Two-way matching, also known as purchase order matching, is a crucial business finance process that verifies purchase order (PO) details against invoice details before authorizing payment. The goal is to ensure that the products or services ordered were delivered accurately and at the agreed-upon prices, ensuring no overpayments or payments for undelivered goods/services. This process enhances financial control, fosters trust in vendor relationships, and adheres to compliance standards.
Businesses typically follow a specific process for two-way matching. Initially, a purchase order is issued detailing the order and prices. Then, the vendor delivers the goods/services and provides an invoice. The next step is to match the details on the invoices with those on the POs, verifying that the invoice price is lesser or equal to the PO price and the invoice quantity is lesser or equal to the quantity ordered in the PO. If the match is successful, payment is initiated. However, if there is an unsuccessful match, the invoice processing and payment is paused, and the accounts payable manager manually checks the invoice, either approving or rejecting the invoice payment.
Small companies often engage in manual two-way matching, which involves the Accounts Payable (AP) team carrying out these procedures manually. However, this can be time-consuming, especially for large companies with a high volume of transactions. Therefore, many companies are turning to automated two-way matching systems, where an AI system automatically verifies invoice details against PO details, speeding up the process and reducing the risk of human error.
Several two-way matching tools, such as Nanonets, Oracle’s Payables, Sage Intacct, Nexonia Expenses, Tipalti, and DocuWare offer varying features to meet different business needs. Nanonets, for instance, simplifies invoice processing by auto-importing invoices and POs, using AI for accurate data entry and matching, flagging mismatches for easy review, and updating data in real-time.
Automated two-way matching offers several benefits. For instance, it enables paperless handling, quick matching of POs, easy handling of large volumes of documents, and reduces the risk of errors and fraud. It also provides cost savings, and fosters secure and scalable operations.
In conclusion, two-way matching is a critical process in business accounting aimed at ensuring accurate and ethical transactions. While manual two-way matching can be tedious and error-prone, automated solutions make the process more efficient and reliable. Therefore, businesses should consider integrated, AI-powered two-way matching systems to streamline their invoice processing and secure their financial operations.
