Banks
Large, fragmented data estates with entitlements spread across business units, and AI adoption running ahead of the governance built to supervise it.
Industries
Who we work with.
The problems rhyme across the sector but the constraints do not. Supervision, cost structure, data estate and commercial model all differ, and the diagnostic reflects that.
Asset managers
Cost pressure against a fixed fee base, index and vendor licensing complexity, and derived-data exposure in research and front-office workflows.
Exchanges & market infrastructure
Data as a revenue line rather than only a cost, with commercialisation, policy and distribution questions attached.
Insurance
AI adoption in pricing, underwriting and claims, with supervisory expectations on fairness, explainability and oversight tightening.
FinTech & digital assets
Fast-moving product teams meeting institutional licensing and control requirements for the first time.
Regulators & public sector
Market structure, data policy and technical understanding of practices supervisors are being asked to assess.
Different sector, similar question?
If the problem is data, licensing, AI governance or operating model, it is worth a conversation.