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London Stock Exchange Group plc

LSEG · London Stock Exchange

Market cap (USD)$57.8B
SectorFinancials
IndustryFinancial - Data & Stock Exchanges
CountryGB
Data as of
Moat score
85/ 100

Weighted average of segment moat scores, combining moat strength, durability, confidence, market structure, pricing power, and market share.

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Overview

London Stock Exchange Group plc (LSEG) is a global financial markets infrastructure and data provider spanning Data & Analytics, FTSE Russell, Risk Intelligence and Markets. Its strongest demonstrated moats are workflow embedding in Workspace and World-Check, de facto benchmark adoption represented by $18.1tn linked to FTSE Russell, trading-venue liquidity, SwapClear netting and regulated exchange/CCP recognition. Generic group trust claims and broad data coverage are not recorded as separate brand or unit-cost moats. Q1 2026 total income excluding recoveries grew 9.8%, with Markets up 15.5% and combined subscription businesses up 6.3%. Key risks are data/workflow competition, routeable liquidity and regulatory or geopolitical pressure around clearing location.

Primary segment

Data & Analytics

Market structure

Oligopoly

Market share

HHI:

Coverage

4 segments · 5 tags

Updated 2026-07-12

Segments

Data & Analytics

Financial market data, analytics and workflows (terminals and enterprise feeds)

Revenue

46.5%

Structure

Oligopoly

Pricing

moderate

Share

Peers

SPGIFDSMORNMSCI+2

FTSE Russell

Index benchmarks, index licensing and index-linked analytics

Revenue

10.2%

Structure

Oligopoly

Pricing

strong

Share

Peers

MSCISPGINDAQICE

Risk Intelligence

Financial crime compliance, AML/KYC screening and risk intelligence data

Revenue

6.2%

Structure

Oligopoly

Pricing

strong

Share

Peers

RELXNWSATRIEXPN.L

Markets

Trading venues, capital formation, FX/fixed income platforms, digital markets infrastructure, and CCP clearing

Revenue

37.1%

Structure

Oligopoly

Pricing

strong

Share

Peers

ICECMENDAQCBOE+3

Moat Claims

Data & Analytics

Financial market data, analytics and workflows (terminals and enterprise feeds)

FY2025 total income GBP 4,338m and adjusted operating profit GBP 1,043m (Annual Report 2025, note 2.3). Revenue/profit shares computed across Data & Analytics, FTSE Russell, Risk Intelligence and Markets, excluding Other.

Oligopoly

Data Workflow Lockin

Demand

Strength

Strength 4 of 5

Durability

Durability 3 of 3

Confidence

Confidence 4 of 5

Evidence

Evidence 2 of 5

Core data + analytics are embedded in trading, investment and risk workflows; switching requires re-integration, user retraining, and data entitlement changes.

Data Workflow Lockin moat: definition, examples, and stocks

Erosion risks

  • Bloomberg remains the dominant terminal in many workflows
  • AI-native tooling could change how workflows are delivered (less dependence on traditional terminals)
  • Aggressive price competition in enterprise data feeds

Leading indicators

  • Annual Subscription Value growth (Data & Analytics)
  • Net retention / churn for Workspace
  • Enterprise feed win/loss rates

Counterarguments

  • Many large institutions multi-source data and can switch modules over time
  • Bloomberg ecosystem integration can outweigh LSEG's workflow advantages in front-office use cases

FTSE Russell

Index benchmarks, index licensing and index-linked analytics

FY2025 total income GBP 954m and adjusted operating profit GBP 546m (Annual Report 2025, note 2.3). Revenue/profit shares computed across Data & Analytics, FTSE Russell, Risk Intelligence and Markets, excluding Other.

Oligopoly

De Facto Standard

Network

Strength

Strength 4 of 5

Durability

Durability 3 of 3

Confidence

Confidence 4 of 5

Evidence

Evidence 2 of 5

Widely adopted benchmarks become embedded in mandates and products (ETFs, funds), creating switching frictions and reinforcing adoption via ecosystem complements.

De Facto Standard moat: definition, examples, and stocks

Erosion risks

  • Fee compression as large asset managers negotiate lower index licensing fees
  • Growth of self-indexing / custom indices by large asset managers
  • Benchmark regulation changes increasing compliance costs (e.g., benchmark administrator rules)

Leading indicators

  • Index licensing revenue growth
  • ETF AUM tracking FTSE Russell indices
  • Net new index mandates (wins/losses)

Counterarguments

  • Switching costs can be low for new products; mandates can choose MSCI/S&P alternatives
  • Large clients can diversify index providers and reduce dependency on any single benchmark family

Risk Intelligence

Financial crime compliance, AML/KYC screening and risk intelligence data

FY2025 total income GBP 579m and adjusted operating profit GBP 285m (Annual Report 2025, note 2.3). Revenue/profit shares computed across Data & Analytics, FTSE Russell, Risk Intelligence and Markets, excluding Other.

Oligopoly

Data Workflow Lockin

Demand

Strength

Strength 3 of 5

Durability

Durability 3 of 3

Confidence

Confidence 3 of 5

Evidence

Evidence 1 of 5

World-Check APIs can be embedded directly into payments, onboarding and KYC workflows. Integration creates implementation friction, although current disclosures do not quantify retention or migration cost.

Data Workflow Lockin moat: definition, examples, and stocks

Erosion risks

  • Standardization of APIs and data formats reduces integration friction
  • Procurement shifts toward best-of-breed point solutions

Leading indicators

  • Net revenue retention for Risk Intelligence
  • Expansion into adjacent risk modules per customer

Counterarguments

  • Compliance tooling can be modular and swapped without a full platform replacement

Markets

Trading venues, capital formation, FX/fixed income platforms, digital markets infrastructure, and CCP clearing

FY2025 total income GBP 3,467m and adjusted operating profit GBP 1,623m (Annual Report 2025, note 2.3). From 2025, Capital Markets and Post Trade are reported under a single Markets division.

Oligopoly

Two Sided Network

Network

Strength

Strength 4 of 5

Durability

Durability 3 of 3

Confidence

Confidence 4 of 5

Evidence

Evidence 2 of 5

Trading venues, Tradeweb/FX platforms and market infrastructure benefit from liquidity flywheels: more participants attract tighter spreads, more volume and deeper workflow integration.

Two Sided Network moat: definition, examples, and stocks

Erosion risks

  • Fragmentation of trading across alternative venues and internalization
  • Lower IPO activity and shift to private markets reducing capital formation volumes
  • Regulatory changes affecting market structure and fee models

Leading indicators

  • Equity capital raised and IPO pipeline trends
  • Tradeweb, FX and DMI volume trends
  • Market share of on-book trading vs off-book/MTFs

Counterarguments

  • Liquidity is portable and can shift to alternative venues when pricing/latency is superior
  • Global issuers can choose US/EU exchanges if listing economics are better

Clearing Settlement

Network

Strength

Strength 5 of 5

Durability

Durability 3 of 3

Confidence

Confidence 4 of 5

Evidence

Evidence 3 of 5

LCH/SwapClear clearing has strong network effects and netting benefits: more participants and product scope increase collateral efficiency and reinforce the incumbent CCP. Component-level market-share/HHI is supportable for SwapClear in EUR OIS clearing, but not for the full combined Markets division.

Clearing Settlement moat: definition, examples, and stocks

Erosion risks

  • Regulatory pressure to relocate or split clearing by jurisdiction (e.g., EU active account requirements)
  • Competitive incentives from rival CCPs (e.g., Eurex, CME)
  • Tail-risk events (member default) could harm trust and prompt regulatory intervention

Leading indicators

  • Share of cleared OIS/IRS volumes vs major CCP competitors
  • SwapClear client trade counts and notional cleared
  • Regulatory decisions affecting CCP recognition and location policy

Counterarguments

  • Regulators can mandate clearing location, weakening network effects by force
  • Large dealers can support multiple CCPs if economics/regulation shift

Concession License

Legal

Strength

Strength 5 of 5

Durability

Durability 3 of 3

Confidence

Confidence 4 of 5

Evidence

Evidence 2 of 5

Operating exchanges and CCPs requires regulatory recognition and ongoing supervision; this creates durable barriers to entry and supports incumbent infrastructure positions.

Concession License moat: definition, examples, and stocks

Erosion risks

  • Regulatory changes to exchange or CCP requirements increasing compliance costs
  • Political pressure to diversify away from a single dominant CCP in key products
  • Supervisory findings or outages damaging regulatory confidence

Leading indicators

  • Changes in CCP recognition regimes (UK/EU/US)
  • Material supervisory findings or enforcement actions
  • Capital and default-fund requirement changes

Counterarguments

  • Regulatory approval is a barrier, but incumbents still face competition once multiple venues/CCPs are recognized

Evidence

other

Open platform with high-value data and analytics... providing... workflow to enable customers to execute critical investing, trading and risk decisions.

Explicitly positions the product as workflow-critical, supporting workflow lock-in and switching costs.

other

Workspace users >300,000

Large installed base implies high switching costs (training + habit + tooling) and supports ecosystem adoption.

other

Benchmarks, indices and data solutions... Our indices help inform asset allocation... portfolio construction...

Positions FTSE Russell indices as foundational benchmarks in investment processes, consistent with de facto standard dynamics.

other

2025 FTSE Russell AUM $18.1tn

Large AUM linked to FTSE Russell indicates broad benchmark adoption and an ecosystem of index-linked assets.

other

delivers seamless, secure, enterprise-grade screening embedded directly into payment and onboarding workflows

Directly supports workflow embedding; LSEG Risk Intelligence says it serves more than 40,000 institutions in approximately 190 markets.

Showing 5 of 12 sources.

Risks & Indicators

Erosion risks

  • Bloomberg remains the dominant terminal in many workflows
  • AI-native tooling could change how workflows are delivered (less dependence on traditional terminals)
  • Aggressive price competition in enterprise data feeds
  • Fee compression as large asset managers negotiate lower index licensing fees
  • Growth of self-indexing / custom indices by large asset managers
  • Benchmark regulation changes increasing compliance costs (e.g., benchmark administrator rules)

Leading indicators

  • Annual Subscription Value growth (Data & Analytics)
  • Net retention / churn for Workspace
  • Enterprise feed win/loss rates
  • Seat growth for Workspace users
  • Index licensing revenue growth
  • ETF AUM tracking FTSE Russell indices

Keep the research going

Created 2025-12-30
Updated 2026-07-12

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