Market Data Economics
Spend benchmarking, contract renegotiation, entitlement rationalisation and vendor consolidation across the major and specialist providers.
Explore
Financial Markets. Data. AI. Transformation.
Financial markets are changing. Your data, AI and operating model need to keep up.
ROSE is an independent financial-markets advisory firm helping institutions reduce data cost, govern AI, modernise operating models and turn emerging technology into measurable business value.
Independent · Senior-led · Financial-markets specialist
The ROSE Operating System
A data contract becomes a licensing problem. A licensing problem becomes an AI governance problem. An AI problem becomes an operating-model problem. ROSE connects the decisions.
- 01InsightWhat the data, cost and risk position actually is
- 02DecisionThe business case and the choice it supports
- 03GovernanceControls, ownership and evidence
- 04AdoptionBehaviour, operating model and capability
- 05ValueMeasured against the baseline agreed at the outset
FISD recognised trainerFIA certification provider
Singapore & Asia-PacificIndependent — no vendor relationships
Reduce
Unnecessary market-data and technology cost, contract leakage, duplicated entitlements and operational complexity.
Govern
AI, data and digital-asset risk — before it becomes an operational, contractual or supervisory problem.
Grow
Data, AI and operating capability turned into measurable business value rather than committed spend.
Start here
What problem are you solving?
Most institutions arrive with a specific, expensive question rather than a category. Choose the one closest to yours.
"Our market-data costs are rising and we cannot explain why."Market Data Cost Diagnostic
"We do not know where our AI exposure is."AI Governance Diagnostic
"We want to use licensed financial data with AI."AI Data Licensing Review
"Our AI pilots are not scaling into production."AI Adoption & Transformation
"We want to monetise a data asset."Data Commercialisation
"We are assessing tokenisation."Digital Asset Readiness
The ROSE Decision Architecture
Six steps, applied to every engagement.
The same sequence whether the question is a vendor contract, an AI inventory or a tokenisation thesis. It is how we avoid solving the wrong problem expensively.
01
Understand
Data, cost, risk and operating context as they actually are.
02
Diagnose
Exposure, opportunity and root cause — not symptoms.
03
Decide
The business case and the decision framework behind it.
04
Govern
Controls, ownership and evidence around the decision.
05
Adopt
Behaviour, operating model and capability change.
06
Measure
Value, risk and outcomes against the agreed baseline.
Solutions
Six places we do our best work.
Each overlaps with the others by design. A licensing problem is usually a governance problem, and a governance problem is usually an operating-model problem.
AI Governance
AI inventory, risk materiality, lifecycle controls, third-party exposure and board reporting — aligned to MAS expectations and the EU AI Act.
ExploreAI Adoption & Transformation
Why the pilot stalled, what has to change for it to scale, and the operating model and change work that decides whether anyone uses it.
ExploreData Commercialisation
Governance, lineage and quality as foundations, then turning data assets into products with a distribution model and a price.
ExploreDigital Assets & Tokenisation
Market-entry strategy, regulatory alignment, market structure and the operating model required before a launch is sustainable.
ExploreOperating Model & Advisory Office
Organisational and cost review, plus retained senior capability through the ROSE Advisory Office.
ExploreWhy this work matters
Most AI programmes fail for reasons that have nothing to do with the model.
Unclear success criteria. Data foundations that will not survive an audit. Licences that never anticipated a retrieval pipeline. None of it is a modelling problem, and none of it is fixed by more spend.
See how we approach it95%
of enterprise generative AI pilots deliver no measurable P&L return
MIT Project NANDA
80%
of AI projects fail — roughly twice the rate of conventional IT projects
RAND Corporation
42%
of companies abandoned most AI initiatives, up from 17% a year earlier
S&P Global, 2025
40%
of agentic AI projects forecast to be cancelled by the end of 2027
Gartner
Third-party research, cited to source. Figures reflect the most recent published studies available at the time of writing and are reviewed periodically.
The ROSE Standard
Independent. Evidence-led. Senior-led. Outcome-based.
Four commitments that hold on every engagement, and that you are entitled to hold us to.
We measure against a baseline
Agreed before the engagement begins. If success cannot be defined up front, we will say the engagement is not ready rather than start it anyway.
We hold no vendor relationships
No referral fees, no reseller margin, no implementation arm waiting downstream. Our advice on a vendor costs us nothing either way.
We say when there is no case
A diagnostic that ends in "you do not need us this year" is a good outcome, and it is why institutions come back when they do.
We work with implementation partners
When you need a build, we introduce firms we have worked alongside and stay on your side of the table throughout.
Book a Diagnostic.
Thirty minutes to identify the problem, the potential value and the right next step. No pitch deck.