Pair OCR with Artificial Intelligence and Machine Learning.ĭata extraction using AI or machine learning is able to “understand” what information on a document or invoice needs to be used and, more importantly, what should be done with said information to make it relevant data. Even duplicating efforts in some respects. This might defeat the intent of transitioning to invoice and payment automation because you are not saving time, and it might even be more time-intensive. In this scenario, humans have to constantly manage the templates read them, interpret them, and update them. The retrieval process can be done fairly quickly, however, it can become an administrative burden as templates must be manually managed and updated as documents change. In a template-based data extraction software, a user has to build or predefine specifically “where” on a document a specific piece of information can be found and “what” the tool should do with the data it finds. Kind of defeats the purpose of moving from a manual AP process to an automated process to save time, right? In this scenario data entry is done by an outsourced firm and takes time as the data is being populated by people, typically 24 to 72 business hours. OCR extraction that layers human verification uses people to put data read by the OCR into predefined fields. Some AP automation software providers might use OCR, but then apply human extraction, outsourcing to a third party-also called third-party verification. OCR can scan the text on a pdf invoice or document but doesn’t know where to put that information. These are all necessary as OCR by itself does not know what to do with the information it reads from your documents. Systems based upon artificial intelligence (AI) or machine learning.Zonal-based extraction that utilizes predefined templates.Human verified or outsourced extraction.Today, there are three predominant types of extraction technology: But what you really want to know when investigating invoice and payment processing automation providers is if the software has a complete technology, combining OCR (converting images to text), smart data extraction (transforming the text into relevant data), and machine learning (remembering the data and populating it into the applicable data fields each time the data is recognized). As many of you are exploring AP automation software providers, you may ask, “Do you have OCR technology?” Good question. The next layer, smart data extraction, understands and processes the text from the OCR to transform or format it into relevant data. OCR is a technology that turns a picture into words. Simply put, it’s a computer looking at an image or document, such as a supplier invoice, and being able to identify what is on it.ĭon’t confuse OCR invoice scanning with data extraction. The text can come from a scanned document (like a vendor invoice), a photo of a document (like a receipt), a scene-photo (for example the text on signs and billboards in a landscape photo), or from subtitle text superimposed on an image (like from a television broadcast). The official definition of optical character recognition (OCR) is the mechanical or electronic conversion of images of typed, printed, or even handwritten text, into machine-encoded text. What is Optical Character Recognition (OCR)? But what is it? More importantly what isn’t it? How does it even work? And how does it make a difference in the AP workflow? In this blog, we’ll answer all your questions about OCR and it’s role in automating invoice processing. It’s of particular interest in FinTech (another new buzzword that stands for ‘financial technology’) and even more specifically in accounts payable. OCR: Another one of those technical buzzwords that we’re hearing a lot about these days in accounting and technology.
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