AI by department · finance
AI in finance: less retyping, more control over the numbers
For finance teams and controllers who lose their week to invoices, matching and monthly reports. AI reads invoices, matches them with the purchase order, prepares the booking and flags what deviates. Your team approves, and has time left for analysis and advice.
- 12 hours a week saved on invoices
- Works with Exact, AFAS and SAP
- A human approves
Finance agent
livereads 146 invoices from the invoice inbox
matches them with purchase orders and goods receipts in Exact
prepares 131 bookings, books only after approval
Worked with us
01 / What it is
What does AI do in finance?
AI in finance does the reading, matching and searching in the accounts. It reads invoices, matches them with purchase orders and goods receipts, prepares bookings, flags exceptions and writes the first draft of reports. A human approves what gets booked and decides what happens with an exception.
Finance is a rewarding department for AI. The work is often already digital, the volume is high and every error shows up in the check. That last point matters: with an invoice, you know exactly when it's right. So you can measure how often AI gets it right, and build trust with evidence.
And it's a department where people are often too good for the work they do. A controller who spends three days a month pasting figures out of systems could use that time to work out why the margin on product group B has been falling for three months. That's worth more to the management team.
01Reading invoices
PDF, email or portal: supplier, amount, VAT and lines recognized.
02Matching and booking
Against purchase order and receipt, with the booking ready for approval.
03Exceptions
Price differences, duplicate invoices and missing order numbers set apart.
04Reports
Figures from several systems, with an explanation of what stands out.
02 / Sound familiar?
Where finance's time really goes.
Not to analysis and advice. To all the work that comes before it.
The invoice inbox
“Hundreds of PDFs a week, each in a different format. We retype them into the accounting software.”
Matching
“Invoice, purchase order, packing slip. Three documents, three systems, one colleague putting them side by side.”
Paid twice
“A supplier sent the invoice twice. We only noticed when a credit note arrived. Or we didn't.”
Month-end close
“In the first week of the month, finance is unreachable. Everyone is in Excel.”
The question from management
“Why has the margin dropped? The answer takes a day of searching in three systems.”
Compliance
“Every file through the same checklist. A hundred times a month, by hand.”
03 / Before and after
A month in finance, before and after AI.
Six tasks we automate for finance teams. Where there's a client figure, it comes from a case. What it delivers for you, we calculate with your own volumes.
- Client case: 12 hours a week
A purchase invoice
Before
Open the PDF, look up the supplier, retype amounts and VAT, code it.
With AI
Read, coded and prepared as a booking. The bookkeeper approves.
Matching invoice, order and receipt
Before
Putting three documents from three systems side by side by hand.
With AI
Matched automatically. Only the differences go to the work list, with the documents attached.
Duplicate and deviating invoices
Before
Noticed when it's too late, or not at all.
With AI
Flagged before anything is paid: same amount, same supplier, different number.
Following up on receivables
Before
A list of open items and an afternoon of calling and emailing.
With AI
Reminders drafted in the right tone for each customer, calls prepared with the history. The credit controller decides.
- Consultancy firm: 55% time saved
The monthly report
Before
Exports from three systems, an afternoon of pasting, an hour of formatting.
With AI
The figures in one place, with an explanation of what deviates from budget and last year. The controller writes the interpretation.
- Advisory firm: 95% accuracy
A compliance check
Before
Every file through the same checklist, by hand.
With AI
Files run through the checklist automatically, with what was found for each point. The advisor reviews.
04 / Exceptions
Why AI in finance is especially good at what doesn't add up.
An invoice that matches the purchase order exactly isn't interesting. It just needs to be booked. The value is in the invoices that deviate: a price higher than agreed, an invoice without an order number, a supplier that invoices twice, a VAT amount that isn't right.
By hand, you find those by checking everything. That takes a lot of time, and at high volumes in particular something slips through. AI turns it around. Everything that matches goes for approval as a prepared booking. Everything that deviates goes to the top of the work list, with the reason and the documents attached. Your team spends its attention on the exception instead of the rule.
The same works in reporting. Instead of a table with a hundred lines, you get the five items that stand out, with a question attached: is this an error, a shift or a trend? The answer stays with the controller.
01What matches
Prepared as a booking. Approval per invoice at first, later spot checks once it has proven itself.
02What deviates
At the top of the work list, with the reason and the documents.
03What stands out in the figures
A signal with an explanation. The interpretation belongs to the controller.
04What AI doesn't do
Send payments without approval from an authorized colleague.
05 / Who does what?
Where does each kind of finance work land: with a human or with AI?
Invoice processing is one of the few tasks that can eventually move fully to AI, with spot checks: fixed format, high volume and every error shows up in the match. Other tasks stay at 'Human approves' or 'AI assists'. Pick a task and see why.
Pick a task
Human
A person does the work. AI stays out.
AI assists
A person does it, AI drafts or looks things up.
Human approves
AI does the work, a person checks before it goes out.
Fully AI
AI does it by itself. A person spot-checks.
Where it lands: Human approves
AI prepares the answer with the right order details. An employee reads along and sends: tone and exceptions stay human.
06 / What to watch for
Six things to get right before you use AI in finance.
Segregation of duties
Whoever books doesn't approve. That rule stays in place when AI is involved: the AI prepares, an authorized colleague approves.
An audit trail
Every step is logged: what the AI read, what it proposed, who approved it. Helpful for the auditor.
Clean master data
Duplicate suppliers and old general ledger accounts make AI uncertain. Cleaning up is often step one.
Thresholds
Above an amount you choose, always a second pair of eyes. However well it matches.
Data in the EU
Financial data stays in the EU, with you or with a European provider. Azure OpenAI is an option.
Use what's already there
Can your accounting software already do it well enough? Use that. We build where the work runs between systems.
07 / Yourself, tool or partner?
ChatGPT, the invoice scanning in your software or an AI partner?
Three ways to use AI in finance. They don't rule each other out. An honest side-by-side:
| On your own with ChatGPT or Copilot | Invoice scanning in your accounting software | AI Partnership with NinA | |
|---|---|---|---|
| What it does | Summarize a table or explain a formula | Read invoices and suggest a booking | Reading, matching, exceptions, reports and checks across all your systems |
| Matches with purchase order and receipt | · | Sometimes, depending on the software | ✓ |
| Works across several systems (ERP, bank, CRM, Excel) | · | · | ✓ |
| Report with explanation | If you supply the data yourself | · | ✓ |
| Audit trail and approval | · | Within the software | Across the whole chain, logged per step |
| Who builds and maintains | Everyone for themselves | The vendor | A dedicated NinA team |
| Fits | One-off analyses and questions | Standard invoices, one software package | High volume, several systems, exceptions and reports |
Swipe sideways to see all columns →
Good invoice scanning in your software is often a fine start. We build around it: the matching, the exceptions and the reporting.
08 / How to approach it
From first conversation to a month-end close that no longer takes a week.
We build within the AI Partnership. You start with the € 6,000 AI Quick Scan: one day on site, and within a week you know what AI delivers in your finance team.
- 01
Intro call
Fifteen minutes
How many invoices, which systems, and where is the manual work?
- 02
AI Quick Scan
One day plus a week
We walk through the chain from invoice to report. Three numbers per step: duration, number of people and frequency. A business case per opportunity, and a twelve-month roadmap.
- 03
First process live
Quarter 1
Almost always invoice processing: high volume, fixed format, measurable. Tested on hundreds of invoices from last month, with a bookkeeper who approves everything.
- 04
Expand
After that
Exceptions, receivables, reports, compliance checks. Every month you see what it delivers in hours and euros.
09 / Cases
Documents, checks and admin with AI, in practice.
10 / Questions
Frequently asked questions about AI in finance.
What can AI do in finance?
In finance, AI can read invoices, match them with purchase orders and goods receipts, prepare bookings, flag duplicate or deviating invoices, follow up on receivables, prepare monthly reports and run files through a compliance checklist. A human approves what gets booked and paid. At one NinA AI client, invoice processing alone saved 12 hours a week.
Can AI process invoices automatically?
Yes. AI reads invoices from PDF, email or portal, recognizes the supplier, amounts, VAT and lines, matches them with the purchase order and prepares the booking. At first, a bookkeeper approves every booking. What runs without errors for a long time can move to spot checks. Exceptions always go to a human, with the reason and the documents attached.
Does AI book directly in our accounting software?
Only if you want it to, and only once it has proven itself. We start with prepared bookings that an authorized colleague approves. Segregation of duties stays in place, above a threshold amount a second person always checks, and every step is logged. Payments never go out without a human's approval.
Which accounting and ERP packages does it work with?
With Exact, AFAS, SAP, Microsoft Dynamics and other packages with an API or export, plus email in Microsoft 365 or Google Workspace and Excel. We usually build in n8n, with custom work where needed. The condition is access with the right permissions, set up with your administrator.
What does the auditor think of AI in the accounts?
Raise it with your auditor beforehand. With a clear audit trail, segregation of duties and approval thresholds, the accounts are often easier to audit than with retyping, because every step is recorded. We document how the workflow works, so your auditor can see what the AI does and where a human decides.
How quickly does AI in finance pay for itself?
That depends on the volume. An example from our practice (anonymous): € 77,000 saved against € 28,000 in build costs, paid back in about 4.5 months. At NinA AI we only start if the whole partnership delivers at least twice the investment in the first year. We calculate that in advance in the AI Quick Scan, with your own numbers.
What does AI for finance cost at NinA AI?
You start with the € 6,000 AI Quick Scan. Building happens within the AI Partnership: package S costs € 4,500 per month (30 hours), M € 7,500 (50 hours) and L € 12,000 (80 hours), for a minimum of twelve months. What goes live is covered by a maintenance contract from € 245 per month, including AI usage: Bronze runs on your own servers, Silver and Gold on our platform in the EU. All amounts excluding VAT.
Is our financial data safe?
Financial data stays in the EU, on your own infrastructure or on servers with a European provider. Azure OpenAI is an option. The AI only gets access to what it needs for its task, and everything is logged. We work to ISO 27001 and NEN 7510; certification is in preparation. Code, data and documentation are yours and come with you within 30 days if you stop.
Further reading
- AI in operationsOrders and requests into the ERP, planning proposals and work preparation.
- AI agentsDigital colleagues that plan, carry out and report, with a human in the loop.
- AI PartnershipA dedicated AI team that builds, measures and maintains, process by process.
- Automating reports with AIFrom data to report, with the figures from the source.
More time for analysis, less for retyping?
Book an intro call. Together we'll look at your invoices, systems and reports, and where AI saves time first.
01
Intro call
Fifteen minutes, no strings. Where does work get stuck and what do you want to achieve?
02
AI Quick Scan
One day on site. Within a week, a business case and a roadmap.
03
AI Partnership
A dedicated team that builds, trains and shows what it delivers every month.
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