Use Cases of Advanced Character Recognition Technologies in Automating Document Transcriptions

Manual transcription of scanned documents into editable format is error-prone. This prompted the development and implementation of Character Recognition Technology, which accurately converts scanned documents into more manageable forms.

Intelligent Character Recognition (ICR) and Optical Character Recognition (OCR) are two important technologies that are widely used in banking and finance for digital document transcription.

This newsletter discusses ICR/OCR technologies, their applications, and how iStart assists banks and financial institutions in digitizing their manual and error-prone transcription process.

What is Optical Character Recognition?

OCR is a text recognition technology that electronically identifies and repurposes data from scanned documents, camera images, and image-only pdf files.

The technology combines hardware such as an optical scanner with software such as Artificial Intelligence (AI) to convert physical documents into machine-readable text.

What is Intelligent Character Recognition?

ICR is a more sophisticated form of optical character recognition. It employs artificial intelligence to learn different fonts and styles of handwriting and has a high level of accuracy in interpreting the text. Essentially, it is a more advanced and detailed application of character recognition.

According to an AIIM study, advanced OCR/ICR technology accounts for 49% of data capture volume, and organizations must convert them into digital systems to leverage data in digital documents.

OCR vs ICR - Banking & Finance Applications

OCR is an ideal solution for businesses that rely on hard copies. It can generate searchable and editable documents quickly and accurately using scanning and file compression technologies.

ICR, on the other hand, specializes in digitizing multiple handwritten notes and manuscripts. It improves organizational workflow by eliminating manual correction and searching through multiple pages.

Use Cases of OCR / ICR in Banking and Finance

iStart’s ICR/OCR Integration

iStart is a customer onboarding platform that provides RBI-approved V-CIP solutions to banks and NBFCs. It allows for immediate onboarding and ensures complete compliance with RBI guidelines.

The video-based customer identification process necessitates real-time verification of Official Valid Documents (OVDs). The platform employs advanced OCR/ICR technologies to verify OVDs such as Aadhaar, PAN, Voter ID, Passport, and driving license in real-time. Through signature matching, it makes it easier to detect fraud.

Character Recognition, in combination with Machine Learning (ML) technology, overcomes issues such as blurs, glares, and incorrect image capture. According to AI Multiple research, OCR/ICR improves data extraction accuracy by 50% with 98% field-level accuracy.

The process used by iStart's character recognition engine to extract useful data from the ID card is as follows:

1. Image cropping and alignment: It removes the background and aligns the ID image perfectly horizontally with 0°.
2. Raw text detection: It uses machine learning to detect text in cropped images.
3. Data extraction: It extracts meaningful data from images, such as separating two names in order to identify the customer's and father's names.

Key Takeaways

1. ICR and OCR are the two most common character recognition technologies.
2. OCR is a technology that extracts data from scanned documents, images, and pdfs.
3. ICR reads handwritten notes and manuscripts to extract data.
4. iStart's Video KYC platform uses OCR/ICR techs to speed up customer onboarding.
5. It increases the accuracy of data extraction while saving time and effort.