Case Study: Major Global Investment Bank achieves real-time personalized trade recommendations with VoltDB

Bank Deploys Real-Time Analytics to Improve Trade Recommendations

Major Global Investment Bank faced a need to remove subjectivity from high-touch equity recommendations for private wealth clients by delivering automated, personalized trade ideas in seconds. The bank required a massively parallel, in-memory database that could scale linearly while preserving transactional consistency and high availability, and selected VoltDB’s in-memory transactional database to drive real-time personalization and analytics for its traders.

VoltDB ingests real-time feeds via message queuing (stock quotes, financial news, internal positions and proprietary data), processes thousands to millions of events per second, and analyzes more than 25 data sources to generate instant, client-tailored trade recommendations and heat-map displays. Deployed in under four months, the VoltDB-powered solution gives traders instant, data-driven options, improves service and retention for high-net-worth clients, reduces risk by filtering poor-fit recommendations, and increases profitability while feeding processed events downstream for reconciliation.