ICR vs OCR - Comparing the Use Cases of Character Recognition Tech for Banking & Finance

ICR vs OCR - Comparing the Use Cases of Character Recognition Tech for Digital Banking

Authored by: Mohammed Mansoor    Reading Time: 02 min 15 sec

Manual transcription of scanned documents into editable format is error-prone. This has led to the development of Character Recognition Technology that turns scanned documents into more manageable forms with high accuracy.
Intelligent Character Recognition (ICR) and Optical Character Recognition (OCR) are two significant technologies widely used in Banking and Finance for digital document transcriptions.
This blog explains the ICR/OCR technologies, their use cases, and how iStart can help banks and financial services to digitize their manual and error prone transcription process
ICR VS OCR for Banking and Finance
ICR VS OCR for Banking and Finance

What is Optical Character Recognition?

OCR is an advanced text recognition technology that electronically identifies and repurposes data from scanned documents, camera images, and image-only pdf.
The tech combines hardware such as an optical scanner and software such as Artificial Intelligence (AI) to convert physical documents into machine-readable text.

What is Intelligent Character Recognition?

ICR is an advanced form of Optical Character Recognition. It uses AI to learn different fonts and styles of handwriting and has high accuracy to interpret the text. Essentially, it is a more intelligent application of character recognition that is more involved and detailed.

According to a study by AIIM, advanced OCR/ICR technology, 49% of data capture volume is paper, and organizations need to convert them into digital systems to leverage data in digital documents.

OCR vs ICR - Use Cases in Banking & Finance

OCR is a perfect solution for organizations that revolve around hard copies. It can quickly and accurately generate searchable and editable documents through scanning and file compression technologies.
On the other hand, ICR specializes in converting multiple handwritten notes and manuscripts into digital characters. It speeds up the workflow within the organization and eliminates manual correction and search through multiple pages.
It enables simple and remote onboarding by extracting key information such as date of birth, signature, and name from uploaded customer documents.
It is used to read information from loan applications, checks, forms, and surveys since Banks and NBFCs can digitally process them.
It eliminates data entry errors in banking and enables institutions to retain workflow efficiency with excellent text recognition accuracy.
Insurance companies use ICR to digitize customer documents, as required by law.
It expedites the processing of loan and mortgage applications, which require the verification of a large number of documents.
It provides comprehensive data verification and eliminates manual data entry time. This increases employee productivity and efficiency.

iStart’s ICR/OCR Integration

iStart is a customer onboarding platform that offers RBI-approved V-CIP solutions for Banks and NBFCs. It enables instant onboarding and ensures full compliance with RBI guidelines.
The video-based customer identification process requires real-time verification of Official Valid Documents (OVDs). The platform uses advanced OCR/ICR technologies to instantly verify OVDs like Aadhaar, PAN, Voter ID, Passport, and driving license. It makes it easier to detect frauds through signature matching.
Character Recognition, coupled with Machine Learning (ML) technology, overcomes the issues like blurs, glares, and incorrect image capture. According to AI Multiple research, OCR/ICR improves 50% accuracy in data extraction with 98% field-level accuracy.
iStart’s character recognition engine extracts meaningful information from the ID card via the following process:
  1. Image cropping and alignment: It removes background and perfectly aligns the ID image horizontally with 0°.  
  2. Raw text detection: It detects text from cropped images with the help of machine learning.  
  3. Data extraction: It extracts meaningful data from the image, such as differentiating two names to identify the customer and father’s name.  

Key Takeaways

1. ICR and OCR are the two major character recognition technologies widely used.

2. OCR extracts data from scanned documents, images, and pdfs.

3. ICR extracts data from handwritten notes and manuscripts.

4. iStart’s Video KYC platform uses ICR/OCR to expedite customer onboarding.

5. It improves data extraction accuracy and saves time and effort.

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