From Mainframe to Modern: Streamlining Credit Data for Faster Decisions

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.