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A leading U.S. bank had multiple templates and methodologies to assess loans which was impacting its ability to service higher volumes
The bank leveraged WNS’ analytics and automation expertise to establish systematic credit appraisal operations
The transformation enabled the bank to reduce bad loans and improve its credit score
This is our story of co-creating a solution with a leading U.S. bank
As we know…
When borrowers default on their loans, banks
lose not only the principal sum and interest,
it has an adverse effect on the cash flow as well.
Higher number of defaults or delinquent loans
lead to low credit scores. It’s also a major barrier
to revenue growth and brings banks under
The challenge for the bank was…
It had numerous templates, methodologies and
manual interventions to assess loan proposals.
This led to multiple handoffs of loan
applications and eventually impacted the
bank’s ability to service higher volumes of loans.
There was also significant backlog in loan
processing from a credit analysis perspective.
The absence of a strong centralized governance
and reporting structure coupled with
inconsistent internal timelines added to the
bank’s lending problems. These factors
hampered the bank’s growth plans as well.
The bank leveraged WNS’ analytics expertise to
reduce bad loans, and establish systematic and
automated credit appraisal operations. The goal was to have a centralized governance structure
to comply with regulatory norms.
Here’s what we co-created as a solution…
WNS conducted an in-depth assessment to
identify gaps in the existing credit appraisal
operations. This comprised accumulation of
relatively high-risk proposals, certain deviations
from guidelines and multiple handoffs. Analysis
was done on parameters such as interest
coverage ratio and debt serviceability.
The Probability of Default (PD), Loss Given
Default (LGD) and Exposure at Default (EAD)
were also analyzed.
A Center of Excellence (CoE) model was
deployed to set up criteria-based standard
operating procedures, centralized practices,
metrics and rating methodologies. All the
metrics were closely monitored to provide a
comprehensive report. Automation was
introduced to reduce errors in the loan review
process. Fragmented processes were
integrated. Flexibility was embedded into the
credit appraisal operations to minimize
bottlenecks in the loan review process.
Our learnings and outcomes from the process of co-creation are...
That the CoE helped improve regulatory
compliance. WNS enabled the client to put
in place a rigorous credit analytics and risk
grading mechanism. As a result, there was
tighter scrutiny of lending procedures, which
eventually brought down bad and delinquent loans. This also helped reduce backlogs and
aided revenue growth. The CoE enabled faster
closure of reviews and improved the bank’s
Other benefits included:
Significant reduction in bad / delinquent loan
provisions; credit decision cycle time was
brought down from 10-12 days to 5 days
which led to 6-8 percent increase in loan
Over 99 percent accuracy levels due
Over 50 percent cost benefits due to the
deployment of cross-trained resources