How AI Invoice Processing Works

Artificial intelligence (AI) has captivated and inspired us since the dawn of mankind. We can see this in the myths and stories of civilizations throughout the world, from sentient statues like Pandora or the Golem to emotional robots like R2D2 and C3PO.

It was perhaps inevitable that AI evolved from mythological concept to mainstream tech, but when you stop to think about it, the technology and its capabilities are no less incredible than tales of living clay mannequins and tin men with hearts. To show you what we mean, we’ll leave the realms of fantastical mechanized beings and enter the no-nonsense world of invoice processing. No, we’re not taking you to limbo, though that’s where your company’s accounts payable (AP) team may feel like it is if it’s extracting data manually or using a template-based optical character recognition (OCR) solution.

Without further ado, let’s get a better understanding of AI and how it processes invoices, as well as how AI-powered data extraction can transform not just AP but your entire organization.

What is AI?

Before we get into AI invoice processing, let’s take a closer look at the technology itself. Put simply, AI is a machine-based simulation of human thought processes. This is a broad term that we can break down into subsections according to level of intelligence. In the context of automated data extraction, we’re most interested in deep learning, which enables computer programs to learn, reason, and correct themselves without human intervention. This highly advanced capability is powered by networks of algorithms known as artificial neural networks.

We’ll just take you a little further down this rabbit hole before we move on to more specifics about AI and invoice data capture. Think of an artificial neural network as a digital brain, where layers of algorithms simulate a human brain’s neurons, interconnecting with each other just like neurons do. Every single one of these algorithm layers is capable of learning specific information with continued use. The use of several layers creates depth; that is, artificial neural networks are capable of self-sufficient deep learning.

The headline-grabbing applications of artificial neural networks include self-driving cars, facial recognition, and medical diagnosis. Each of these three developments come with controversy: US lawmakers still haven’t passed legislation regulating autonomous vehicles, privacy advocates are concerned about the use of facial recognition tech for surveillance, and the medical world has yet to fully embrace deep learning tools “because they solve problems in ways that humans can’t always follow.”

Automated invoice data capture is not as glamorous and contentious as robot vehicles, intelligent CCTV, or smart medical image analysis. But you and your company’s AP department may find it a more practical and transformative application of deep learning. 

AI invoice processing is not fantastical – it’s fantastic

As we have just seen, OCR alone is not capable of processing invoices on its own. All it does is convert images into text that you can work with. To get useful output, you need to instruct traditional OCR invoice recognition software constantly, feeding it new templates and rules for every new invoice your company receives.

A combination of OCR and AI-powered data extraction frees you from this endless loop of instruction. An OCR platform with powerful neural networks can understand and process text contained in each data field in the invoice. With continuous use, deep learning capabilities enable the software to recognize new invoice formats with little to no human intervention – every now and again, minor corrections may be required.

This is a really big deal, especially if you’re working in a financial function. Financial documents are complex and variable. While the data they contain tends to be consistent across all of them, most companies tend to have their own invoice templates, and there are no naming standards for invoice data fields. For example, “Total”, “Amount Due”, and “To pay in USD” can all mean the same thing. 

A simple OCR program is not going to understand any of these differences. With a lack of rules comes an increased risk of inaccurate data capture, and consequential accounting errors. 

AI brings understanding to OCR invoice recognition – it learns templates and naming standards on its own, with occasional assistance from a human operator. It is this application of deep learning that makes AI invoice processing as fascinating as a thinking, feeling robot – it can be transformative, not just in a business context, but also in an individual context, giving AP team members opportunities to take their roles out of the back office and into the front lines.

“AI that can read and understand an invoice at a human level can also be made to do the same work many times faster than a human. If you train a neural network to recognize and work with invoices it has never seen before (just as a human can do), you can turn hundreds of hours of tedious work into a few seconds or minutes of computer processing time.”

Rossum CEO Tomas Gogar, speaking to StartupYard in Exclusive Interview: Rossum – AI for Documents

The benefits of AI invoice processing are real

Of all the use cases for AI-powered data extraction, invoice processing is one of the most significant. The right platform can bring multiple advantages to your AP team and your organization as a whole, including:

Faster invoice processing

This side-by-side comparison of manual data entry and AI invoice processing is like a race between a toddler and Usain Bolt: no contest.

Consider that for one invoice manual data extraction took over three and a half minutes, while AI-enabled extraction took just under 27 seconds. Future invoices from the same supplier will require even less time to process, as the platform now recognizes it and no longer requires human validation. The solution gets smarter with every new invoice it processes; therefore, our example company will eventually have the option of fully automated invoice processing.

Increased productivity

AI saves time on data entry and correction, and eliminates tiresome template and rule creation, enabling AP staff to focus on value-generating activities, such as

• Financial planning
• Tracking company spend
• Deriving actionable insights from analytics
• Collaborating with other corporate functions, such as Procurement
• Strengthening vendor-customer relationships

More accurate data extraction

A deep-learning AI-enabled data capture solution learns to extract data from any invoice template as accurately as a human, using its neural networks to increase its understanding and capabilities with every document it processes. Unlike a human data entry clerk, smart invoice processing software does not come with the risk of making errors due to, for instance, the fatigue of carrying out a dull repetitive task.

Greater impact on financial objectives

Automated invoice data capture increases cost savings in AP. The financial advantages are not limited to AP savings, however. The benefits that AI invoice processing offers to your bottom line include:

• Timely invoice approval and payment can result in early payment discounts from suppliers, increasing profit margins
• More efficient invoice processing can help streamline processes that are directly or indirectly connected to the AP function, e.g. Procurement, Purchasing, Production, and Distribution
• Faster, more accurate invoice data capture helps you monitor and optimize your organization’s working capital, potentially in real time

“Businesses today are expecting more from their AP function. They realize that if they can get at the information and data housed in their AP department, they can use it to support better management of their working capital, mitigate potential risk, and make more strategic decisions,”

Mark Brousseau, Spokesperson for the Institute of Finance Management, How smart data extraction makes for smart AP automation, Spend Matters.

AI-powered data extraction in action

Time for another example of how swiftly Rossum captures OCR invoices:

As the video shows, Rossum’s AI-powered data extraction enables you to batch process invoices in just four easy steps:

1. Import invoices – upload PDFs or scanned invoices.
2. AI processing – wait a couple of minutes for Rossum to automatically extract data.
3. Review data extraction – if necessary*, validate captured data in Rossum’s intuitive UI.
4. Export data – download captured data into your ERP or accounting system.

* This step is only necessary if you’re processing new invoice formats, or if you want to validate data shortly after you’ve implemented Rossum.

This simple procedure never requires you to set up rules or templates to capture data from the invoices you import. You can use Rossum to extract data from a wide variety of invoices immediately. That’s because Rossum works just like humans do – our AI researchers developed a proprietary deep learning technology that understands the general structure of invoices and can learn new templates on its own. The tech itself is a marvel; to make it useful to you in the actual AP process, we built an intuitive user interface that makes Rossum a breeze to work with.

Rossum’s AI is transforming AP

Deep learning AI gives Rossum the power to save mankind from the drudgery of manual data entry and the hassle of setting up templates and rules for traditional OCR software. In some ways, this real-life AI story is more exciting than the myths and legends it is rooted in, as well as the future tales it inspires.