★ WIDE MOAT STOCKS & COMPETITIVE ADVANTAGES ★
VOL. XCIV, NO. 247
S&P Global Inc.
SPGI · New York Stock Exchange
Weighted average of segment moat scores, combining moat strength, durability, confidence, market structure, pricing power, and market share.
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Overview
S&P Global operates five reportable segments: Market Intelligence, Ratings, Energy, Mobility, and Indices. TTM revenue through Q1 2026 was led by Market Intelligence (31%) and Ratings (31%), while Ratings and Indices contributed about 56% of segment adjusted operating profit. The strongest moats remain Ratings, via NRSRO/regulatory barriers and trust, and Indices, via de facto standard benchmarks such as the S&P 500. Energy benefits from benchmark and royalty economics; Market Intelligence and Mobility rely more on workflow embedding and data breadth. Key pressures are data commoditization, fee negotiation by large customers, regulatory scrutiny, and the planned Mobility separation.
Primary segment
S&P Global Market Intelligence
Market structure
Oligopoly
Market share
—
HHI: —
Coverage
5 segments · 5 tags
Updated 2026-07-01
Segments
S&P Global Market Intelligence
Financial market data, analytics, and workflow tools for institutions
Revenue
31.5%
Structure
Oligopoly
Pricing
moderate
Share
—
Peers
S&P Global Ratings
Credit ratings and related research/analytics for debt capital markets
Revenue
30.6%
Structure
Oligopoly
Pricing
strong
Share
49%-52% (estimated)
Peers
S&P Global Energy
Commodity and energy price assessments, benchmarks, market data and analytics (incl. Platts)
Revenue
14.7%
Structure
Oligopoly
Pricing
moderate
Share
—
Peers
S&P Global Mobility
Automotive forecasting, data, analytics, and dealer/vehicle-history solutions
Revenue
11.2%
Structure
Competitive
Pricing
moderate
Share
—
Peers
S&P Dow Jones Indices
Index benchmarks and index licensing for passive funds, derivatives, and structured products
Revenue
12.1%
Structure
Oligopoly
Pricing
strong
Share
—
Peers
Moat Claims
S&P Global Market Intelligence
Financial market data, analytics, and workflow tools for institutions
Revenue share uses TTM segment revenue through Q1 2026 of $5.013bn normalized across the five reported segments. Operating profit share uses TTM adjusted operating profit of $1.714bn normalized across segment adjusted operating profit. Source: S&P Global 1Q 2026 Earnings Supplemental Disclosure.
Data Workflow Lockin
Demand
Data Workflow Lockin
Strength
Durability
Confidence
Evidence
Multi-asset data is delivered inside purpose-built workflows; switching typically requires re-integration, retraining, and process changes across research/risk/portfolio teams. Recent divestitures reduce scope at the margin but do not change the core workflow-lock-in thesis.
Data Workflow Lockin moat: definition, examples, and stocks
Erosion risks
- AI-driven data commoditization
- Price competition and vendor consolidation
- Open/free data substitutes and standardization
Leading indicators
- Organic revenue growth
- Net revenue retention / renewal rates
- User seats and platform adoption (where disclosed)
Counterarguments
- Large customers multi-source and can renegotiate aggressively
- Bloomberg remains the default workflow for many desks
Scope Economies
Supply
Scope Economies
Strength
Durability
Confidence
Evidence
Broad, multi-asset datasets and analytics can be reused across workflows and customer types, improving cross-sell and amortizing data/tech investment.
Scope Economies moat: definition, examples, and stocks
Erosion risks
- Rising third-party data licensing costs
- Regulatory constraints on data usage/transfer
- Customer preference for modular stacks
Leading indicators
- Attach rate of add-on datasets/workflows
- Mix shift toward higher-value analytics
- Gross margin and tech cost trajectory
Counterarguments
- Scope can add complexity; customers may still cherry-pick providers
- Competitors with scale (Bloomberg/LSEG) can match breadth
S&P Global Ratings
Credit ratings and related research/analytics for debt capital markets
Revenue share uses TTM segment revenue through Q1 2026 of $4.877bn normalized across the five reported segments. Operating profit share uses TTM adjusted operating profit of $3.200bn normalized across segment adjusted operating profit. Source: S&P Global 1Q 2026 Earnings Supplemental Disclosure.
Regulated Standards Pipe
Legal
Regulated Standards Pipe
Strength
Durability
Confidence
Evidence
NRSRO status and global CRA regulatory regimes raise compliance costs and create meaningful barriers to entry and scale.
Regulated Standards Pipe moat: definition, examples, and stocks
Erosion risks
- Regulatory initiatives to reduce reliance on ratings
- Higher liability standards / enforcement actions
- Conflicts-of-interest scrutiny (issuer-pay model)
Leading indicators
- Regulatory changes impacting rating usage
- Issuer mix (transaction vs surveillance) and pricing
- Market share in regulated jurisdictions (EU/UK)
Counterarguments
- Regulators may push rotation or encourage smaller CRAs
- Issuers can (and often do) multi-rate, limiting exclusivity
Brand Trust
Demand
Brand Trust
Strength
Durability
Confidence
Evidence
Investor trust and long-standing reputation support continued demand for S&P opinions, especially for widely distributed securities.
Brand Trust moat: definition, examples, and stocks
Erosion risks
- Reputational damage from high-profile rating failures
- Disintermediation by alternative risk signals
- Political/regulatory backlash during crises
Leading indicators
- Issuer adoption and repeat business (where disclosed)
- Investor usage of ratings analytics/research
- Regulatory commentary on CRA reliance
Counterarguments
- Trust is contestable over time (quality, perceived conflicts)
- Market can shift toward other providers for certain asset classes
S&P Global Energy
Commodity and energy price assessments, benchmarks, market data and analytics (incl. Platts)
Revenue share uses TTM segment revenue through Q1 2026 of $2.339bn normalized across the five reported segments. Operating profit share uses TTM adjusted operating profit of $1.121bn normalized across segment adjusted operating profit. S&P renamed this reportable segment Energy in FY2025.
De Facto Standard
Network
De Facto Standard
Strength
Durability
Confidence
Evidence
Benchmark prices and price assessments can become embedded reference points in physical and derivatives markets; exchange licensing reinforces standard-setting.
De Facto Standard moat: definition, examples, and stocks
Erosion risks
- Contract migration to alternative benchmarks
- Regulatory changes affecting benchmark administrators
- Competition from other price reporting agencies
Leading indicators
- Exchange royalty trends
- Subscription renewal performance
- Regulatory actions or benchmark methodology disputes
Counterarguments
- Benchmarks can be replaced if liquidity shifts to alternatives
- Customers may pressure pricing when multiple PRAs exist
Compliance Advantage
Legal
Compliance Advantage
Strength
Durability
Confidence
Evidence
Benchmark-administrator authorization and alignment with regulatory principles can be required for use in regulated contexts and raises barriers for smaller entrants.
Compliance Advantage moat: definition, examples, and stocks
Erosion risks
- Higher compliance costs reduce profitability
- Regulators revise benchmark rules or oversight
- Legal challenges to benchmark methodology
Leading indicators
- Benchmark regulatory audits/findings
- Changes to EU/UK benchmark frameworks
- Compliance investment requirements
Counterarguments
- Compliance is a cost and may not prevent competition from other authorized administrators
Data Workflow Lockin
Demand
Data Workflow Lockin
Strength
Durability
Confidence
Evidence
Subscriptions to market data, commentary, analytics, and software tools can be embedded into trading and risk workflows, creating practical switching frictions.
Data Workflow Lockin moat: definition, examples, and stocks
Erosion risks
- Data unbundling and price pressure
- Customer build-vs-buy internal analytics
- Free/low-cost data alternatives
Leading indicators
- Net retention rate and churn (where disclosed)
- Subscription vs non-subscription mix
- Customer concentration changes
Counterarguments
- Some data products are substitutable; customers can multi-source
S&P Global Mobility
Automotive forecasting, data, analytics, and dealer/vehicle-history solutions
Revenue share uses TTM segment revenue through Q1 2026 of $1.781bn normalized across the five reported segments. Operating profit share uses TTM adjusted operating profit of $717m normalized across segment adjusted operating profit. S&P announced a planned full separation of Mobility, expected mid-2026 subject to approvals.
Data Workflow Lockin
Demand
Data Workflow Lockin
Strength
Durability
Confidence
Evidence
Broad automotive value-chain coverage supports dataset depth and workflow embedding across planning, marketing, pricing, and finance/insurance use cases. A planned full separation of Mobility adds execution risk but does not invalidate current segment economics.
Data Workflow Lockin moat: definition, examples, and stocks
Erosion risks
- OEMs and large dealers building internal analytics stacks
- Alternative automotive datasets and platforms
- Cyclicality in automotive markets affecting spend
Leading indicators
- Dealer and OEM subscription trends (where disclosed)
- Retention/churn in Dealer business
- Share of revenue from new products/features
Counterarguments
- Automotive data/analytics is fragmented with many substitutes
- Coverage does not guarantee pricing power if switching is manageable
Switching Costs General
Demand
Switching Costs General
Strength
Durability
Confidence
Evidence
Dealer and OEM tooling tends to integrate with CRM/marketing/pricing processes; switching often requires data migration and workflow retraining.
Switching Costs General moat: definition, examples, and stocks
Erosion risks
- Interoperable APIs reduce switching friction
- Dealer consolidation increases buyer power
- New entrants with lower-cost offerings
Leading indicators
- Integration partnerships and API usage
- Customer concentration and renewal rates
- Competitive pricing trends
Counterarguments
- If data is standardized, customers can migrate with manageable cost
- Competitors can bundle similar dealer tools with marketplaces/financing
S&P Dow Jones Indices
Index benchmarks and index licensing for passive funds, derivatives, and structured products
Revenue share uses TTM segment revenue through Q1 2026 of $1.925bn normalized across the five reported segments. Operating profit share uses TTM adjusted operating profit of $1.371bn normalized across segment adjusted operating profit. Benchmark adoption context from S&P DJI Annual Survey of Assets.
De Facto Standard
Network
De Facto Standard
Strength
Durability
Confidence
Evidence
Flagship benchmarks (e.g., S&P 500) have extremely large assets indexed/benchmarked, reinforcing their role as default standards for funds and derivatives.
De Facto Standard moat: definition, examples, and stocks
Erosion risks
- Fee pressure from asset managers and exchanges
- Shift to alternative/custom indices
- Regulatory changes to benchmark administration
Leading indicators
- Assets linked/benchmarked to S&P DJI indices
- ETF/mutual fund AUM tied to S&P indices (where disclosed)
- Exchange-traded derivatives volumes referencing S&P indices
Counterarguments
- Large asset managers can sponsor or build proprietary indices
- Switching is possible for some products (especially new launches)
Ecosystem Complements
Network
Ecosystem Complements
Strength
Durability
Confidence
Evidence
An ecosystem of exchanges, asset managers, issuers, and investors builds products around established indices; this complements and reinforces adoption over time.
Ecosystem Complements moat: definition, examples, and stocks
Erosion risks
- Product innovation shifts liquidity to alternative ecosystems
- Key exchange relationships change
- Benchmark methodology controversy
Leading indicators
- New index-based product launches on S&P indices
- Renewals/expansions of exchange licensing
- Derivatives volume growth tied to S&P benchmarks
Counterarguments
- Ecosystem advantages can be competed away in newer asset classes
- Large partners may renegotiate fees due to scale and bargaining power
Benchmark Pricing Power
Financial
Benchmark Pricing Power
Strength
Durability
Confidence
Evidence
Asset-linked fees and usage-based royalties scale with AUM/volume; the segment has very high operating margins, consistent with strong pricing power on benchmarks.
Benchmark Pricing Power moat: definition, examples, and stocks
Erosion risks
- Asset outflows reduce AUM-linked fees
- Competitive fee compression
- Regulatory or legal constraints on index licensing
Leading indicators
- Asset-linked fee growth vs market AUM growth
- Operating margin trend
- Concentration in large asset managers/exchanges
Counterarguments
- Pricing may be capped by large counterparties bargaining power
- Benchmark fees can face scrutiny as passive investing scales
Evidence
Market Intelligence is a global provider of multi-asset-class data and analytics integrated with purpose-built workflow solutions.
Supports workflow-embedded product positioning, which typically drives integration + organizational switching costs.
registered with the SEC as a Nationally Recognized Statistical Rating Organization
Direct evidence of regulated status (NRSRO), a key structural barrier in the U.S. and a template for global regulatory frameworks.
has played a leading role for over 150 years
Company characterization supports the trust/reputation mechanism (stakeholders rely on the brand as financial infrastructure).
S&P Global Ratings Europe Limited 50.42% No
EU total market share for S&P Global Ratings Europe (2024 audited turnover basis).
S&P 1,055,822 1,066,386
S&P outstanding ratings as of Dec. 31, 2024 (supports scale share proxy vs total outstanding ratings).
Showing 5 of 19 sources.
Risks & Indicators
Erosion risks
- AI-driven data commoditization
- Price competition and vendor consolidation
- Open/free data substitutes and standardization
- Rising third-party data licensing costs
- Regulatory constraints on data usage/transfer
- Customer preference for modular stacks
Leading indicators
- Organic revenue growth
- Net revenue retention / renewal rates
- User seats and platform adoption (where disclosed)
- Competitive win/loss vs Bloomberg/LSEG
- Attach rate of add-on datasets/workflows
- Mix shift toward higher-value analytics
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