AI-OCR is Reshaping AP

Published Jan 3, 2024

Revolutionising the Accounts Payable Function with AI-OCR

In the world of business, the procure-to-pay process packs a powerful punch.

The Accounts Payable (AP) function is a critical component of a company’s procure-to-pay cycle because it ensures financial transactions related to procurement are handled accurately, efficiently, and in compliance with policies and regulations.

It helps manage cash flow, build vendor relationships, maintain compliance, control costs, provide financial data for reporting, and contribute to overall efficiency and accountability.

Because it is responsible for managing and recording the company’s outgoing payments to suppliers, vendors, and creditors, effective AP management is crucial in ensuring the financial stability and smooth operation of a business.

Let’s delve into key technology that has transformed the AP process.

Technology and the AP Function

In the past, AP departments relied heavily on paper-based, manual workflows, where invoices arrived via mail, and payments were made using printed cheques.

Technology has revolutionised invoice processing and other core AP activities by automating processes, improving accuracy, reducing costs, enhancing security, and providing better visibility into financial data.

These advancements have not only increased business efficiency but have also elevated the strategic importance of AP within organisations.

As businesses continue to seek ways to streamline operations and enhance financial management, technology remains a primary enabler for achieving these goals within the AP department.

The Traction of OCR Technology

Optical Character Recognition (OCR) is a technology that gained traction in the late 20th century as a tool to convert printed or handwritten text, numbers, or symbols into machine-readable, digital text.

As businesses sought ways to improve efficiency and reduce manual data entry errors in their AP processes, OCR technology found its way into the AP function. By the early 2000s organisations started implementing OCR software to automate the extraction of data from invoices, purchase orders, and other financial documents.

With advancements in OCR technology and the integration of OCR solutions with other financial software systems, the adoption of OCR in AP accelerated in the mid-2000s.

Organisations increasingly relied on OCR to expedite invoice processing, reduce manual intervention, enhance data accuracy, and become more responsive to the demands of a dynamic business environment.

Combined with other automation tools, OCR technology transformed the AP function by making it more streamlined and digitally driven.

Artificial Intelligence (AI) and OCR

The application of OCR in the AP function has continued to evolve and improve, with the integration of artificial intelligence (AI) and machine learning (ML) technologies.

The single biggest benefit of AI-OCR is the ability to automatically capture information contained on a document of virtually any format, and then use the data to automate what would otherwise be time-consuming tasks with high potential for oversight or error.

In addition to automation, modern AI-OCR solutions utilise advanced algorithms and statistical models to enhance accuracy by continuously improving text and image recognition capabilities.

While the intelligent part of AI-OCR enables it to predict (with a degree of confidence) the context of the data it reads, if it makes an incorrect assumption, the machine learning capabilities mean user corrections can help it refine its contextual predictions and improve recognition accuracy over time.

These advancements have further improved data capture and extraction accuracy and have enabled more intelligent automation of AP processes making it an indispensable technology for the digital age.

Key Differences: Traditional OCR v AI-OCR

Both traditional OCR and AI-enhanced OCR technologies are used to automate and streamline document processing tasks; however, they have key differences in their capabilities and impact on the AP process.

Traditional OCR

  • Basic Technology: Converts printed or handwritten text from scanned documents or images into machine-readable text.
  • Rules-Based Approach: Uses predefined rules and templates to identify characters and words in images. It relies on pattern matching and templates to recognise text.
  • Limited Adaptability: OCR’s recognition accuracy is often limited by factors such as font variations, low-quality scans, and unusual text layouts. It may struggle with handwriting or complex fonts.
  • Language and Format Support: OCR systems may support multiple languages, but their ability to handle diverse fonts and formats may be limited.
  • Accuracy: OCR accuracy can vary depending on the quality of the input image and the complexity of the text. It may require manual corrections in some cases.

AI-enhanced OCR

  • Advanced Technology: AI-OCR is an evolution of OCR that incorporates AI and ML techniques to improve text recognition.
  • Machine Learning Algorithms: AI-OCR uses ML algorithms, including neural networks, to learn and adapt to various fonts, languages, and text layouts. It can continuously improve its recognition capabilities.
  • Adaptability: AI-OCR is more adaptable and robust, capable of handling a wide range of fonts, languages, and document formats. It can also recognise handwriting and cursive writing to some extent.
  • Accuracy: AI-OCR typically offers higher accuracy compared to traditional OCR. It can achieve near-human levels of accuracy in many cases, reducing the need for manual corrections.
  • Real-Time Processing: AI-OCR can process text recognition tasks in real-time or near-real-time, making it suitable for applications like mobile scanning and document automation.

While both traditional OCR and AI-OCR perform core text recognition functions in the AP process, AI-OCR offers advanced capabilities, adaptability, and automation, making it a more efficient and accurate choice for modern AP automation and processing needs.

Core components of Predictive Maintenance

Boosting the Accounts Payable Function with AI-OCR

Online requisition management workflow solutions are designed specifically to address procurement process inefficiencies; right from the initial point of requisition to the moment the purchase order (PO) is received.

Streamlining and automating each stage of the procurement process minimises the number of additional tasks filtering through to the AP team.

When AP workflow functionality is integrated with a requisition management system, the processing of AP invoices becomes automated.

However, a crucial first step in this process has traditionally been manually entering AP invoice data into the system such as header or line details. This manual entry can – and has – resulted in delays and errors which have quickly grown into costly problems for many businesses.

This is where AI-OCR technology integrated with a requisition management system can shine.

For both PO-related and non-PO (miscellaneous) AP invoices, AI-OCR technology can scan and lift data from an invoice to automate the process of entering AP invoice data.

If an inaccuracy or anomaly occurs from the initial AP invoice scan, and the AP team makes a correction in the system, artificial intelligence updates the AI-OCR process, assigning a higher ‘confidence’ to the corrected value which increases the accuracy of subsequent scans. So, the more the AI-OCR technology is trained, the more it learns, and the more accurate it becomes.

Ultimately for the AP team, their role in this crucial first step becomes one of exception handling.

AI-OCR can also significantly reduce the time spent manually matching PO invoices with PO receipts. AI algorithm functionality examines part numbers and several other fields on scanned invoices to identify potential matches among open PO receipts.

When large volumes of invoicing are required, AI-enhanced OCR is better equipped than traditional OCR to handle the complexities and variations encountered in financial documents. This capacity to automatically capture, extract, and validate data from PO invoices, and match to PO receipts, enables businesses to process invoices more efficiently, reduce errors, and gain better visibility into their financial obligations.

Is your business ready to embrace AI-OCR for your AP functions?

Whilst many procurement and AP automation systems offer OCR or Intelligent Data Capture (IDC) technology, there are few that include AI along with machine learning.

If you are looking for a functionally rich, yet affordable, procure-to-pay solution that has been built for Epicor Kinetic and Epicor Cloud and embraces the latest AI-OCR technology, look no further than Advanced Requisition Management.

Contact us to discuss your procurement and AP automation requirements. If you like what you hear, we can set up an obligation free demo so that you can take a closer look.


Inspired to Act?

Book a Discovery Call with one of our product specialists to learn more about how an ERP system can transform your business.
Subscribe to our LinkedIn Newsletter and get alerts when we post about topics that matter to you.