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How Asian FIs can survive digital disruption

Nurdianah Md Nur | June 7, 2016
"The FI that is able to ensure the continuous delivery of microservices will be the one that comes out ahead," says Sean Lee, Head of Business Development, Pivotal Asia Pacific and Japan.

Can you share with us examples and customer use cases on what Pivotal is doing with financial institutions in Asia  (including FinTech startups, bank funded startups and banking services solution providers)?

Data analytics is increasingly being imbued into every aspect of the financial institutions to accelerate digital transformation, improve business outcomes and maximise customer value. We have done a number of projects with financial institutions in the region.

For instance, SBI Securities was looking for a solution that would drastically reduce downtime and deliver greater performance with fewer resources. To help them meet their business goals, we worked together with both NRI and Hitachi, Ltd.  to build an In-Memory, Distributed Data Grid. The solution drastically reduced SBI Securities' data centre footprint by a factor of five, enjoy cost savings while affording the business with a system that is able to handle transactions at twice the volume as before with reference latency that is 20 times faster (.05 seconds vs. 1 second), and execution throughput that is three to four times faster.

On the other hand, facing intense domestic competition, China CITIC Bank Credit Card Centre was in need of a platform that delivered real-time mission-critical analytics and the ability to access data that would allow employees to customise their product marketing materials to specific customer profiles and complete campaign delivery in the shortest time possible. To help them meet their goals, Pivotal developed an enterprise data warehouse solution for China CITIC Bank that provided MPP architecture for data loading and parallel query processing to support operational, tactical and strategic business intelligence (BI) activities across the company. This enabled the integration of all data within a central database, optimised existing resources while delivering major savings due to reductions in space, power consumption and hardware requirements.

 

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