The ‘What’, ‘How’, ‘Why’, and ‘When’ of Intelligent Character Recognition
Due to the highly competitive market and increasing customer needs, online businesses are adopting intelligent solutions to streamline their operations. From remote customer onboarding to effective business services, Artificial Intelligence is setting up the pace. Traditional means of extracting data from customers’ identity documents have become outdated and error-prone. Today, enterprises are looking for improved solutions to extract user data more effectively. Intelligent Character Recognition adopts AI-powered techniques to reduce the false-positive rates and significantly improve the character recognition process of user documents during client enrollments.
In 1993, the discovery of automated processing of forms by Joseph Corcoran led to the development of ICR. The system consisted of a three-stage process that involved capturing an image of a paper-based form and preparing it for the ICR to process, feeding the information into the system, and processing and sharing the results to validate the output. This paved the way for solutions having intelligent character recognition which are now used for faster data retrieval and scanning documents with hard-to-read fonts and different languages.
ICR, a subdomain of Optical Character Recognition, incorporates machine learning algorithms to learn different fonts and handwriting styles to effectively extract relevant information including hand-printed characters, a wide range of symbols, and multilingual text. It is an extended version of OCR but more intelligent and improved in terms of acquiring and processing information. ICR takes into account any type of document it extracts to help improve its accuracy over time, eventually getting better.
How is it different?
When compared to conventional OCRs which generally focus on printed documents, ICR uses Intelligent Word Recognition (IWR) to better recognize handwritten text and work with digital documents as well. An OCR will normally fail if it is presented with a document containing complex fonts, and comes with a limited ability to perceive handwriting. On the other hand, ICR software uses Natural Language Processing and Deep Learning to read data on documents, point out relevant information and extract it for creating user verification or creating a digital PDF of the acquired information.
This does not mean ICR services are correct by all means since the neural network running behind needs data to train and learn different types, formats, and styles of handwriting and printed text. The data is stored in databases over time and used to train the model to help improve accuracy. Also, intelligent OCRs come with the support of reading multiple languages which in most cases is not a feature of traditional OCR engines.
How it Works
Usually, the ICR software is integrated into a system, application, or website to carry out its operations. The document uploaded by the user is canned and data is extracted just like a normal OCR system, but with better accuracy and understanding of the information present on the document. The process entails the following details:
Input and Extract Data
The user is prompted to display an identity document such as a government-issued ID card, a passport, or a driver’s license. The ICR engine scans the document and extracts useful details like the full name, last name, date of birth, address, and other relevant information.
In the next step, the user could be asked to show a handwritten consent on a piece of paper which the ICR reads and acknowledges as proof of identification.
Since the system is intelligent it will incorporate AI-based techniques to assess handwritten text or relatively difficult fonts. The information extracted previously, in the final step, is verified against a series of AI checks and the results are shared with the client.
ICRs are important because of their use cases in numerous fields. Below are listed some points which explain why ICRs are significant in today’s setting.
- ICRs can aid online businesses in automating the data extraction process during customer onboarding bringing down the verification time to minutes.
- Document verification can now be done remotely with better accuracy irrespective of where a user is present and what time zone they are in
- ICR can read handwritten consents that can be used for identification during a new account opening
- Workplace operations are streamlined with ICRs since manual and tedious tasks are now replaced with intelligent solutions.
To sum it up, Intelligent Character Recognition (ICR) services allow accurate data extraction from user documents, significantly improving the business operations and customer experience.