Automating invoice processing helps reduce repetitive tasks, saving your finance team plenty of resources. It also minimises the potential for human errors, increasing overall efficiency and accuracy.

Here’s a few ways automation can benefit you:

Invoice Capture:

AI-powered invoice capture builds on legacy Optical Character Recognition (OCR) technology that can scan and digitise your paper invoices, by adding context to the document. That means it not only ‘reads’ what’s on an invoice, but it understands what each datapoint means thanks to its deep understanding of the invoice format, and can also fill in or correct missing or inaccurate information. This allows for faster data capyure as well as increased consistency and accuracy when it comes to capturing invoices, even if they come in various formats.

Data extraction:

AI tools can accurately extract and structure data from invoices, such as invoice number, date, amount, and supplier details, directly into the accounting system. Natural Language Processing (NLP) can even understand and extract relevant information from unstructured data within invoices.

Data validation:

AI can cross-check extracted data against existing records and databases to ensure accuracy and consistency for a real-time data check. This way, AI algorithms can identify anomalies or discrepancies in invoice data, such as incorrect totals or mismatched supplier information. Moreover, verification could be calling back to your supplier database to validate that a supplier is legitimate, and it could also include performing checks against watch lists and banned suppliers.

Reducing human errors:

Machine learning significantly reduces the likelihood of human errors and fraud that can happen with manual data entry and checks. Being able to rely on accurately captured data gives you the ability to streamline your workflow and focus on higher-value tasks. With ML-powered automation handling repetitive and error-prone processes, your team can spend more time on strategic activities, such as analysing spending patterns and optimising supplier relationships. Additionally, the improved accuracy and consistency provided by ML minimise the need for rework and corrections. This reliability also builds greater confidence in your financial data, enabling better decision-making and fostering a proactive approach to managing compliance and risk.

Customised approval workflows:

AI can create customised approval workflows based on your company’s policies, ensuring that invoices are routed to the right approvers. While legacy automation technology is restricted by using a few pre-built templates, artificial intelligence is able to dynamically adjust workflows in response to changes in the environment, without needing a template. For example, if an invoice comes from a supplier on a company’s watchlist, AI would send the invoice through a different route than if it was a validated invoice from a utility company, which is might automatically approve because it knows the route such invoices normally take through the company.

Smart coding:

AI can automatically assign general ledger (GL) codes to invoices based on historical data and predefined rules. This automated process saves time and enhances the accuracy and consistency of financial records. Moreover, machine learning can predict the correct expense categories for invoices based on learning from how your people have coded invoices in the past, improving coding accuracy and ensuring that costs are properly categorised for further reporting and analysis.