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  • Case study

Banking on cloud to build resilience

How a global financial institution enhanced its reputation with better business insights and a cloud-based system

Who we worked with

A multinational investment bank and financial services company

What the bank needed

  • A better customer and employee experience
  • Meaningful insights to drive business decisions

How we helped

  • Designed and implemented a cloud migration and modernization roadmap
  • Redesigned wealth management processes and applications using a microservices architecture
  • Created a unified and future-ready banking platform

What the bank got

  • Improved customer and employee experience
  • A 50% increase in the speed of customer data retrieval
  • Greater system uptime and reliability
  • Reduced infrastructure costs

​The challenge

Delays in customer response time caused by data overload and monolithic mainframes

The world's largest financial institutions manage countless transactions daily for customers around the globe. Regardless, customers expect their stock trading and other activities to proceed quickly and efficiently.

But a high volume of data threatened to overwhelm this bank's outdated systems – and the employees who managed them. The bank's huge, on-premise, and outdated mainframe systems had begun to cause delays in customer response times and overall system instability. Concerns about the loss of customer data, increases in disaster recovery times, and outages were on the rise.

The bank knew it was time to act – before its customers experienced major service disruptions that could damage its reputation.

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The solution

A redesign focused on speed, stability, and growth

The bank chose Genpact, its longstanding digital transformation partner, to develop a plan to eliminate its dependency on legacy systems.

For many businesses looking to future-proof their operations, the solution begins with cloud. Genpact advised the firm to migrate its applications to cloud on a new and improved microservices-based application – ideal for processing large volumes of data.

First, we conducted a design session with key business stakeholders to understand their challenges. Then, we developed an agile plan divided into 'sprints' – set periods of time during which we had to complete specific work. At the end of each sprint, we sought feedback from executives so we could incorporate their input into the next phase.

We also redesigned crucial wealth management processes and applications (such as financial advisor trading platforms) using a state-of-the-art, cloud-enabled microservices architecture. Microservices are to software what assembly lines are to manufacturing. The architecture splits large applications into smaller, more manageable pieces. This means that updates, maintenance fixes, and feature enhancements no longer require the bank's wealth management applications to be exposed, regression tested, and released to every single active installation, which reduces risk.

We built all of these changes into the firm's private cloud, but with a design flexible enough to support the firm's ambition to explore a migration to public cloud in the future.

Better still, the new banking platform integrates seamlessly with the older legacy systems and can cope with huge volumes of real-time data to support the firm's growth targets.

The impact

Happier customers, happier employees, and ongoing agility

Thanks to the modernization of legacy applications, data retrieval speed has increased by 50%, and data processing times have reduced. As a result, employees feel empowered to respond quickly and efficiently to customer requests – a win for everyone.

Today, the bank experiences greater system uptime and fewer crisis-management concerns. Offloading data from legacy systems has simplified processes, provided greater stability, and improved business resilience. If a problem should arise, the microservices architecture ensures quick resolution, which increases overall system uptime and decreases risk.

The move to the cloud also improved real-time data visibility to support the firm's ability to act on insight. It also helped employees work more efficiently and cut down on expensive mainframe processing and operational costs.

Looking to the future, the firm can use data-driven insights to create predictive analytics models to inform new go-to-market strategies – essential in a world where agility can make or break a business.

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