A Leading UK Bank Reduced Cost of Ownership by 20% and Accelerated Regulatory Reporting Using AWS-Powered Big Data Platform

Challenges

The client’s large-scale, on-premises big data environment—spanning over 100 nodes—struggled to meet the demands of a dynamic banking ecosystem. Migration to the cloud was critical, yet it posed substantial risks and challenges:

• Ensuring regulatory reporting SLAs were met during migration without service disruption
• Modernizing outdated Spark and Java codebases for cloud compatibility
• Lack of automated testing, resulting in inconsistent code quality and elevated operational risks
• Persistent scalability issues in non-production environments, slowing delivery and innovation cycles

Solution

We engineered a modern, AWS-powered Big Data Analytics Platform, enabling seamless migration while safeguarding compliance, improving efficiency, and eliminating infrastructure overheads.

 Key solution highlights:

• Deployed an AWS Data Lake for centralized, secure storage and batch processing of 70+ regulatory data pipelines
• Utilized on-demand EMR clusters for optimized data processing and AWS Step Functions for automated workflow orchestration
• Upgraded Spark and Java frameworks, enhanced libraries, and implemented automated test coverage to elevate code quality
• Integrated AWS Glue for structured metadata and Amazon Athena for high-speed querying and analytics
• Enabled multi-source ingestion for accurate and timely risk assessments across secured and unsecured lending portfolios

The Impact

Our engagement delivered measurable business value:

• 20% reduction in total cost of ownership with zero ongoing infrastructure maintenance
• 20% faster execution times, ensuring SLA adherence and accelerating regulatory reporting
• Reduced job delays from ~5 per month to 0, enabling 100% on-time UAT completion
• Eliminated scalability bottlenecks, enabling faster parallel processing and improved time-to-market