AI for Finance, Accounting and Procurement
Processes, use cases and architecture
Invoice extraction, purchase order/receipt/invoice matching, anomaly detection and cash forecasting. An OCR/extraction/rules pipeline matches documents; ambiguous cases enter a review queue. Forecasts use historical series and out-of-sample model evaluation.
Required data and applications
Finance ERP, invoices, purchase orders, supplier master data, accounting rules and payment history. Permissions and segregation of duties remain in force.
Human accountability and limitations
Time per invoice, correct matching rate, false positives and forecast accuracy. An anomaly score does not prove fraud. Accountants approve entries and authorised staff approve payments.
Measuring benefits
The pilot compares a baseline with the target process on representative cases. Business owners define quality thresholds and the right to revert to manual processing before launch.
Bringing the right expertise together
FAQ
How can AI be integrated into an ERP?
Define a specific task, assess data and APIs, separate reads from writes, then test a connector with restricted permissions. Consequential writes and decisions require approval, logging and rollback.