OCR technology eliminates the need to hire employees for manual data entry and speeds up data processing workflows by automating information retrieval and input into systems. The global OCR industry was valued at USD 7.48 billion in 2020 and is expected to grow at an annual CAGR rate of 16.7% from 2021 to 2028. From logistics, real estate, BFSI, manufacturing, education, retail, and healthcare, these solutions are increasingly being used by both large-scale and smaller corporations to make document management and processing seamless.
Below we answer a list of common OCR FAQs for those who want to know more about this technology:-
OCR stands for Optical Character Recognition.
It is the technology used for scanning numbers, letters, shapes, and images from all sorts of documents. It is capable of reading special characters, symbols, and paragraphs from PDFs, spreadsheets, and various electronic files as well.
OCR’s history traces back to the 1920s when physicist Emanuel Goldberg created a machine that became capable of reading characters and converting them into telegraphic codes. The evolution of modern OCR took place after the 19th century when neural networks and the field of Natural Language Processing (NLP) made advancements in technological innovations.
The definition of OCR scanning is to recognize and read information from physical documents, scan it, and process the data into electronic formats. The meaning of ‘scanning,’ is to retrieve information from documents and process it in file management systems.
OCR programs store information as editable text or as documents on computers. For example, if you scan a piece of paper, OCR technology will enable you to extract data from this scanned image. This process involves converting the characters from these images into a machine-readable format.
OCR software programs let computers recognize text from physical documents, clean it up, and make it easier to interpret. OCR algorithm preprocess images from these documents and prepare them for reading in order for better chances of recognition. Common OCR scanning techniques include character isolation, aspect ratio scaling and normalization, de-skewing documents, and converting images to black and white photos for distinguishing text..
Zonal OCR is a subset of OCR technology which lets users scan specific “zones” or regions of documents and ignore the rest. This is useful for identifying the key-value pairs and line-items in a document, and save it instead of processing entire documents.
OCR technology is used by different industry verticals for the purpose of scanning, storing, processing, and sharing documents. Banks do data capture and extraction using OCR algorithms to archive client-related paperwork and make digital content more accessible. Signature recognition and validation using OCR is used for detecting fraud in documents and identifying cases of forgery for processing loan applications.
The logistics industry deals with huge volumes of data and requires authorities to identify inaccuracies in documentation. OCR solutions make it easy to automate process workflows, capture and validate information, and forward alerts as EDIs to stakeholders. The logistics industry is going paperless and OCR software lets employees save time and make remote work possible by removing the need for their physical presence when it comes to submitting relevant documentation.
Real estate industry uses OCR to get faster and accurate data analysis for verifying properties. Robotic Process Automation technology embedded with modern OCR solutions helps companies save the total cost of ownership and process more than 50 million documents a year, thus drastically increasing efficiency and generating savings in sales due to genuine paperwork. Commercial real estate deals automate the underwriting process and extract data from rent rolls for faster processing using modern OCR solutions.
OCR is used by insurance companies for filing claims, performing customer profile analysis, and automating data capture to save time and reduce errors associated with manual data entry. It can take over a 100 employees to process 10,000 documents a month but OCR in insurance can finish document processing in a matter of days!
Automated data extraction via OCR helps businesses in cutting costs and being more efficient in document processing. OCR offers users the following benefits over manual data entry:
OCR technology is generally accepted to be 98% to 99% accurate when it comes to reading and interpreting information correctly from documents. This means that for a 1,000-page document, up to 980 or 990 characters are accurately read by the software and recorded electronically.
Reliable OCR solutions like Docsumo don’t just have 99% page accuracy but a high level of field-accuracy as well. High field-level accuracy scores let users achieve true automation when it comes to intelligent data entry and these programs require minimal manual review after data is entered by software algorithms.
OCR APIs are designed to transcribe text from handwritten documents for interpretation by machines. Popular use cases of OCR APIs include banking, finance, legal sectors, educational institutions, and the real estate industry. For legal documents, you can use OCR APIs to transcribe documents such as affidavits, judgments, filings, etc.
OCR APIs are used for automatically processing invoices, receipts, bill of laden, and extract information from tax records. There are APIs dedicated to scanning KYC documents, survey forms, and classifying text from a variety of documents.
The most popular OCR APIs in the industry are:
OCR is used for extracting text data from images and classifying it using intelligent analysis. However, even OCR has a set number of limitations which are as follows:
OCR and ICR each have their own use-cases when it comes to document processing and scanning. The key difference between the two is the way data is read from paper-based documents. OCR is best used for scanning text-based documents and converting them into digital files. There is no need to manually retype data when you use OCR software and it is considered to be a very cost-effective solution for businesses.
ICR, on the other hand, is ideal for reading handwritten fonts and different styles of cursive text. It can recognize and convert multiple styles of handwriting effectively and is powered by intelligent neural networks which are capable of automatically updating databases.
Although it is more expensive than OCR, it can save countless hours of time since it virtually reads any font and prevents human input errors associated with handwritten data entry.
If you’re new to the world of OCR and want to give a test drive, the best way to get started is by using the Docsumo free online OCR scanner. If you have a few document samples ready, you can upload your PDFs and image files to extract data automatically. You don’t need to install the software in your system. It’s completely free to use and there are no usage limitations.
Another free OCR tool we recommend to see the technology in action is the Docsumo OCR Chrome Extension. You can use it to scan text from websites, blogs, news articles, forums, and a variety of online portals. The data read can be translated into different languages like Spanish, Portuguese, German, etc. as well at no additional cost. Docsumo’s OCR Chrome Extension is also capable of reading text from visuals, graphical elements, video thumbnails, and a variety of images online.
Docsumo uses proprietary machine learning algorithms and AI technology for automating data capture in businesses and enterprises. Besides enjoying complete data privacy and legal compliance, you can use our intelligent OCR tools to automate document processing and improve productivity at work.
To get a first-hand experience of how intelligent OCR can benefit your business, sign up for a free demo with Docsumo and experience the difference today!
In today’s dynamic business world, filing and archiving official documents in the digital form makes it handy, and works wonders in the future or in unforeseen circumstances.
With an automated data extraction solution, loan documents can automatically be processed end-to-end without any human errors and delays. Automation in loan document processing prevents downtimes, eliminates data redundancy, and allows companies to respond faster to client queries. By combining machine learning with deep learning and OCR, companies can eliminate huge costs, derive actionable insights, and streamline loan processing and approvals through efficient data extraction and analysis.
Mortgage lenders receive multiple identity and income verification documents along with different forms from loan applicants in a variety of formats and styles. Traditional OCR solutions fail to extract data from these semi-structured documents and that’s why more and more lenders are adopting intelligent document processing solutions. IDP solutions not only extract data correctly, they are able to validate extracted data against predefined rules in order to improve accuracy.
Intelligent Document Processing is an automation technology that captures information from a myriad of documents and data sources, extract data, and organizes it for further processing. IDP solutions enable businesses to seamlessly integrate with core processes, eliminate manual labour, address challenges faced in reading different document layouts, and meeting legal & compliance requirements. Accurate data is the foundation of every organization, and IDP assists businesses in dealing with the complexity of processing huge volumes of documents, helping them automate manual data entry processes, and move away from traditional semi-automated OCR workflows.