Customer Success Story

BUSINESS INTELLIGENCE AND AUTOMATION IN
INDIA’S LARGEST PRIVATE SECTOR BANK

Client Background

One of the leading private sector banks having a nation-wide network of over 2,000 branches in India. It is the sixth largest bank in India by assets and the first largest bank by market capitalization as of 2020. It has been ranked amongst Top 1000 Banks by The Banker Magazine and among Fab 50 Companies for 5 years in a row, by Forbes Asia.

Business Challenges

The client is one amongst the few nationalized banks, empaneled by Central Government, for one of the prestigious loan scheme, being extended to a particular strata, which falls ‘below poverty line’. The complexities were enormous as end-users could fill on-line applications and upload supporting documents, from anywhere.

Application processing would be required to undergo multiple stages of re-work in case of spelling errors in specific critical fields and / or challenges in extracting information from various file formats. The scenario became further complicated as post processing, applicant details had to be uploaded in a specific file format. This format was on most occasions, different from the format(s) in which applicant documents had been originally received.

Solution Strategy & Deployment

The bank evaluated the vast suite of products offered by eDAS, with capabilities to work in “Seamless Integrated” manner. The focus was on maximizing Automation, Business Intelligence and RPA tools, as possible.

Some of these areas identified across the value-chain, where eDAS could bring in value- addition, included:

  • Need for deploying an RPA-based tool to overcome the challenges of spelling errors. Often branch details if keyed wrongly would hinder further processing. Here the bank’s Unique Branch ID would have to be mapped with the one provided by applicant.
  • RPA-based tool had to be deployed. This could help overcome the challenges faced on various fronts like making data available in editable format from different file formats, as well as uploading data post quality check against respective ‘Unique Loan ID’, etc.

eDAS subsequently extended “Business Intelligence & Automation” services, with the following capabilities:

  • “eDAS RPA-based tool”: This was best suited for an environ ment that have chances of frequent errors and requires regular inputs.
  • “eDAS RPA-based tool” was able to extract data in an edit able format, from format-agnostic documents (like .pdf, jpg etc.) through its inherent capabilities of “Intelligent Doc ment Processing”.
  • eDAS RPA-based tool was strengthened to perform upload of processed applications. This was done through a web-link upload such that respective loan application details would get populated against the respective ‘Unique Loan IDs”
  • Overall processing was further strengthened through inclu sion of ‘SMS’ triggering and ‘WhatsApp’ at appropriate stage of processing. This significantly helped in scenario-based for warding of “Loan Applications”

Benefits for the Client

  • Deployment of “eDAS RPA-based tool” resulted in creating benchmark TAT of an application being processed in less than 2 hours
  • The solution resulted in bringing about 57% cost reduction for the client. Italso created opportunity for re-skilling talent pool to concentrate on judge ment-based roles, critical thinking and problem-solving situations.
  • eDAS has now been entrusted with the responsibility of working as a “Consultant” to the client, for evaluating other LOBs of the Bank, where this solution could be de ployed and similar success story could be replicated.

AT A GLANCE

Business Challenges

  • Processing applications from multiple sources
  • Need to upload applications in specific format
  • Different formats of files in pre-processing and post-processing stages

Solution Strategy & Deployment

  • Deployed RPA-based tool
  • Extended Business Intelligence & Automation services
  • Included SMS and WhatsApp triggering

Benefits for the Client

  • Application based in less than 2 hours
  • Reduced client costs by 57%

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