An Optical Character Recognition (OCR) can detect and extract text from images. For example, if you scan a form or a receipt, your computer saves the scan as an image file. You cannot use a text editor to edit, search, or count the words in the image file. However, you can use OCR to convert the image into a text document with its contents stored as text data.
Content Overview
Why is OCR important?
Most business workflows involve receiving information from print media. Paper forms, invoices, scanned legal documents, and printed contracts are all part of business processes. These large volumes of paperwork take a lot of time and space to store and manage. Though paperless document management is the way to go, scanning the document into an image creates challenges. The process requires manual intervention and can be tedious and slow.
Moreover, digitizing this document content creates image files with the text hidden within it. Text in images cannot be processed by word processing software in the same way as text documents. OCR technology solves the problem by converting text images into text data that can be analyzed by other business software. You can then use the data to conduct analytics, streamline operations, automate processes, and improve productivity.
Optical Character Recognition (OCR) Use Cases across Industries
The following are some common OCR use cases in various industries:
Banking
The banking industry uses OCR to process and verify paperwork for loan documents, deposit checks, and other financial transactions. This verification has improved fraud prevention and enhanced transaction security. For example, BlueVine is a financial technology company that provides financing to small and medium-sized businesses. It used Amazon Textract, a cloud-based OCR service, to develop a product for small businesses in the US to quickly access Paycheck Protection Program (PPP) loans as part of the COVID-19 relief stimulus package. Amazon Textract automatically processed and analyzed tens of thousands of PPP forms per day so that BlueVine could help several thousand businesses get funds, saving over 400,000 jobs in the process.
Healthcare
The healthcare industry uses OCR to process patient records, including treatments, tests, hospital records, and insurance payments. OCR helps to streamline workflow and reduce manual work at hospitals while keeping records up to date. For example, the nib Group provides health and medical insurance to over 1 million Australians and receives thousands of medical claims per day. Its customers can take photos of their medical invoice and submit them through the nib mobile app. Amazon Textract processes these images automatically so that the company can approve claims much faster.
Logistics
Logistics companies use OCR to track package labels, invoices, receipts, and other documents more efficiently. For example, the Foresight Group uses Amazon Textract to automate invoice processing in SAP. Manual entry of these business documents was time-consuming and error-prone because Foresight employees had to enter the data in multiple accounting systems. With Amazon Textract, Foresight software can read characters more accurately across many different layouts, which increases business efficiency.
Traveling
OCR technologies also make traveling an easy path for you by fast-tracking the passport checking and travel application for security and data storage purposes. Also, OCR helps in reducing manual errors in data verification and processing the data faster than humans. From booking the checking process to travel expense management, OCR technology can be leveraged for reimagining the travel industry and customer experience as well.
Government
Many government and legal industries still rely on the paper trail method to process information. From license registration to voting ID cards, OCR Technology can be used to streamline the workflow. Instead of manual verification, OCR technology can easily check the registered users’ information just by scanning the card and accessing information in a smooth process way.
Food Industry
Using machine learning algorithms with OCR features can help the food industry in creating a digitized menu, and a database of multiple recipes with calorie information and their apt intake amount. That’s how OCR feature not only give enhance the customer experience but also give the food industry an idea for creating more innovative process.
Retail
OCR feature can up-level the retail operations by offering retail industries to scan and extract the relevant information from bills of payment, packing lists, invoices, purchase order’s, and many other processes. In addition, OCR can create structured format data for easy data access and offer end-to-end data processing.