Automation helpsbank cut manual fraud
processing by 90%
An automation initiative builds in the capacity
to process 30+ million transactions a year,saving a leading bank $20M annually.

The challenge
Our client is one of the largest banks in the world, offering
services such wealth management, mortgage banking
and card services. It is one of the top credit card issuers inthe US and processes a large number of US-based
e-commerce transactions.
After trying to scale its automation initiative with two previous
vendors, our banking client turned to Cognizant. Despite initialsetbacks, the company was committed to automating its timesensitive processes so the firm could offer a high added value
to clients, while performing the important work of detecting
fraudulent charges, among other processes. The bank wasmonitoring over tens of thousands credit and debit card
posting transactions a day, and all the transactions needed tobe screened for incidents of fraud.
Fine-tuning fraud detection processes is important to any
financial institution. If the process is too sensitive, issues canarise when payments are rejected on non-fraudulent postings
and a customer’s access to their card is paused unnecessarily
as the incident is investigated. Or, if detection is not sensitive
enough, the bank is at risk of paying fraudulent charges toprotect its customer, which hurts the bottom line.

At a glance
A major bank engaged Cognizant toautomate processes that accesseda very high volume of sensitive data
across 25+ applications including
web, Windows, mainframe, Pega
BPM software and other thirdparty products. The firm needed,an enterprise automation strategy,
a more detailed roadmap forautomation projects, as well as
skilled resources to help execute.
Cognizant worked collaboratively
with client teams to deliver several
impactful business outcomes:• R educed current Average HandlingTime (AHT) by 20%• R educed exceptions from
100% to 8-10%• R epurposed 425+ FTEs across theUS, India and Manila saving $20M
annually in staff/direct costs andinfrastructure/indirect costs• Improved ROI for fraud anddispute-related processes,delivering $8.10 per every
dollar spent• E nabled capacity to process 30
million transactions annually

There were also issues managing criticalcompliance data for regulations such as
Automated Clearing House, the primary systemthat regulatory agencies use for electronic funds
transfer (EFT); and the US Service Members
Civil Relief Act, which protects the financial andlegal affairs of individuals on active duty military
service. Our client wanted to ensure its regulatory
data was managed properly to prevent incurringcosts and penalties if processes were notexecuted on time and according to mandates.
Additional automation requirements
were outlined:• Automate the fraud and dispute managementprocess, which monitors over tens of thousands
daily credit and debit card posting transactions• Automate adjustments to merchant credits,stop payments and write-offs to avoid manualverifications and ensure timely processing to
improve the user experience• Manage sensitive PII data related to card
details according to data storage compliancerequirements• Integrate data needed to validate end-toend business flow, to ensure that automatedprocesses can accurately pass values anddata between multiple systems forenvironmental stability• Bring real-time data access processes in house,to cut dependency on products and services
outside the bank’s network2• Improve tools that have hindered the scaling ofautomations across the organization• Repurpose up to 425+ full time employees overa 15-month period

More IT resources needed for theautomation
The bank was dealing with limited IT resources
to handle the automation, preventing themfrom scaling to the enterprise level or addressing
specific challenges. The automation plan
was not a simple one and required accessing
a very high volume of sensitive data across25+ applications including web, Windows,mainframe, Pega BPM software and otherthird-party products. The lack of staff, plus theneed for an enterprise automation strategy
and roadmap, created the need to bring in anautomation partner.
Adhering to critical performance standards wasanother goal, and the firm had to stay withineach process’s limited operating window andaggressive average handling time (AHT) of lessthan 10 minutes per transaction. There were also
target product metrics such as the percentageof records a bot should process; generally,
between 80% to 95% with the remainder leftto a specialist to resolve. Meeting these
performance metrics was key to ensuring thatthe bank could successfully process its tens of
thousands daily transactions.

| Intelligent automation helps bank cut fraud processing by 90%

The approach
We began with an assessment of the businessacross three areas: fraud and dispute
management, claims and alerts, and regulationand compliance.
Following our initial discovery and creation ofa scalable automation strategy that included
an enterprise-wide level architecture, wemoved forward to automate key businessprocesses. These included fraud recovery
processes, payment refund and electronicmoney management for several business
units: cards and payments, reconciliation,
onboarding, customer service, and regulatory
and compliance.
We set up a centralized operational model witha dedicated early engagement team, scalable
development pods and a flexible support team.
We used a Tableau dashboard to report input,output and outcome-based metrics, which
resulted in a self-service capability that gives thebusiness a real-time view of process performance
during automation, and this also reduced
dependency on the support team.

During the implementation, we built anddeveloped several automation capabilities
such as:• Automated health check bots to monitor
application availability, generate businessalerts/notifications and perform regression tests
periodically, unsolicited• Code review and coverage bots to ensure code
quality, efficiency and effectiveness, resulting ina very low defect density (4.3 out of 100story points)• A diamond architecture model following
the principles of separation of concernsand single responsibility with horizontal
auto-scaling of process bots based on seasonal
volume fluctuations• Frameworks like Spring Boot & .NET to build
reusable assets and components to overcome
WinAutomation tool limitations• Enabler bots to augment functional bots,covering cross-cutting between different
parts of the engineering project such as
generate/run logs, exception handling andalerts management• Custom bots to simulate/mimic the potential
test data for maximum test coverage tomitigate the challenge of test data availability• Definition-of-ready scorecard factoring intechnical and environmental factors toestimate automation feasibility, and tovalidate the readiness of business processes
for development

3| Intelligent automation helps bank cut fraud processing by 90%

Business outcomesOur managed services engagement delivered
the automation transformation our client
wanted, from feasibility through all necessary
automations. Because the engagement structure
allowed us to understand and predict what it
would take to support the various bots, we wereable to commit to a fixed capacity support
team—something no other competitor wasable to offer. This gave our customer thepredictability and risk transfer needed to realize
its automation vision.

The engagement also defined the line ofbusiness (LoB) level architecture framework
for automation, which paves the way for
new automations to use the established bestpractices, reusable components and standards
for coding, naming conventions and more.
These guidelines help inform and improve thedevelopment of newer bots at a faster pace.
In addition, several automation innovations that
we recommended are now standardized acrossthe bank.

Our banking client achieved several
business benefits:• Reduced current Average Handling Time (AHT)
by 20%• Reduced exceptions from 100% to 8-10%• Repurposed 425+ FTEs across the US, Indiaand Manila saving $20M annually in staff/direct
costs and infrastructure/indirect costs• Improved ROI for fraud and dispute-related
processes, delivering $8.10 per every
dollar spent• Enabled capacity to process 30 million
transactions annually

Cognizant (Nasdaq-100: CTSH) engineers modern businesses. We help our clients modernize technology, reimagine processes and transform experiences so they can stayahead in our fast-changing world. Together, we’re improving everyday life. See how at www.cognizant.com or @cognizant.

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