Missing details
One missing detail on an invoice stops the whole process and triggers follow-up questions.
AI agents for finance processes
Finance processes that think ahead
The world of finance is large and its processes are varied. Posting incoming invoices, approving expenses, reconciling accounts and producing analyses. For all of these tasks, employees have to gather information, assign it, match it and follow up – and much of that is still done by hand. AI agents prepare these transactions.
AI agents prepare transactions.
Finance teams save time and stay in control.
Challenges
Finance processes rarely fail for lack of data
In most finance departments the figures are reliably available. What is harder is that information is spread across mailboxes, documents, sub-ledgers and upstream systems. At month-end, during the ongoing close or against another deadline, it then has to be gathered and classified laboriously – often by hand. And whatever is posted in the end has to be justifiable later.
Standard cases usually run through finance processes smoothly. It is the exceptions that take up most of the time:
Unclear assignment
An invoice without a clear assignment has to be researched and classified manually.
Diverging ledgers
Two ledgers that do not match cause the biggest review effort at period end.
The data is there. The effort comes from getting it to the right place.
Added value
Where AI agents create real value in finance
This is where AI agents play to their full strength: in individual processes. Four examples from everyday finance work show where they already provide concrete relief today and where responsibility stays with the team.
Incoming invoices: from the mailbox to a checked transaction
Expenses and out-of-pocket costs: capturing receipts faster and preparing them in line with the rules
Why the monthly close should not start at month-end
Financial analysis: spotting anomalies and preparing decisions
Supplier invoices arrive through different channels and in inconsistent formats. In the end they still have to be assigned to the right supplier, the matching order and the right account.
An agent can recognize incoming invoices, read the contents, assign the supplier and prepare an invoice draft for review.
For the finance team that means less manual groundwork and a much faster start to the accounts payable process. Approval still comes from a person.
Expenses look like a small matter but quickly become laborious day to day.
- Receipts are missing
- Details are incomplete
- Categories have to be checked
- Spending has to be prepared for approval
AI agents integrated directly into the ERP system can read such data, assign it to a category and combine the individual items into an expense report.
Loose receipts thus become structured transactions. Employees submit their spending more easily, while rules and workflows stay stored in the system.
Account reconciliation is one of the delicate topics in finance, because errors often surface late. General ledger, accounts payable, accounts receivable, bank and tax all have to match in the end. If a discrepancy only becomes visible at period end, the pressure arrives exactly when there is little time left.
AI agents are a significant step towards a continuous close. They spot exceptions early, propose suitable measures and log every step, so that the handling stays traceable.
Reconciliation thus becomes less reactive and exceptions can be assessed earlier.
A finance team does not only have to post correctly. It should explain variances, spot risks early and provide a sound basis for decisions. The analyses for this usually still have to be produced by hand.
Agents integrate financial data into the solutions your employees already work with.
This way they support reconciliations, produce the associated reports and point out anomalies. Ideally straight away with a suggestion for how to handle specific variances.
How agents, ERP and the finance team work together
In finance, agents support your employees: they take on preparatory work and draw on the data and rules of your ERP system to do so. Decisions and approvals stay with people.
| Process | What the agent takes on | Role of the ERP system | Responsibility of the finance team |
|---|---|---|---|
| Incoming invoice | Recognize invoices, read contents, prepare drafts | Supplier, order, payment terms, account assignment | Approval and unclear assignments |
| Expenses | Capture receipts, extract data, categorize, bundle into a report | Rules, posting logic, permissions | Approval and special cases |
| Account reconciliation | Spot discrepancies, propose measures, log steps | General and sub-ledgers, balances | Assessing the exception |
| Financial analysis | Spot anomalies, produce reports, propose how to handle them | Financial data, reporting structures | Interpretation and decision |
Intelligent finance processes
From a single agent to an intelligent finance process
An agent for invoices, a tool for expenses, an ERP system for posting. Each element is useful on its own, but together they do not yet make an end-to-end finance process.
When agents, automation and ERP work together
The value only emerges when data, rules, approvals and responsibilities mesh. A typical sequence as an example:
A supplier invoice arrives
The agent reads the contents and prepares the transaction
The ERP supplies supplier, order, payment terms and account assignment
Matching against order and goods receipt shows whether everything fits
For clean cases, automation triggers approval and payment
The people in your finance department decide on exceptions and stay in control
Technologies
Modern finance processes emerge from several technologies working together
No single tool carries a modern finance process on its own. ERP, automation and AI agents each have their own job in it.
ERP as a reliable data and process basis
The foundation is the ERP system, such as Microsoft Dynamics 365. This is where master data, documents and posting logic sit, along with the workflows and permissions everything else follows. Only this clean basis makes automation and agents reliable at all, because they draw on checked data and clear rules.
Automation for recurring routines
Workflows that repeat reliably do not need AI. Here classic automation takes on the routine and works through fixed steps quickly and with few errors. It remains the most stable route wherever the rules are unambiguous.
AI agents for analysis and decisions
It gets interesting beyond the clear rule. AI agents prepare transactions, analyze exceptions and bring information from different sources together into a proposed action. And they bring the human in exactly when a decision is due.
Bank Automation Suite for bank-related processes
Some tasks in finance are less suited to AI agents. Bank-related workflows around payment information and payment transactions benefit more from specialized automation.
One example from practice is the Bank Automation Suite for Microsoft Dynamics 365 Finance. It processes bank statements and payment data automatically, matches them against open items and prepares the postings in the ERP.
Process by process, this creates a finance function in which ERP, automation and agents each take on what they suit best.
Microsoft agents
Which Microsoft agents already support finance processes
For Microsoft Dynamics 365 and Business Central there are several agents already built firmly into both ERP solutions. A brief overview of what they take on today.
Dynamics 365 Business Central · generally available
Payables Agent for accounts payable
- Recognizes incoming supplier invoices,
- reads them and
- creates an invoice draft for review.
Dynamics 365 Finance · production-ready preview
Account Reconciliation Agent for account reconciliation
- Spots exceptions in the reconciliation,
- proposes measures and
- makes the process more transparent.
Dynamics 365 Business Central · production-ready preview
Expense Agent for expenses and out-of-pocket costs
- Captures receipts,
- extracts the data,
- assigns spending and
- prepares the expense report.
Microsoft 365 Copilot · generally available
Finance Agent for analysis and decisions
- Brings financial data into Excel, Outlook and Microsoft 365 Copilot,
- supports reconciliations and
- prepares analyses.
Microsoft delivers the technology, the finished agent. Whether it really works in your company depends on how it is connected to your systems, your approval rules and your processes. That is where agenic comes in.
Standard or custom
When standard agents are enough and when custom finance agents make sense
Processes in the world of finance are varied. Often a ready-made agent is enough, sometimes the custom route is worthwhile. Which it is depends above all on the process itself.
Standard agents
Quick to use when process and system fit
Ready-made agents can be used quickly as soon as a process follows the common pattern and is mapped in Dynamics 365. That applies to many accounts payable workflows, as well as to clearly defined expense processes and typical reconciliations. Here the standard has an effect quickly, without much groundwork.
Custom finance agents
When processes are more complex than the standard
As soon as a process departs from the standard, a tailor-made agent is worthwhile. That is the case, for example, when several ERP systems are involved or when special processes run through DMS and email. When your own approval rules apply, country-specific requirements come into play or particular documentation duties exist, the standard quickly reaches its limits. The same is true for the transitions between finance, purchasing and operations, where several areas have to work together.
What matters is not the agent, but the process
An agent only helps if it starts where you actually lose time. How many features it brings is secondary. Sometimes a ready-made standard agent is enough, sometimes it takes custom development. What separates the two is shown on the page “What are AI agents”. The more important question comes first, though: where in the process does an agent bring the greatest benefit? At the right point, even a simple solution beats an elaborate one that misses the actual problem.
Scope & control
You define what a finance agent may do
The more an agent takes on day to day, the more important the question of the scope it works in. In finance in particular, where every posting has to stay auditable, four points decide whether it is used safely. You set them before the first agent goes live.
Access
Which systems, clients and accounts may an agent access, and which not? A role and permission concept governs that, just as it does for every employee in accounting.
Approval
What may the agent trigger itself, and from what point is human approval mandatory? Value limits and clear rules define where a transaction continues automatically and where it is submitted for review.
Traceability
Which invoice was prepared when and on what basis, and who approved it? Every step is logged and stays verifiable for internal control and auditing.
Control
Can the agent be monitored in operation and stopped if needed? Exceptions land with the team anyway, and responsibility stays with people day to day.
FAQ
Frequently asked questions
Which finance processes are particularly suited to AI agents?
Particularly suitable are workflows that recur often and require many manual steps. In practice these are often accounts payable, expense reporting and account reconciliation. As a rule of thumb: the more information comes together from different sources and the more exceptions occur, the greater the benefit.
Can AI agents post entries themselves?
They can prepare postings and create a proposal. Whether that proposal is posted automatically or only after approval is up to you. As a rule, the final posting stays a deliberate decision of the finance team.
How does the finance team stay in control?
An agent works within the boundaries you set for it. You decide which data it accesses, which steps it handles alone and where approval is mandatory. Every action is logged, so it always stays traceable what happened and on what basis.
What role does your ERP system such as Microsoft Dynamics 365 Finance play?
Your ERP system such as Microsoft Dynamics 365 Finance is the data basis the agents work on. That is where documents, posting logic and permissions sit. Several of the agents described are already part of this environment; others can be added or developed individually.
What is the difference between finance agents and classic automation?
Classic automation follows fixed rules and suits workflows that always run the same way. A finance agent comes in where context matters, for example with incomplete details or with exceptions. The two approaches often complement each other in the same process. More on this on our AI automation page.
Where does the Bank Automation Suite fit into modern finance processes?
The Bank Automation Suite specializes in bank-related workflows, for example around payment information and payment transactions. It is not an AI agent but proven automation that complements the ERP system Microsoft Dynamics 365 Finance at exactly these points. Together with ERP and agents it becomes a building block of an end-to-end finance process.
Is your finance function ready for AI agents?
An AI agent will not do your accounting for you. But it makes sure fewer steps have to be done by hand and that you can trace at any time what is happening in your finance processes. The answers to the following four questions quickly show where your company stands:
- Which finance processes are still largely manual today?
- Where do exceptions and follow-up questions pile up?
- Which data already sits cleanly in the ERP?
- Where does a person have to stay involved for compliance or control reasons?
Where the best entry point is for you is something we work out fastest together. We look at one of your processes and you see what an agent could concretely take on there.
Let’s look at your finance processes together
Every company has different workflows, systems and priorities. In the free initial consultation we look at your starting situation and clarify which next steps make sense, both functionally and economically.
Arrange an initial consultation
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