycle time from receipt to approved for payment
- Field-level extraction accuracy and the share of documents with no manual touch
- Days to close
- Unapplied cash and days sales outstanding
- Finance hours returned to analysis each month
Case study · Iyuno
Iyuno cut invoice processing from days to minutes.
Native helped Iyuno build an extraction engine that reads the invoices reaching its finance team, whatever the format, at 99.9% field-level accuracy. It gave the team back over 250 hours.
Frequently asked questions
How can AI help a finance team?
AI reads invoices, statements and remittances, matches them to the ledger, prepares close schedules and drafts commentary. People keep approvals, adjustments and anything that needs judgement, and spend less time keying data.
Can AI automate accounts payable?
It can automate most of the work in accounts payable: reading the invoice, matching it to the PO and receipt, and coding it. Payment release stays with a person, inside the approval limits already set in your ERP.
Is AI accurate enough for financial data?
Built properly, yes. Two independent reads of each document checked against each other, plus validation against the ledger, catch the errors one pass would miss. At Iyuno, field-level accuracy reached 99.9%.
Will AI agents post journal entries?
Not on their own. Agents prepare entries and schedules with the evidence attached, and an accountant reviews and posts them, so segregation of duties and the audit trail stay intact.
What finance process should we automate first?
Usually AP invoice intake, because the volume is high and the result is easy to check. Cash application and the reconciliations that delay the close tend to follow.
