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Migration of Credit Risk Analytics Platform from SAS to Open Source Big Data Stack

senlainc.com

Financial services

Banking & Finance

Legacy SAS Infrastructure Limitations

Existing SAS-based credit risk analytics platform operates on a single dedicated server with limited scalability, high operational costs, and cloud dependency, creating bottlenecks for processing growing loan portfolios while maintaining Basel regulatory compliance

About the Client

A top-tier European bank with 200,000+ employees and 100+ million customers, requiring scalable and secure financial risk management solutions

Modernization Goals

Replace SAS with scalable on-premise open-source big data architecture
Maintain 100% calculation accuracy during migration
Reduce infrastructure costs through horizontal scaling
Enhance data security through self-hosted storage
Ensure seamless integration with existing compliance frameworks

Core System Capabilities

Apache Hadoop distributed storage layer
Apache Spark processing engine for risk calculations
Basel III/IV regulatory reporting module
In-memory analytics acceleration
Multi-node horizontal scaling architecture

Technology Stack

Apache Hadoop

Apache Spark

Java

On-premise distributed computing

System Integrations

Legacy banking systems
Regulatory compliance frameworks
Internal data governance tools

Operational Requirements

99.99% calculation accuracy retention
Linear scalability to petabyte-level datasets
Sub-second query response times
Enterprise-grade data encryption
High-availability cluster configuration

Business Transformation Outcomes

Enables 40-60% infrastructure cost reduction through open-source adoption, achieves 5x processing speed improvement with distributed architecture, maintains full regulatory compliance while enhancing data security posture, and future-proofs analytics capabilities for Basel IV readiness