Table of Contents

OCR and Invoice Processing: Why It’s Not Enough

Invoice processing has come a long way, thanks to technological advancements such as Optical Character Recognition (OCR). However, relying solely on OCR is not enough to create an efficient and scalable invoice processing system. In this article, we’ll explore the limitations of OCR in invoice processing and discuss the additional technologies and features that can help transform your accounts payable system into a dynamic workflow.

What is OCR and How Does It Work?

Optical Character Recognition (OCR) is a technology that allows the automatic extraction of data from scanned or digital invoices. It works by recognizing and interpreting characters, such as numbers and letters, from an image or PDF file, and then converts them into machine-readable data that can be stored and processed in a computer system.

While OCR has undoubtedly revolutionized invoice processing, it’s not a perfect solution. Let’s explore three reasons why relying solely on OCR is not enough for effective invoice capture.

OCR’s Accuracy Rate Leaves Room for Error

OCR technology providers often advertise a 90% accuracy rate – an impressive figure, but one that still leaves room for error. In the context of invoice processing, a 10% error rate means that one in every ten characters will not be accurately recognized.

For businesses processing hundreds or thousands of invoices every month, this can lead to a significant number of inaccuracies. As a result, manual intervention is still required to correct these errors, ultimately reducing the time-saving benefits of OCR technology.

Invoices’ Diversity Hinders OCR Performance

OCR technology can “learn” and improve its accuracy over time, particularly when it comes to reading specific types of invoices. However, the ever-changing nature of invoices – from one-off projects to vendor turnover – makes it challenging for OCR to truly thrive in an accounts payable setting.

The constant influx of new and varying invoice formats reduces the opportunity for OCR technology to learn and improve its recognition capabilities, ultimately limiting its overall effectiveness.

A Holistic Approach is More Effective than Point Solutions

Accounts payable is a complex and time-consuming process. Instead of investing in a single solution like OCR, businesses should consider adopting a more comprehensive approach that tackles pain points across the entire accounts payable process.

AP automation solutions combine OCR technology with human review to ensure a higher level of accuracy (typically around 99.5%) for every invoice. Furthermore, these solutions streamline the entire accounts payable process, from invoice capture to approval and payment authorization.

Going Beyond OCR: Machine Learning and AP Automation

While OCR is a powerful tool for invoice processing, it can’t solve all the challenges faced by businesses when managing their accounts payable workflows. This is where machine learning comes into play.

Machine learning, a subset of artificial intelligence, enables software applications to learn from data and improve their performance without manual intervention. By combining OCR with machine learning, businesses can create a more robust and efficient invoice processing system.

How Machine Learning Enhances OCR

OCR technology extracts data from digital documents, while machine learning analyzes the structure of an invoice to identify patterns. Together, they can discern critical information, such as the difference between an address number and the amount due.

This integration allows accounts payable software to accurately place extracted invoice data into the correct fields for processing within the system. Machine learning automates tasks that once required manual oversight, such as:

  • Matching general ledger codes to specific vendors or transaction types
  • Transferring invoice information (e.g., invoice number, supplier identification, and amount total) into the automated accounts payable system for payment processing
  • Sending invoices to the correct approver for sign-off

Moreover, machine learning enables companies to quickly implement an automated solution. Traditionally, setting up an automated accounts payable workflow required configuring rule-based logic before launching a new platform. However, machine learning allows the AP software to learn the workflow logic as it processes invoices.

Enhancing Invoice Recognition with Managed Services

Even with OCR and machine learning working together, there may still be concerns about potential errors or missing information in the invoice processing system. To address these concerns, businesses should consider incorporating managed services into their accounts payable platform.

Managed services involve a dedicated team conducting manual reviews of invoices when the invoice scanning software triggers an alert (e.g., missing vendor tax identification). The AP system automatically routes the invoice to the managed service team for review, without requiring manual intervention from your company’s accounts payable staff.

This additional layer of oversight creates a “touchless” accounts payable workflow, allowing your team to focus on tasks that require a human touch, such as customer-facing issues or revenue-generating initiatives.

Additional Features to Enhance Invoice Recognition Software

OCR, machine learning, and managed services form a powerful trio for an automated accounts payable system. However, businesses should also consider additional features that can further enhance their invoice processing capabilities.

Multilingual Capabilities

As your business expands beyond domestic operations, it’s essential to have an invoice recognition software that can process data from various languages. This capability ensures that your accounts payable system can scale with your growing business.

Cloud Access

A cloud-based software allows companies to add multiple users with ease and enables businesses to run operations from anywhere. Opting for a cloud-based platform means that anyone with an internet connection can access your automated accounts payable system, further streamlining your invoice processing workflow.

In Summary

OCR technology has undoubtedly improved invoice processing, but relying solely on OCR is not enough for an efficient and scalable accounts payable system. By integrating machine learning, managed services, and additional features such as multilingual capabilities and cloud access, businesses can create a robust and dynamic automated accounts payable workflow.

Remember, the key to success lies in the details. By leveraging a combination of OCR, machine learning, and other technologies, businesses can create a “touchless” invoice processing system, freeing up their accounts payable team to focus on more critical tasks and driving revenue generation.