OCR: Another one of those technical buzzwords that we’re hearing a lot about these days. It’s of particular interest in FinTech (another new buzzword that stands for ‘financial technology’) and even more specifically in accounts payable. 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 first of a two-part blog, we’ll use clues to solve the mystery of OCR.
OCR stands for optical character recognition. The official definition is the mechanical or electronic conversion of images of typed, printed, or even handwritten text, into machine-encoded text. The text can come from a scanned document, a photo of a document, 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).
First Clue: It looks like this1:
Simply put, it’s a computer looking at an image or file and being able to identify what is on it.
Second Clue: Don’t confuse OCR with data extraction.
OCR is a technology that turns a picture into words. The next layer, smart data extraction, understands and processes the text from the OCR to transform it into relevant data. As many of you are exploring AP automation providers, you may ask, “Do you have OCR technology?” Good question. But what you really want to know is if the solution has a complete technology, combining OCR, smart data extraction, and machine learning. Today, there are three predominant types of extraction technology:
- Human verified or outsourced extraction
- Zonal-based extraction that utilizes predefined templates
- Systems based upon artificial intelligence (A.I.) or machine learning.
Third Clue: These are all necessary as OCR by itself does not know what to do with the information it reads. Some providers might use OCR, but then apply human extraction, outsourcing to a third party—also called third-party verification. OCR extraction that layers human verification uses people to put data read by the OCR into predefined fields. 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. Kind of defeats the purpose of moving from a manual AP process to an automated process to save time, right?
In Part 2 of this blog series, we’ll uncover more clues to solving the mystery of OCR.
1Hewlett Packard Enterprise Development LP. 2018. Retrieved June 29, 2018 from https://dev.havenondemand.com/apis/ocrdocument#overview