Sustainable trading analytics capability, built to last
We partner with trading organizations to deploy purpose-built tools and train teams in new ways of working — turning analytics from a discrete project into a lasting, in-house capability.
What we're here to do
Every engagement is built around four outcomes.
Material impact on trading P&L
Partner to deliver a framework for sustainable analytics development that has a materially positive impact on trading performance.
A toolset built for step-change
Implement a trading-analytics-specific toolset and associated work processes that enable rapid capability growth and the foundations required to deploy impactful AI.
Upskilling that sticks
Deliver upskilling via apprenticeship that ensures sustainable subject-matter expertise and the ability to keep improving long after the engagement ends.
Planning & performance discipline
Establish planning and performance processes that ensure quality in analytics and support change management on your organization's analytics growth journey.
Tools, people, process, and performance
Builds on decades of practical experience, providing the foundations for systematic analytics and AI.
Tools
What actually runs the analysis?
Model Development & Quality Assurance (MDQ) systematizes model builds and makes quality transparent. Clio Analytics Tool (CAT) facilitates rapid, systematic analysis. Forecast Analytics & Version Retention (FAVR) embeds data strategy and continuous improvement.
People
Who keeps it running after we leave?
An apprenticeship model develops internal subject-matter experts, coached on process and tools and trusted to steer AI — paired with broad organizational training.
Processes
How does it become the default way of working?
Standardized methods for model build-out, analytics reviews, and quality assurance — so common approaches hold across the organization.
Planning & Performance
How do we know it's working?
A benchmarked analytics roadmap, prioritized by value potential, with quality assurance and management oversight built in.
Principles that guide every engagement
The six beliefs that guide every engagement.
Trust is the currency of analytics impact
If you can't explain why a trade makes sense, will you know when the recommendation stops being valid?
Commercial impact depends on the analyst-trader partnership, driven by the quality of past recommendations.
Every recommendation must be explainable, provable, and qualified
Are insights limited by scale, or by robustness?
To unlock margin, analysts and AI agents rely on having large volumes of high-quality data surfaced and ready for analysis.
Analysts lead the thinking
Whose judgment is the AI amplifying?
Commercial impact depends on the analyst-trader partnership, driven by the quality of past recommendations — not the tool alone.
Deploy AI to amplify judgment, not replace it
Is AI expediting analysts' thinking, or shortcutting it?
AI should expedite and sharpen analysts' thinking and surface better questions — it does not shortcut the analytics process.
The product is capability, not just tools
What survives after the project ends?
Growing high-margin trading activity requires new, sustained capability, not just software. Capability-centricity drives analyst buy-in.
Change programs need to work on the first try
What happens to the next attempt if this one stalls?
First impressions stick — a failed step-change makes the next attempt harder.