AI Agent

Finance Agent

Finance Agent that automates finance workflows using your data and tools.

The challenge

Close is a fortnight of spreadsheets. Analysts match bank and intercompany lines by hand, chase explanations for variances that were understood last month, and rewrite the same commentary each period. Materiality calls are inconsistent, and audit queries mean digging through mailboxes for evidence.

The outcome

Azure AI Document Intelligence reads statements and confirmations, Azure Functions run the reconciliation, and a Microsoft Foundry agent traces variances to drivers using Azure AI Search over prior periods. Journals and commentary arrive drafted; a controller approves every posting, with the rule and evidence stored.

At a glance

Type: ai agents
Category: business

Next step

Move from solution to engagement.

Build This Solution

01 — Architecture

End-to-end architecture

Ledgers, statements and sub-ledger extracts are gathered and normalised, matched by Functions, then reasoned over by the Foundry agent against policy and prior periods. Journals and commentary are proposed, checked for materiality and disclosure, and posted only after a named controller approves.

Figure 1 — End-to-end reference architecture for a financial close agent on the Microsoft stack.

02 — Workflow

Process & decision workflow

How a period is collected, matched, explained and reported — then branched. Matched, immaterial items clear automatically with their evidence retained, while unmatched or material movements go to a controller with the driver and a proposed journal already prepared.

Figure 2 — Collect → match → explain → draft → check → materiality branch → auto-clear or approve.

03 — Components

Key Microsoft components

A close agent must be reproducible and defensible — matching, evidence, approval and reporting all stay on the Microsoft stack.

Dynamics 365 / ERPGeneral ledger, sub-ledgers and the system of record.
Azure AI Document IntelligenceReads bank statements, invoices and third-party confirmations.
Azure FunctionsNormalisation, matching rules and materiality calculation.
Azure API ManagementSecure gateway for ERP, banking and treasury APIs.
Microsoft Foundry Agent ServiceReconciliation, explanation and approval orchestration.
Azure OpenAI modelsVariance commentary, driver attribution and summarisation.
Azure AI SearchGrounding over accounting policy and prior close packs.
Azure AI Content SafetyGuardrails on disclosure language and unverified figures.
Azure Logic AppsClose calendar, task assignment, reminders and escalation.
Azure SQLBalances, journals, reconciliations and approval records.
Azure Cosmos DBClose task state, checklists and per-item history.
Azure Key VaultERP and banking credentials and integration secrets.
Azure Blob StorageSource statements, evidence packs and archived close files.
Power BI / Microsoft FabricClose status, variance and management reporting packs.

04 — AI

What the agent consumes

The capabilities the agent applies across the close, and the line it does not cross.

AI capabilities embedded in the agent

Statement extraction
Transaction matching
Variance analysis
Driver attribution
Retrieval-augmented generation
Commentary drafting
Materiality checks
Anomaly detection
Journal proposal
Task orchestration
Audit summarisation
Human approval routing

AI responsibility boundaries

The agent proposes journals and commentary; a named controller approves every posting and every external disclosure. It does not change accounting policy, override materiality thresholds or publish figures that have not been reconciled. Each proposal carries its source, the rule applied and the approver.

05 — Personalization

Personalization & evolving process

The same methodology applies to every agent in the catalog. Tune the entity structure, the close template, the thresholds and the value model — the page structure stays identical.

Entity & close profile

Define the legal entities, currencies, chart of accounts, close calendar and materiality thresholds. The personas are the analyst, the controller, the finance director and the external auditor.

06 — Impact

Key outcomes & business impact

Starting targets for the value case — validate each one against the customer baseline during discovery.

Days to close−40%Reconciliation and commentary start before the period ends.
Reconciliation effort−60%Analysts review exceptions instead of matching line by line.
Variance coverage100%Every material movement carries an explained driver.
Audit readinessContinuousEvidence, rule and approver stored with each entry.