How OCR invoice automation can help you create a paperless office

OCR invoice data entry: A little less human, a lot more effecttive

Manual or OCR invoice? Discover the highs and lows of manual invoice data entry from a former data entry clerk as he breaks down the realities in a more personal way. Read about the experience of paperless invoices, with automated OCR invoice processing. 

OCR invoice

One of the most important departments in your enterprise is your accounts payable (AP) team. The AP team is responsible for capturing the data from invoices, coding invoices, connecting invoices with purchase orders, and posting for payments. Without this valuable work, organizations would not be able to purchase or pay for supplies. 

There are three main documents in the accounts payable workflow: the purchase order (PO), the receiving report (or receipt), and the vendor invoice. 

For large and small businesses, the cycle of making and documenting purchases is nothing new. Most organizations have experienced this cycle hundreds of times: 

• First, the buying organization makes a purchase from a vendor. 
• Then, the vendor then creates an invoice and sends it to the buying organization. 
• After that, the AP department in the buying organization is responsible for processing that invoice and sending it to the accounting department — where it is then paid for. 

For decades, invoices have been processed manually. Even today, variable invoice formats and low tech capacity are reasons why many businesses still use manual invoice processing. 

With manual data processing, the valuable time of skilled employees is taken up by repetitive, manual processes. Manual invoice processing is error-prone and demotivating for your AP talent — nevertheless, it’s all too common. 

Some businesses have attempted to improve upon manual invoice processing using template-based optical character recognition invoice programs. Optical character recognition (OCR) is a type of software that can automatically detect and capture data within scanned images of business documents.

OCR works using invoice segmentation, in which the image of an invoice is divided into just the regions containing data. These systems have created more efficiencies but have also introduced their own flaws, which can be difficult to manage — since OCR templates only work for perfectly-structured data.

Compared to traditional OCR, cognitive OCR uses machine learning technology to extract the invoice dataset with more speed and accuracy than any system before.

Invoice data extraction software

Invoice data extraction software was first developed as a way to address the inefficiencies and other problems associated with manual data entry. With OCR invoice to Excel technology, the data within invoices could be scanned, extracted, and then easily sent to an Excel spreadsheet for use later on. OCR addresses a fundamental problem with how business data is currently stored. 

Research has shown that 80% of all business data is embedded in unstructured formats such as business documents, emails, images, and PDF documents. Unstructured data cannot be used or understood by computers or applications. 

As a result, manual data entry is still commonly used for semi-structured and unstructured documents. Until recently, it has been only possible for humans to take unstructured data, and convert it into structured formats. 

Traditional OCR relies on structured data, meaning it can only automate about 50% of the tasks associated with data entry. Template-based OCR requires expensive experts to spend hours creating new rules and templates for every single variation of every new format — and some will ultimately still need to be processed manually. 

In contrast, cognitive OCR software can extract invoice data from semi-structured and even unstructured files quickly and efficiently. If you want to know how to convert PDF to Excel without losing formatting, look no further than an effective AI-enabled OCR platform. 

Moreover, intelligent OCR invoice processing can operate with unparalleled accuracy. Thanks to machine learning, OCR can automatically detect new variations of documents and automate up to 90% of document processing tasks. 

This means that hundreds of invoices can be processed rapidly and accurately, leaving your AP team more time to focus on the strategic initiatives that matter to growing your organization. 

OCR in invoice processing

The purpose of AI-enabled OCR platforms is to reduce the paperwork burden on accounts payable teams, and to enable complete OCR automation opportunities. The best OCR invoice processing programs can extract data from hundreds of invoices, and export that data to your accounting system — in minutes. 

OCR in invoice processing usually requires you create an account with a processing service, then log into the platform (if it’s online). Next, you decide what kinds of data fields you want the system to export from the invoices. 

Rossum makes data extraction easy by allowing you to simply check and uncheck the boxes to decide which fields to extract. After that, you’ll load your invoices — whether it’s one, or hundreds — into the queue. 

Businesses often choose to upload invoices into an OCR system in PDF or image formats. As soon as the documents are uploaded, the data is captured. This whole process often takes less than one minute to complete even if you’ve uploaded hundreds of invoices. 

Finally, intelligent OCR software provides an easy-to-use validation interface to validate the data, before extracting it and sending it to its destination. 

Extracting structured data from invoices can be easy when you use the right kind of OCR platform. However, to fully automate the invoice processing workflow, your OCR platform needs to be connected to your accounting system. 

With integration, invoice data can be seamlessly transferred. In order to design such a software bridge, it’s important to find an effective invoice OCR API. 

Invoice OCR API

Once the data has been extracted and captured from an invoice, there are three options for how you can get the data over to your accounting system. The first option is to process it manually. In this method, you can export data from an invoice into a structured format like Excel. Then, you simply manually upload this data into your accounting or ERP system. 

The second option is to use an invoice OCR API. API (short for Application Programming Interface) allows your own software engineers to build a custom integration between your OCR engine and your accounting or ERP system. 

Rossum’s API, for example, makes it easy to build an invoice OCR Python integration for any kind of accounting software. The best OCR API is straightforward, allowing you to easily set up the integration in a matter of hours. 

The third way to connect your OCR platform to your accounting system is to use robotic integration. This is the easiest way to integrate, but it only works if your preferred OCR platform is compatible with a robotic process automation (RPA) platform. The goal of an API should be to provide flexibility to customers so that they can build the solutions they need.

Invoice OCR software

Online OCR software has another huge advantage over traditional manual data entry workflows — it is secure, and easy to monitor for errors. Because intelligent OCR is based in the cloud, online OCR software can give you 24/7 visibility into all your document-based processes. This means you can easily check from a smartphone any invoice that your team may have questions about. 

If you’re not sure your business is ready for automated invoice processing, there are basic invoice management solutions available online. A quick search for “invoice OCR GitHub” will bring up a variety of different programs that use OCR technology on invoices. 

Web-based options include free open source solutions, like Tesseract. Tesseract is an OCR engine that you can use with Python and other programming languages to build your own OCR program for invoices.

However, you will need to find a method or software to connect an interface to it if you want a user-friendly service with a wide range of functions. Open source options like Tesseract are limited in their functionality. 

Basic OCR invoice programs often encounter challenges when faced with new fonts and formats. Often, it’s better to go with an enterprise solution that has already been trusted — and is easy for non-techies to use.  

Best OCR for invoice processing

The best OCR online platform does more than just capture data — it can be fully integrated into your accounting or ERP systems.

Truly taking control of your invoice processing requires more than just template-based OCR. Although OCR is an important element of intelligent document processing, Intelligent Document Processing (IDP) is an AI-based approach with no templates necessary. 

IDP streamlines your entire document workflow, allowing you to import, process, validate, and post-process a large number of documents quickly. 

The best OCR for invoice processing goes beyond just scanning documents for characters. Intelligent OCR enables you to fully automate a variety of business processes. In any OCR invoice solution, user friendliness is key — there is little value in a program that is too complex for your team to easily use. 

Rossum is an invoice classification machine learning program that uses OCR as part of a complete IDP platform. Rossum was built with uniquely powerful AI capabilities to rapidly and accurately extract data from a huge variety of documents, including invoices. With Rossum, you can build an accounts payable team that’s paperless and efficient — and transform AP into a profit generator.