Digital transformation isn’t as easy, or simple, as turning a switch that’s “off,” “on.”
Rather, it’s a series of interlinked and ideally compounding process modernizations. Digital transformation takes time.
And within the engine of progress, optical character recognition (OCR) is proving to be a key piece powering step-by-step advances for businesses, particularly within accounts payable (AP) and accounts receivable (AR) departments looking to unlock new opportunities by streamlining workflows and advancing the larger goal of eliminating paper-based inefficiencies.
Historically, both AP and AR functions have been bogged down by manual processes and mountains of paperwork, with employees spending countless hours sifting through invoices, purchase orders and other transactional documents. While digitization has already transformed parts of these processes, a significant portion of AP/AR tasks are still linked to paper documentation.
OCR, once viewed as a niche solution primarily focused on digitizing printed text, is now emerging as a cornerstone in the automation of AP/AR processes.
By enabling machines to “read” and interpret unstructured or semi-structured documents with greater accuracy, OCR is addressing some of the most persistent challenges in AP/AR.
Read also: Unlocking the 3 Biggest Benefits of Automating Accounts Payable
Powered by advances in computational capabilities and artificial intelligence (AI), OCR is a key moving part in the engine driving digitization — helping firms improve data extraction and reduce errors in invoice processing.
After all, despite the proliferation of digital payment methods and automation tools, paper invoices, purchase orders, and checks still play a prominent role in many organizations, especially in small and medium-sized businesses (SMBs). The PYMNTS Intelligence report “Getting Paid: Digital Payments for Improving Cash Flow and Customer Experience” found that 75% of companies still use paper checks.
The reliance on paper creates inefficiencies, such as delays in payment processing, errors in manual data entry, and difficulty in tracking invoice status. It also increases costs related to storage, printing, and postal services. The PYMNTS Intelligence report “Businesses at Risk: The High Cost of Manual AR Processes and What to Do About It” revealed that 59% of U.S. businesses link poor cash flow and forecasting to outdated manual AR methods.
In a world where digital workflows are becoming the norm, paper remains an outlier — but an important one. This is where OCR comes into play, converting physical documents into digital assets that can be processed automatically.
Initially, OCR was limited to reading printed text, but new advancements allow it to decipher more complex documents with various fonts, layouts and handwritten elements. This evolution is crucial for AP/AR departments, where invoices and related documents often follow non-standardized formats, complicating efforts to automate their processing.
That’s because modern OCR systems are now powered by machine learning (ML) and AI, allowing them to “learn” from past errors and improve accuracy over time. These systems can also be trained to recognize specific formats, logos, or document layouts commonly used by a particular supplier, resulting in better interpretation of invoice data.
This improvement is critical for AP/AR departments, where even a small percentage of errors can lead to significant delays, additional manual interventions, and, ultimately, dissatisfied vendors or customers.
Learn more: 4 Questions for CFOs About AP and AR Automation
The PYMNTS Intelligence report “Automating Accounts Payable for Cost Savings” found that 34% of businesses process more than 5,000 invoices per month.
Absent the assistance of digital tools, the sheer volume of an AP/AR department’s to-do list can leave many employees drowning in paperwork. Fortunately, the application of OCR technology in AP/AR goes beyond simply converting physical documents into digital form. It fundamentally transforms the entire workflow, bringing automation to previously manual tasks and enabling organizations to adopt a paperless strategy.
By extracting key data from invoices — such as invoice number, supplier details, payment terms and line-item information — OCR reduces the need for manual data entry, which is often prone to errors. This ensures that invoices can be processed faster and more accurately, reducing the chances of late payments or disputes. OCR can also be integrated with other software tools to automate the three-way matching process, which compares the purchase order, the goods received and the invoice.
The PYMNTS Intelligence report “CFOs Eye Accounts Receivable as New Direction for AI Investments” found that 55% of chief financial officers representing middle-market businesses would be willing to pay 3% of the invoice amount to accept payments using a solution that automates invoice approval and payment.
However, while OCR represents a significant step forward, it is not the final destination. It must be implemented alongside complementary technologies like RPA and AI-driven analytics to unlock its full potential. For organizations willing to invest in these technologies, the benefits are clear: faster payments, better financial controls and a more agile, responsive finance department capable of supporting the broader goals of digital transformation
Together, these innovations are reshaping the landscape of AP/AR, paving the way for a future where manual processes and paper-based inefficiencies become relics of the past.
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