Case Study: Finastra achieves real-time, high-performance risk and pricing at scale with GridGain

Finastra Uses GridGain to Enable High-Performance, Real-Time Data Processing

Finastra, a London‑headquartered provider of financial services software used by thousands of customers including 90 of the world’s top 100 banks, faced growing bottlenecks from batch processing as it moved to a Java-based stack and data‑lake architecture. The company needed real‑time calculation and reporting to meet customer demands and evolving European regulatory requirements (such as FRTB) for more compute‑intensive risk and valuation workflows.

Finastra deployed the GridGain in‑memory computing platform (built on Apache Ignite) to cache data in memory and parallelize processing across commodity-server clusters. The solution delivered synchronous, low‑latency transactions and analytics, enabled the FusionFabric.cloud service with elastic, real‑time pricing and risk valuation, dramatically reduced processing times for regulatory calculations, and was implemented with responsive GridGain support.

Finastra

Benoît Riquet

Director Product Management for Fusion Risk and Pricing