AP Invoice Automation

Intelligent Document Processing comes into play here. IDP leverages OCR (Optical Character Recognition) and machine learning models to extract relevant data from the invoices, such as vendor name, invoice number, date, line items, amounts, and taxes. This eliminates manual data entry, reducing errors and accelerating the process.

Extracted data is validated against predefined rules and master data (vendor lists, POs, etc.). RPA bots can check for discrepancies, duplicates, or missing information. IDP can also be used to enrich data by extracting additional details from unstructured parts of the invoice.

For PO-based invoices, RPA bots perform a three-way match between the invoice, the purchase order, and the goods receipt. If there's a match, the invoice is approved for payment. If there are discrepancies, the process may be paused for manual review or handled based on pre-defined rules.

RPA bots can initiate and manage the approval workflow, routing invoices to the appropriate approvers based on predefined rules. The approval process can be automated using digital signatures or notifications.

Once approved, RPA bots can initiate payment processing, integrating with the ERP system or banking software to generate payment files or directly execute payments.

RPA bots archive processed invoices in a structured repository, ensuring easy retrieval for audit or analysis purposes. They can also generate reports on invoice processing metrics, providing insights into bottlenecks, turnaround times, and cost savings.