Enterprise Data Platform for Financial Services
From Batch Processing to Real-Time Intelligence.
Top-20 U.S. Bank
The Challenge
A major U.S. bank relied on legacy batch-processing systems that introduced 24-hour data latency across risk management, fraud detection, and regulatory reporting. This delay created compliance exposure and prevented real-time fraud mitigation, resulting in $8M+ in annual fraud losses.
The Solution
We designed and implemented an enterprise-grade real-time data platform that replaced legacy batch jobs with streaming data pipelines. The new architecture enables sub-second data availability across all business-critical systems while maintaining strict regulatory compliance.
Our Approach
- Assessed existing data infrastructure and mapped 200+ data flows across departments
- Architected a modern lakehouse platform using Databricks and Delta Lake
- Migrated critical ETL workloads from legacy COBOL to Apache Spark
- Built real-time fraud detection pipeline processing 50,000+ transactions per second
- Implemented data governance framework with automated lineage tracking and PII masking
Technologies Used
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