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Risk Management

Renowned Investment Bank Enhances Risk Management System (RMS)

Overview

A leading investment bank’s Risk Management System (RMS) had accumulated significant technical debt. Originally designed for daily batch processing, it was being pushed to support near-real-time risk calculations in an increasingly automated trading environment — and showing the strain.

This engagement reflects our core model: retained technical governance that operates alongside existing engineering teams, providing architectural authority without replacing headcount.

The Challenge

The legacy RMS could not handle modern intraday trading volumes without degraded performance. Risk calculations that should complete in milliseconds were taking seconds. Stress testing scenarios ran overnight rather than in minutes. The system’s monolithic architecture made it impossible to scale individual components, and any change risked cascading failures across the entire risk stack.

Our Approach

  • Full architectural assessment and latency profiling of the existing RMS
  • Decomposition roadmap: identified 7 independently scalable risk calculation modules
  • Deterministic Replay framework to validate new calculations against historical scenarios
  • Infrastructure modernization: migrated risk calculation to high-performance computing tier
  • Zero-Failover protocol with automated failback and calculation continuity guarantees
  • Governance framework to manage the 18-month modernization without operational disruption

Outcomes

60%
Faster intraday risk calculations
99.99%
System uptime during modernization
12hrs→8min
Stress test scenario runtime

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