OCR, short for Optical Character Recognition, is a technology that found its place in accounting companies. OCR tools assist accounting teams in processing thousands of documents such as invoices and receipts. In this article, we delve into the OCR technology meaning, the benefits of OCR application in Accounts Payable, and the particular examples of using OCR in Accounting.
Some technologies have quietly found their place in our lives, to the point when we no longer realize they’re there.
That’s the reality with OCR tools.
Whether it’s scanning barcodes, an image search function in Google, or converting files from PDF to .txt online, we are supported by OCR tools.
But did you know that the concept OCR appeared already in the 19th century?
Of course, it wasn’t the OCR that everyone is familiar with today.
A brief history of pre-OCR innovations
The roots of OCR technologies – the earliest precursors so to say – can be traced back to the innovations developed in the second half of the 19th century. In the beginning OCRs used technologies related to telegraphy and the creation of reading devices for the blind. One of such aids was Tauschek’s Reading Machine.
In 1914, Emanuel Goldberg developed a machine that read characters and converted them into a standard telegraph code. Around the same time, Edmund Fournier d’Albe created the Optophone -a hand-held scanner that produced tones corresponding to specific letters or characters – an optophone. The scanner translated text from ordinary books and newspapers into sounds, so if the user learned the sound alphabet, he could read a book, even one letter at a time.
In the 1930s, Emanuel Goldberg developed the “Statistical Machine”, used to search microfilm archives. It was the first electronic system for retrieving documents.
Then in 1974, Ray Kurzweil continued to develop OCR technology. Kurzweil returned to the medical application in the 19th century, but his invention brought around a significant milestone. A computer was designed to read text aloud to blind people.
Finally, we’re moving to a more recent – and a more relatable part of this story. In the 1980s, OCR technology became an integral part of barcode scanners in retail stores and photocopiers in offices and schools.
As of the beginning of the 2000s, OCRs started to appear in many forms – available online, in mobile applications, or as the more advanced ones sold as proprietary products.
Over the past few years, OCRs have become increasingly sophisticated.
There is still the familiar rule-based legacy OCRs, which have certain limitations. However, modern OCRs based on innovative technologies such as machine learning and artificial intelligence are also emerging.
We’ll cover this in the next section.
The modern OCR
As you can see, OCR has evolved. From the earliest versions of the technology created for the blind to today’s cutting-edge and reliable AI-based OCRs, which are becoming a staple for many companies.
And it’s this most advanced OCR that we’ll focus on later in our article, where we’ll show how crucial it is for today’s business.
But before we dive into the business impact of OCR, let’s start with the basics.
Modern OCR is a business technology for scanning documents and converting visual objects into editable text. More advanced software would further process documents to extract data and create links between the various docs.
Imagine that this is the invoice you would like to process automatically.
And then go through the simple 4 steps.
1. Upload the file
Select invoice in any form.
Digital or paper-based? PDF, PNG, or XLSX? It doesn’t matter.
Since AI-based OCR is flexible and not rule-based, it can handle any document – regardless of its format, structure, or arrangement of elements.
With Alphamoon – a platform for Intelligent Document Processing with an AI-based OCR feature – you can upload a single document or an entire set of them.
2. Preprocess document
Preprocessing is designed to make it as easy as possible for the OCR tool to distinguish characters. This step increases the chance of recognition and utilizes a combination of techniques.
When your file doesn’t have the right DPI, that is, too few or too many image dots per inch, the OCR software needs to scale it.
When the contrast is inadequate, the tool increases it. When the image is skewed, skew correction is necessary.
Sometimes, the OCR software also performs image binarization – that is converting a color image to a black and white format. This step helps the engine understand the data well.
Images are not always clear and free of noise either. Therefore, if a certain image has noise in the background or foreground, the OCR tool removes it to extract the data and not reduce its quality.
3. Let your OCR work
After preprocessing is complete – meaning the files are ready for scanning – the tool analyzes the image and begins to translate it into editable text. While that may sound like a long process, worry not – it’s all done in a split second.
4. Get the extracted data in a structured form
The OCR-processed data is delivered to the user in the form of text.
The unstructured data is converted to structured data – data that is ordered according to a pattern and readily available to humans and programs for later use.
Documents turned into structured data are an added value for any company and team. Working on automatically prepared data is easier than relying on the hundreds of documents needed to be manually reviewed and processed. And this is what AI-based OCR being implemented in many industries provides.
Specific application of OCR software in accounting
Accounting is one of those industries where OCR finds great application.
Preparing ledgers, creating balance sheets of losses and profits, and entering transfers for invoices and salaries into the system – are only part of the work of accountants. These are activities in which there are many repetitive elements and patterns.
On top of that, one common part is found here.
All the work of accountants is based precisely on documents. Invoices, receipts, cash memos, cheques – this is the daily routine of accountants, who encounter hundreds of documents daily.
Accounting and financial documents usually share similarities in terms of their visual layout, so typical legacy OCRs can handle most documents in the accounting industry. However, not all of them.
That’s where AI-based OCR tools, such as Alphamoon, come in handy. Instead of doing the basic processing, Alphamoon provides a comprehensive service, enhanced by AI and Machine Learning. Alphamoon’s engine enables the capture of any type of data from handwriting, tables, or images. It also learns over time and provides higher data extraction accuracy than traditional vendors.
As a consequence, document automation of financial and accounting data brings significant benefits to the company and its employees.
Traditional OCR tools vs. AI OCR
To validate the competitive advantage that AI OCR provides over legacy OCR software, we conducted a study on a set of publicly available sets of invoices and receipts.
We took the most well-known OCR vendors like Microsoft, Google, Abbyy, Kofax, and Alphamoon under the microscope and tested how they handle extracting data from invoices and receipts.
OCRs were supposed to process the documents and extract from the data such as company name, VAT number, price, and many others that the user specifies. The image below shows how it works in practice.
In the end, receipt and invoice AI OCR proved that it is definitely suitable for processing accounting documents. Furthermore, it achieves high results that translate into increased efficiency for accounting teams.
Want to read the full experiment analysis?
Benefits of OCR automation for Accounts Payable
Now, let’s cover the benefits of using AI OCR software for invoices and other documents.
By implementing the OCR tech, the work of accounting teams can be made easier and more efficient.
A few things are at play here:
Fewer errors in OCR invoice processing
When humans process invoices manually, reviewing them, searching for and extracting data, there is a high probability of simple human error. Additionally, one error pulls in a string of subsequent actions – checking for the error and re-entering the data or fixing the error. When technology comes into play that replaces humans – the risk of errors is reduced.
Capturing all types of information
OCR processes thousands of documents. Starting with receipts and invoices, AI-based OCR has tremendous capabilities in deciphering a multitude of documents – not just the most standard ones. Some OCRs like Alphamoon will decipher tables or handwriting, making even more automation possible.
Saving the environment
You no longer need to receive physical documents or make scans that consume paper and electricity – just keep them in a digitized form.
Intelligent document processing
OCR is based on artificial intelligence. It not only searches and extracts information, but can handle unknown documents, and classify them by type, for example. Additionally, with the support of other technologies, it enables full automation of accounting.
Reduced processing time
OCR allows to process commitments and payments faster and helps accountants by performing repetitive tasks. This saves a lot of time that can be spent on other creative activities and keeps employees motivated.
OCR makes it easier to control expenses and eliminate costs associated with document storage and processing. This affects the operating costs of the entire enterprise.
OCR processes documents in any format and can convert them to any format.
How Alphamoon OCR Supports Accounting Teams
We’ve established that automation of document processing perfectly fits accounting teams and their challenges. Now, it’s time to choose the right software.
Alphamoon’s platform for Intelligent Document Processing works seamlessly like your team’s virtual assistant. Our tool can classify documents, scan them with the AI-based OCR feature, extract data and store it securely, and further support integration with your ERP system.
Moreover, it beats leading companies like Microsoft, Google, Abbyy, and Kofax, delivering 98% accuracy in extracting data from invoices and 89.5% for receipts.
Shifting to AI OCR – whether it’s an upgrade from traditional OCR or an entirely new chapter in your company’s history – will help you establish better processes related to documents.