How we helped a leading BFSI corporation improve process efficiency by 60% using AI-based OCR.

By September 26, 2019 May 4th, 2020 AWS, Case Study

Written by Vinit Balani, Associate product manager at Powerupcloud Technologies

 

Demonetization has changed the way the Indian banking sector functions. While the wider acceptance of Aadhaar has made documentation and authentication easier, for BFSI clients mainly the insurance companies, document verification is still required for processing of loans and policies. Most of this process still remains manual, adding to the time required for opening an account or processing the claims.

One of India’s largest insurance companies was facing this challenge and wanted to resolve this problem. In this case study, we highlight the problem statement and take you through how Powerupcloud came up with the solution using AI automation.

 

Problem Statement:

With a customer base of 115 million users and expanding, one of India’s largest private Insurance companies wanted a resolve the problem where field agents were dealing with a large quantum of information including images captured as a part of a KYC process.

The company already had an android application for these agents to capture photos of documents, while an account was being created. However, once these photos were captured the data had to be manually entered into the customer repository.

Another challenge was the bad quality of document photographs being taken by the agents, which often resulted in them going back to the customer to re-capture the photos. This was ultimately also increased lead-time for account opening.

The company was looking to automate this process using an OCR (Optical Character Recognition) solution, which could help approve or reject the photo based on quality at the point of capture itself.

 

Proposed Solution:

Powerup proposed creating a native android application to be integrated within the company’s primary application by leveraging AWS Rekognition’s OCR technology. In addition an application with features to improve the image and do a quality check using open source technologies.

The current scope included developing an OCR mechanism for only the Aadhaar Card. With its successful implementation, it is now going to be extended to other KYC documents.

 

Solution Flow:

 

 

Solution Details

The app (OCR) developed by Powerup is a native android app integrated within the company’s existing android app. The OCR app gets triggered when the Aadhaar document has to be captured by the field agent.

Once the image is captured, it allows the user to crop and enhance the image using features like brightness, contrast, saturation, etc. Post this, the image quality check is done for brightness, contrast, and blurriness. If the image fails the quality check, the agent is asked to re-capture it. However, if it passes the test, the Aadhaar image is scanned to check for QR code and extract information from it. If the scan succeeds, the output with parameter values (like Aadhaar number, Name, Gender, Address) is sent to the company’s application. However, if the QR scan is not successful, the text/parameters are extracted from the image using AWS Rekognition’s OCR technology.

The extracted parameters are then passed on to the company’s Android application as JSON. Below are some snapshots of the native OCR app –

 

 

 

Cloud platform

AWS.

Technologies/Features/Services used

AWS Rekognition, Python.

Benefit

The application is now live and being used by 6000+ field agents across India. There has led to a 60% reduction in the lead-time for processing an application. In addition, the solution has also helped improve the productivity of the field agents who can now cover a lot more customers.

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