Case Study: Algorithmic Trading Platform — RMB Morgan Stanley | Belton Bridge Analytics
Project Delivery & Trading Systems

Algorithmic Trading Platform — End‑to‑End Delivery

Taking a new equity derivatives algo trading product from concept to live trading, ahead of schedule and 40% under budget.

40%
under budget vs projection
1 month
ahead of schedule at go-live
£250m
trading capital allocated on launch
18% ROE
projected return on strategy
20+
stakeholder groups coordinated
ClientInvestment Bank & International Stockbroker JV
Duration18 months
ServicesProject Delivery · Trading Systems · Murex
Location UK / South Africa

The challenge

A joint venture between two leading investment banks and an international stockbroker had the technical infrastructure, Murex platform, pricing models, and risk analytics to support algorithmic trading in equity derivatives. But they had consistently failed to bring these capabilities to market.

Previous launches had stalled due to fragmented ownership, insufficient business cases, unclear value propositions, and difficulty coordinating across more than twenty internal functions with competing priorities. The organisation needed someone who could span the full gap between technical delivery and commercial execution — simultaneously operating as business analyst, project manager, Murex specialist, and strategic advisor.

The core problem wasn't technical. The infrastructure existed. The gap was translating it into a commercially viable, cross-functionally approved, operationally ready product — and doing so quickly enough to justify the investment.

What we delivered

  • 1
    Business development & value proposition (months 1–2)Needs analysis with business leadership. Capabilities assessment across staff, systems and platforms. Financial models and ROI projections to secure C-suite approval and project funding.
  • 2
    Multi-stakeholder engagement framework (months 2–3)Mapped all 20+ stakeholder groups, defined requirements, decision rights and dependencies. Established governance structure with clear escalation procedures and accountability.
  • 3
    Technical-commercial translation (months 3–5)Worked with Murex and technical teams to document platform capabilities in commercial terms. Created tailored materials for different audiences. Represented the product through executive, change management, methodology, and regulatory review boards.
  • 4
    Multi-party agreement management (months 4–6)Negotiated service agreements between JV entities with different governance requirements. Structured arrangements covering IP ownership, data sharing protocols, and liability allocation across multiple jurisdictions.
  • 5
    End-to-end delivery & go-live (months 1–18)Led all coordination across technical delivery, operations, compliance, and commercial teams. Managed vendor relationships and system integrations. Reported directly to executive steering committee.

Stakeholder groups coordinated to sign-off

IT / Markets TechnologyMurex DevelopmentOperationsFinanceProduct ValuationModel ValidationMarket DataMarket RiskCredit RiskCollateralBusiness Resource MgmtLegalTaxationALMAExchange ControlLiquidity & FundingComplianceInsuranceElectronic TradingOperational Risk

Outcomes

40%
Cost reduction vs original budget through vendor management and scope control
1 month
Ahead of schedule at live trading launch
£250m
Trading capital allocation secured at launch from institutional investors
18% ROE
Projected return on equity for deployed algorithmic trading strategy
20+
Stakeholder groups aligned and signed off, many with competing priorities
Adopted
Delivery methodology became template for all subsequent product launches

Belton Bridge Analytics demonstrated professionalism, effective stakeholder engagement, and strong project delivery discipline. Their work met our internal standards, particularly regarding regulatory and operational requirements. The project was delivered ahead of schedule and met the agreed scope and governance standards.

Electronic Trading Head, Stockbroker Stakeholder

What made the difference

The key to delivering where previous attempts had failed was combining capabilities rarely found in one resource: deep Murex and trading systems knowledge, genuine project management discipline, and the ability to build business cases and navigate commercial conversations at C-suite level.

Rather than treating the 20+ stakeholder groups as a coordination overhead, the engagement framework turned them into a structured approval pipeline. Each group received tailored communication, had clearly defined decision rights, and was held accountable within a governance structure they helped shape.

The 40% cost saving came from leveraging existing platform infrastructure rather than building new components, and from consolidating what would typically be the three separate roles of BA, PM, and Murex analyst into a single experienced resource from Belton Bridge Analytics.

Why this approach worked

  • One resource spanning technical and commercial — no translation gap
  • Governance framework built with stakeholders, not imposed on them
  • Existing infrastructure leveraged rather than rebuilt from scratch
  • Budget discipline from day one — scope managed proactively
  • Methodology documented for reuse across subsequent initiatives

Directly applicable to

  • New financial product launches stalling at stakeholder sign-off
  • Algo or electronic trading initiatives needing end-to-end delivery
  • Murex platform upgrades requiring BA + technical + PM coverage
  • Cross-border product rollouts with multi-jurisdiction complexity
  • Projects where previous attempts have overrun or been abandoned

Working on a similar challenge?

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