System
Equity Trading Transformation.
Electronic equities trading at a global investment bank.
Replacing a fragmented, homegrown trading infrastructure with a single platform across the entire equity flow, on the bank’s own timeline, without freezing the development of the existing business.
Problem
A homegrown trading stack at the end of its useful life.
The system in production was a homegrown trading platform assembled over a decade and then strained by inheritance, with additional flows acquired through mergers, each built against a different set of internal infrastructural assumptions. By the time the bank started the rebuild, the consequences had compounded: performance below requirement, data loss on outages, feature velocity slowed by infrastructure maintenance, and a server footprint of more than 200 machines just for the order-management system.
Roughly 60% of the development team’s time was being spent on infrastructure rather than business logic. With trading alpha increasingly driven by data rather than infrastructure, that distribution had become untenable. The bank launched an initiative to revamp its equity trading system across every flow.
Architectural Constraint
The network between compute and state.
Traditional multi-tier architectures separate compute, data, and messaging into distinct tiers connected over a network. For trading systems, that separation is the bottleneck. The volume and velocity of data is too high, and the latency budget too tight, to support fetching data across the network on every request.
Industry practice had evolved to a different pattern, co-located compute and state communicating via message-passing between nodes. But no foundational substrate existed for it. Each trading team built its own from scratch. The bank’s team had been doing exactly that for years, and the infrastructure they had built could no longer keep pace.
Rumi solution
A common foundation across front office and middle office.
The bank standardized its next-generation equity trading system on Rumi. Rumi provides the substrate that the co-located-compute-and-state architecture was missing: data sourcing, persistence, encoding and decoding, HA consensus, message passing, exactly-once semantics, deployment, telemetry, and elastic scaling are all handled by the platform.
The bank’s developers wrote plumbing-free Java business logic, unit-tested in isolation, and promoted it to a distributed runtime through configuration alone. A single platform served front-office trade execution and middle-office services side by side, despite their different latency and high-availability characteristics. The rebuild proceeded flow by flow, with the existing system running in parallel during cutover.
Operational Outcomes
Performance, footprint, and cost together.
- <9 monthsfirst flow live in production
- <3 yearsfull sunset of the legacy system
- >10×throughput on high-touch flows (60× sustained during Covid)
- >10×wire-to-wire latency reduction on zero-touch flows
- 200+ → 6OMS server footprint, single consolidated OMS
- $50M / yrcost reduction across hardware, operations, and SLA penalties
- Zerodata or message loss across multi-year operation
- JVM & apptelemetry to per-message granularity with negligible overhead