From Mainframe to Modern: Streamlining Credit Data for Faster Decisions
Overview.
A major European bank needed to update its credit data sharing process with Credit Reference Agencies (CRAs). Legacy systems slowed processing and limited scalability. Coforge helped them migrate data to a modern tech stack, enabling faster credit decisions and improved customer experience.
Challenge.
Legacy mainframe system hindered efficient credit data sharing with CRAs. Delays in credit scoring process due to limited transaction processing capabilities. Inability to comply with evolving regulations and interact with multiple CRAs. High maintenance costs associated with the legacy system.
Solution.
Conducted a discovery phase to identify data location (Bank's Data Lake). Built new data processing modules using Skala/Spark framework on the Hadoop Data Lake. Migrated data from legacy RDBMS to a modern SQL Server database. Implemented a micro-services and API-based architecture for dynamic CRA interaction. Decommissioned the mainframe processing system.
The Impact.
Metric
Improvement
Cost Reduction (Decommissioning Mainframe)
30%
System Maintenance Cost Reduction
25%
Transaction Processing Capability & Throughput
Increased
System Stability
Increased
Processing Errors & Infrastructure Issues
Reduced by 45%
Credit Decision Time
Days to Hours
Customer Experience
Improved
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