As businesses from around the world embrace digitization to cut costs and enhance efficiency, most try to leverage the financial and operational benefits offered by accounts payable software.
AP software plays a critical role in automating key processes in accounts payable, allowing companies to significantly reduce the time, cost, and errors caused by manual procedures. At the same time, AP solutions ensure timely payment of invoices by simplifying routing and approval in invoice workflows.
The software market is filled with products equipped with many AP automation features. However, regardless of which product you choose, you will find features such as OCR at the heart of each solution.
Although techniques such as OCR are an essential component of AP automation solutions, they are not sufficient on their own. In this article, we will discuss why alone is not enough to optimize AP processes.
What is OCR?
OCR is short for Optical Character Recognition, a technology that transforms digital documents into editable files with searchable text. It works by using a specialized form of image detection algorithm to recognize characters in a digital document. Using OCR, businesses can digitally capture data from a range of documents such as PDFs, as well as scanned images.
A number of industries ranging from medical records to banking, leverage this technology to process heavy loads of data. However, for the past few years, this technology has seeped into accounts payable, as well.
OCR is a key component of invoice capture in AP processes and helps companies automatically extract invoice data. Whenever the AP department receives an invoice, the OCR feature recognizes digital characters and forwards the information its algorithm has detected, eliminating the need for manual entry.
Although OCR features are necessary, invoice detection alone cannot transform your accounts payable system into a dynamic invoice workflow. You need other features to scale your AP solution along with your growing business needs.
How OCR Works?
An OCR engine is capable of detecting hundreds of different font styles and text image patterns as it feeds various fonts and text image patterns as templates in its database. OCR technology works by analyzing a document and matching it with a database of known characters. It then looks for patterns and uses them to identify each character. Once the characters have been identified, they can be converted into text that can be edited or searched. OCR technology has come a long way in recent years and is now able to recognize a wide range of characters, including those in languages other than English.
Limitations of OCR in Efficient Invoice Processing
While extracting data from an invoice is essential, we also need to categorize extracted data and transfer the data into the correct fields in the accounts payable system. For instance, if you add invoices to your accounting system, you must state the due amount, date of invoice, payment due date, as well a description of the product or service purchased.
At the same time, the system must extract information related to payee identification, such as tax identification, phone number, or address. To further complicate things, the format of each invoice is different among vendors. For accurate bookkeeping, it’s essential to precisely determine the type of document.
Some vendors might utilize invoice software to generate invoices for their orders, whereas others would transfer word processing programs or PDFs to convey the bill. The various types of file formats in invoices are highly complex, and OCR alone is not advanced enough to classify each document and its given data accurately.
This is why merely extracting data is not enough to truly automate data capture from digital invoices. Businesses need a system that can reliably transfer data from invoices to their AP software system without needing any oversight or manual intervention. If you only use OCR in your digital processes, your accounts payable process will remain static.
OCR and Machine Learning: The Foundations of a Dynamic Workflow
Machine Learning is a subset of Artificial Intelligence that lets us create software applications that solve ongoing problems by analyzing data. These intelligent solutions require minimal to zero manual intervention and are useful in every field ranging from disease detection, customer service, self-driving cars, text classification, and much more.
In the context of AP automation, the combination of OCR and machine learning can become the driving force behind intelligent data capture. While OCR extracts data from digital documents and scanned images, advanced machine learning algorithms can analyze the structure of an invoice for patterns.
Working together, these solutions can classify data and differentiate between the due amounts and address numbers (as well as other types of information) accurately. Because of these technologies, AP staff no longer needs to worry about sending invoice data into the correct fields for processing.
By using OCR and advanced machine learning, your AP staff can match up correct general ledger codes with specific transaction types or vendors. At the same time, it’s possible to transfer invoice information such as supplier identification, amount total, and invoice number into the automated accounts payable system. Similarly, these solutions can also be used to send invoices to the correct approvers for sign-off without manual effort.
The combination of machine learning and OCR lay the foundation of a dynamic Accounts Payable solution. Instead of spending time configuring rule-based logic in the AP workflow, you can rely on these technologies to learn the workflow logic as it processes invoices.
Why Managed Services Are Necessary for a Touchless AP Platform
Although machine learning and OCR eliminate the need to manage each step of the AP workflow manually, some businesses still have concerns about extracting incorrect invoice amounts.
It’s common for invoice processing solutions to receive exceptions while processing invoices. Sometimes, an impending invoice can miss vendor tax information, which leads to a sequence of errors if your solution is not ready to handle these exceptions.
When considering various automated AP solutions for your business, you must look for platforms that can handle these one-off situations effectively. For instance, some AP platforms offer managed services that transfer irregular invoices for manual review.
Whenever the solution detects an invoice with missing information such as vendor tax identification, it will direct that invoice to a managed service team for further review. Since this slight manual review doesn’t involve your AP staff, you can create a touchless account payable workflow within your business.
Capabilities for Multiple Languages
Machine learning, managed services, and OCR invoice processing can provide you with a dynamic and touchless Accounts Payable system. However, as companies grow, they need to accommodate suppliers and payees from different regions and countries. This is why many intelligent invoice processing solutions can process data from a variety of languages, helping you take your business to the international stage.
Similarly, cloud access is also a useful feature in an automated AP solution. Cloud-based AP solutions let businesses run business operations from anywhere and add multiple users with ease. Instead of being restricted to an on-premise invoice capture solution, cloud access lets you make intelligent data capture features easily accessible from anywhere, anytime.
OCR supplemented with machine learning, and managed services can optimize all AP processes and create a touchless invoice processing workflow for your company.