AI Powers a Changing of the Guard

The Essentials

Processing invoices is a necessary part of doing business. If a company buys something from a supplier, the company has to pay for it – and ironically, processing and paying the invoice costs time and money on top of the amount billed. Companies have long sought ways to automate invoice processing in order to reduce the cost of paying to pay.

To reach acceptable levels of automation, invoice processing has traditionally required large datasets to train the systems and extensive professional services to integrate the data capture into the enterprise resource planning (ERP) systems. The expense and time-to-value have relegated this to a niche solution. After nearly 30 years, it would be reasonable to think invoice processing is a very mature niche market dominated by a handful of vendors and predictably lacking in innovation.

But things are about to change. As with many other legacy software segments, AI is radically disrupting the staid invoice processing marketplace. This Brief describes the marketplace and the recent events that are shaking it up.

The Evolution of Invoice Processing

Every business must pay its suppliers, and every supplier sends invoice documents to businesses containing the essential data to process and complete the payment. It’s up to someone in accounts payable to read the invoice, find the data, and enter that data into the accounting system so the invoice can be recorded properly and paid. Despite several initiatives over the years, as of today there is still no industry standard template for invoices. They come in all shapes, colors, and sizes, and the data is rarely found in the same place from vendor to vendor.

This lack of standards means that every invoice needs special attention from a human. The cost to process a single invoice can be as high as $13, according to the Institute of Finance & Management. It’s no wonder that business managers have long sought ways to automate invoice processing and drive that cost down as far as possible. Automation can also save cash in another way: faster invoice processing means a business can more often take advantage of early payment discounts offered by suppliers.

Extracting data from invoices by using computers instead of humans became a leading use case for document capture and process automation in the 1990s. Several capture start-ups, led by Readsoft, flourished by creating software to read scanned invoices without human intervention and deliver some of those promised savings and efficiencies. As businesses moved from mailing paper invoices to emailing PDFs, capture vendors added PDF data extraction alongside scanned capture. (Paper invoices show no sign of disappearing and will be part of any solution for years to come.)

The largest capture companies today (Kofax, OpenText, Hyland, ABBYY) sell invoice processing, as do their top challengers (Ephesoft, IRIS, KnowledgeLake, and others). In our estimation, well over 100 software companies are marketing an invoice data extraction or invoice processing solution. And there are over 66,000 projects for invoice processing and data extraction on the GitHub development platform, a leading indicator of the mainstream demand for this type of solution.

Most vendors focus on integrations with SAP or Oracle, the leading financial software for large enterprises, to pass the extracted data directly into the ERP system. These solutions can be very expensive, with deals over $1 million not uncommon and professional services engagements lasting several months to years. Other capture vendors focus on the small and mid-sized enterprise (SME) market and enable financial software such as Microsoft Dynamics and Sage.

The largest barrier to entry for competition has been the enormous task of gathering the pre-existing invoice samples required to train machine learning algorithms to achieve a reasonable level of automation (typically 60%-70%) and produce a good ROI. For many years, the legacy leaders had the advantage with their training databases of hundreds of thousands or even millions of invoices. Their solutions were less about “AI” and more about matching an invoice with a template in the database. But that advantage is now slipping as new competitors using deep learning enter the market.

Four Events That Rocked the Invoice Processing World

Four big events happened in the second half of 2021 that we believe will transform automated invoice processing from a niche market to a mainstream application used by every business. We also predict that these events foreshadow an eventual changing of the guard, with current market leaders passed by new entrants.

Rossum raised $100 million

Rossum, an AI start-up from the Czech Republic, raised an eye-watering $100 million in Series A funding for its invoice data extraction cloud platform. While Rossum’s valuation wasn’t published, in our estimation – which is in line with the industry’s thinking – Rossum’s valuation alone could surpass the total annual invoice processing revenues of the legacy market leaders (see Figure 1). Clearly, some investors believe in the unlimited market potential of invoice automation. (Rossum also announced plans to offer data extraction for all business documents.)

Rossum is a prime example of the new generation of AI-driven start-ups that are leveraging the deep learning advancements from Google, Amazon, and Microsoft to disrupt the cognitive capture market (see Table 1). Today, the availability of vast and cheap deep learning models has eroded the legacy leaders’ advantage, as start-ups can now deploy advanced deep learning models capable of learning faster with far fewer samples than the old ML models. In addition, the start-ups are using the cloud, so they can potentially offer quick and easy integrations into almost any financial software.

Figure 1
Rossum vs. the Legacy Leaders

Microsoft entered the ring

At Ignite 2021 in November, Microsoft introduced an invoice data extraction model for SharePoint based on its Syntex deep learning platform. The Microsoft team demonstrated how a “citizen developer” can create an out-of-the-box, end-to-end invoice payment approval process for its ERP solution, Dynamics.
SharePoint is completely integrated with PowerAutomate, Microsoft’s no-code drag-and-drop RPA application, so creating the workflows and the bots is straightforward. To monitor invoice flows, PowerBI, Microsoft’s business analytics tool, adds a full-featured dashboard.

In addition to enabling its own financial platform, Microsoft is also going after SAP and Oracle through its acquisition of Clear Software, which provides deep connectivity to their systems. We’ve talked with legacy vendors who think the Microsoft solution still has a long way to go to reach parity with the existing products, citing barriers such as SharePoint library limitations and lack of transparency into the AI models. But they also expect Microsoft will get there in time.

Table 1
Some of the Cool Start-ups Challenging the Leaders

SAP got in the game

At TechEd2021 in mid-November, SAP announced SAP Process Automation, its new low code/no code hyper-automation platform that integrates its new document extraction AI skill (based on its Leonardo machine learning platform) with its RPA bots (Contextor rebranded), SAP Workflow Management, and SAP Business Intelligence. To demonstrate the new platform, SAP issued a video showing (you guessed it) how to create an out-of-the-box, end-to-end invoice approval process using easy-peasy drag and drop.

With the integration of its powerful BPM capabilities, SAP can now offer a serious alternative to any BPM/BPA/hyper-automation competitor. The key benefit here is the tight integration of invoice processing within the SAP automation and AI ecosystem.

AWS lowered costs with an API

For those who prefer to roll their own, AWS recently introduced a new invoice processing API for Textract, Amazon’s text extraction service. AnalyzeExpense API can extract line-item details and key-value pairs from invoices and receipts. Textract uses machine learning to understand the context of invoices and receipts, and automatically extracts specific information like vendor name, price, and payment terms. It claims to work on any style of invoice or receipt, and there are no templates or configuration required.

The raw cost per invoice processed is among the lowest out there: in the US, you’d pay $0.01 per page for the first one million pages and then $0.008 per page. Also, AWS makes it very easy to try before you buy.

Call to Action

Now is a good time to explore your options for improving your invoice processing solution.

— If you’re a large enterprise, take notice that low-cost, easy-to-use invoice processing is now poised to become a feature function bundled in the stack from your choice of financial software vendor. Or you may opt for a customized solution built on AWS by your in-house team or a global system integrator such as Cognizant or Wipro.

If you’re a smaller enterprise using other financial software, you can opt for the low cost and simplicity of integrating a cloud solution such as Rossum’s or those from other start-ups.

— In either case, when should you consider a switch to these new solutions? We recommend that you at least investigate and run a proof of concept to game out the potential cost and efficiency improvements. If you’re a Dynamics shop, why not put the new SharePoint on your shortlist for invoice process automation? If you’re an SAP shop, why not use SAP’s integrated invoice processing and eliminate the cost and the hassles of third-party integration? Anyone else can test their invoices on one of the new cloud-based solutions.

If you are wondering what’s to become of the legacy invoice processing solutions from today’s market leaders, we think they will be around for a while. Switching takes time; rip and replace is not that simple. End-to-end invoice processing automation involves more than the data extraction and workflow parts. The legacy vendors have also accumulated years of experience at working out the details of the process, which for some businesses can be quite complex. Their skills will count for something against the start-ups.

Still, they are in for the fight of their lives to compete with the new economics and the new speed-to-value from these new entrants. ABBYY for one has recently shipped its Vantage platform with pre-trained deep learning skills for invoice processing.

What’s certain is that invoice processing is a real-world example of how AI-driven cognitive capture can improve a core business process for every company, and we at Deep Analysis will continue to follow the evolution of this market closely.

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