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H1 2026 interim results More valuable in an AI world
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2LSEG | +8.4% Record financial performance and significant strategic progress 1. Total Income (excl. recoveries). Constant currency growth 2. Adj. EBITDA margin, excluding FX impacts and including +140 bps benefit from the SwapClear revenue share agreement 3. Reported growth in adjusted EPS 4. Buybacks completed and dividends paid in H1 2026 Forging deep partnerships with our customers Developing sophisticated, multi - layered solutions Delivering trusted data and engineering expertise Organic Including accelerating subscription growth of +6.3% 52.7% +260 bps yoy 2 £2.6bn Strong revenue growth EBITDA margin expansion Double - digit earnings growth Significant shareholder returns +17.2% 2LSEG | 3 1 4
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3LSEG | 3LSEG | Our Markets businesses are critical to customers Interest Rate Swaps Foreign Exchange Trading +46% ADV of interest rate derivatives Trading +6% ADV of nominal value traded Clearing +45% ForexClear Notional value cleared Fixed Income Equity Trading UK +34% ADV of value traded Clearing +29% Notional cleared in interest rate swaps SwapClear +6% ADV of value traded Pan - European Clearing +7% Notional cleared +9% Nominal value RepoClear CDSClear Trading +9% ADV of cash credit instruments Notes: ADV – average daily volume
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4LSEG | 4LSEG | Driving sustained growth through innovation across Markets Powered by relentless focus on innovation o Expanding access to capital for private businesses through Private Securities Market o Facilitating instantaneous settlement of bank deposits with Digital Settlement House (DiSH) o Transforming the bilateral derivatives market with Post Trade Solutions o Providing new settlement options for gilts through the Digital Securities Depository (DSD) o Enabling near - continuous trading with LSE 24 Strong track record of organic growth across the Markets division 1 8.7% 7.9% 10.9% 8.9% 11.9% FY22 FY23 FY24 FY25 H1'26 1. Organic, constant currency growth
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5LSEG | 5.0% 5.8% 6.3% 6.7% 7.7% 7.1% 8.4% Our all - weather business model in action 5LSEG | 2020 2021 2022 2023 2025 2024 H1 26 1. Total Income (excl. recoveries) Source: LSEG data - 4% +10% - 40% +80% LSEG organic growth 1 (LHS,%) World Real GDP growth (LHS,%) Global Debt Issuance growth (RHS, %) Fed Funds Rate (LHS,%) FTSE World Index growth (RHS, %) US Equity Volatility (RHS,%) Global Equity Issuance (RHS,%) 8.4% 5.0% 5.8% 5.0% 8.4% 7.1% 7.7% 6.7% 6.3% 5.8% 5LSEG |
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6LSEG | Driving growth, expanding margins, actively deploying capital Michel - Alain Proch, CFO
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7LSEG | Delivering strong income growth Continuing strong organic growth1 8.2% 7.8% 6.3% 8.4% H2 2024 H1 2025 H2 2025 H1 2026 (GBP million) Q1 Q2 H1 2026 total income excl. recoveries 2,415 2,384 4,799 2025 total income excl. recoveries 2,261 2,228 4,489 Reported growth 6.8% 7.0% 6.9% Organic growth 1 9.8% 7.1% 8.4% Subscription businesses 1 6.3% 6.3% 6.3% 1. Organic, constant currency growth
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8LSEG | Driving growth across all divisions (GBP million) H1 2026 H1 2025 Reported growth vs H1 2025 Organic growth 1 vs H1 2025 Data & Analytics 2,061 1,991 3.5% 5.1% FTSE Russell 504 472 6.8% 9.1% Risk Intelligence 310 287 8.0% 9.7% Subscription businesses 2,875 2,750 4.5% 6.3% Markets 1,920 1,735 10.7% 11.9% Total income excluding recoveries 2 4,799 4,489 6.9% 8.4% Accelerating subscription revenues 1. Organic, constant currency growth 2. Totals include other income of £4m in H1 2026 and £4m in H1 2025 8LSEG |
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9LSEG | 1,991 2,061 H1 2025 Workflows Data & Feeds Analytics FX H1 2026 9LSEG | Data & Analytics £m 2.8% 6.0 % 7.5% Workflows Strong take - up of new AI tools; continued pipeline of innovation Data & Feeds Demand for data continues to grow; content expansion and enhanced distribution capabilities Analytics 33% growth in API consumption; strong demand for new cloud - based solutions Strong innovation - led growth across all businesses Growth rates on an organic constant currency basis.
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10LSEG | Data consumption continues to grow exponentially Our Real - Time platform continues to scale at pace Our innovation is driving growing data demand 21 m 23 m 25 m 30 m 39 m 44 m 2H 23 1H 24 2H 24 1H 25 2H 25 1H 26 ~39% p.a. growth in use of Tick History 2 Total number of customer requests for our data 4x increase in Real - Time data in 10 years 1 Peak number of datapoints provided each second (in millions) #1 global real - time data provider (~2x size of #2) ~ 26 million datapoints per second Unrivalled ~30yr time - series; continuously growing 110trn rows of data across 100m instruments 1. Increase in peak messaging rate in H1 2026 vs. H1 2016 2. Two year CAGR in Tick History API requests, H1 2026 vs. H1 2024 0 5 10 15 20 25 30 Nov-11 Oct-14 Sep-17 Aug-20 Jul-23 Jun-26
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11LSEG | 287 310 H1 2025 Organic FX H1 2026 472 504 11LSEG | Strong demand for flagship indices; innovation and higher asset prices supporting growth in asset - based revenues Sustained demand for World - Check; significant product innovation; strong volume growth in Digital Identity & Fraud 6.2% 14.9% 9.7% Risk Intelligence: £m FTSE Russell: £m FTSE Russell and Risk Intelligence Strength in recurring and asset - based revenues Growth rates on an organic constant currency basis. H1 2025 Subscription Asset - based FX H1 2026
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12LSEG | 92.8% Healthy sales and improving retention Retention rate 1 12 LSEG | £482m Gross Sales 2 25% New product vitality index 3 6.1% ASV 4 92.6% 92.4% 92.8% Jun-25 Dec-25 Jun-26 435 481 482 Jun-25 Dec-25 Jun-26 19% 24% 25% Jun-25 Dec-25 Jun-26 5.8% 5.9% 6.1% Jun-25 Dec-25 Jun-26 Supported by product innovation 1. Retention rate reflects the % of annualised subscription revenues from 12 months ago still being received today across Data & An alytics, FTSE Russell and Risk Intelligence 2. New business subscription sales over the last 12 months across Data & Analytics, FTSE Russell and Risk Intelligence 3. Income from products that are new or enhanced in the last five years, as % of total income excluding recoveries, across Data & A nalytics, FTSE Russell and Risk Intelligence 4. ASV growth will be retired as a KPI at the end of FY2026
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13LSEG | 1,735 1,920 13.0 % 13 LSEG | Markets £m Fixed Income Following exceptional Q1 volumes, Q2 growth normalised against demanding prior - year comparator Foreign Exchange New functionality driving volume growth despite moderation in market volatility OTC Derivatives Broad - based growth across all clearing businesses Driving growth across asset classes and through the trade lifecycle H1 2025 Fixed Income, Derivatives & Other Foreign Exchange OTC Derivatives Equities & Other 1 FX H1 2026 7.6% 13.6% Incl. Equities + 12.2 % Total income, all growth rates on an organic constant currency basis. 1. Other consists of Equities, Securities & Reporting, Non - Cash Collateral and Net Treasury Income
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14LSEG | 17.2% 16.6% 14.1% 8.4% AEPS AOP Adj. EBITDA Total income Strong EBITDA growth flowing through to AEPS Operating leverage in action 2 (GBP million) H1 2026 H1 2025 Reported Organic 1 Total income excl. recoveries 4,799 4,489 6.9% 8.4% Adjusted EBITDA 2,527 2,223 13.7% 14.1% Adjusted EBITDA margin 52.7% 49.5% Adjusted depreciation, amortisation & impairment (519) (497) 4.4% 5.6% Adjusted operating profit 2,008 1,726 16.3% 16.6% Adjusted net finance expense (149) (66) 125.8% Adjusted tax expense (448) (399) 12.3% Adjusted effective tax rate 24.1% 24.0% Non - controlling interest (194) (156) 24.4% Adjusted profit attributable to equity holders 1,217 1,105 10.1% Weighted average number of shares (million) 497 529 Adjusted earnings per share (pence) 244.9 208.9 17.2% 17.5% Growth % vs H1 2025 1. Constant currency organic growth 2. Total income, Adj. EBITDA and Adj. operating profit (‘AOP’) reflect organic constant currency growth. Adj. earnings per share (‘ AEPS’) growth on a reported basis 3. Total income excluding recoveries 3
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15LSEG | Continued healthy cost discipline Good progress on our insourcing programme (GBP million) 1H 2026 1H 2025 Reported Organic 1 Cost of sales 576 602 (4.3%) (2.5%) Staff costs 1,211 1,173 3.2% 5.7% Third - party services 138 172 (19.8%) (15.4%) Total labour cost 1,349 1,345 0.3% 3.1% As a % of total income excl. recoveries 28.1% 30.0% IT costs 343 324 5.9% 8.7% Other costs 191 165 15.8% 8.4% Total adjusted operating expenses ex FX items 2 1,883 1,834 2.7% 4.6% FX - related items 2 (1) 13 (107.7%) n/a Total adjusted operating expenses 1,882 1,847 1.9% 4.6% Total Group cost base 3 2,458 2,449 0.4% 2.8% Jun-25 Dec-25 Jun-26 72% 77% 75% 28% 23% 25% 37,700 37,494 37,495 HC Internal External HC HC 1. Constant currency organic growth 2. FX - related items represent fair value movements on embedded derivative contracts and foreign exchange (gains)/losses 3. Total Group cost base consists of cost of sales and adjusted operating expenses Growth % vs H1 2025
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16LSEG | 49.5% 49.8% 52.4% 52.7% Delivering operating leverage through disciplined execution H1 2025 EBITDA margin FX - related items 1 H1 2025 comparable Staff cost Third - party services Non - labour costs Change in SwapClear revenue share agreement H1 2026 underlying FX - related items 1 H1 2026 EBITDA Margin + 120bps underlying operating leverage 1. FX - related items represent fair value losses on embedded foreign exchange c ontracts (H1 2026: £8 million; H1 2025: £19 million), foreign exchange gains (H1 2026: £9 million; H1 2025: £6 million) and t ran slational FX 2. Non - labour costs include recoveries revenue, cost of sales and other operating expenses 30bps +60bps +80bps - 20bps +140bps 30bps
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17LSEG | Net finance expense reflects new interest rate environment (GBP million) 1H 2026 1H 2025 Interest expense on bank and other borrowings, net of derivative interest (198) (142) Bank deposit and other interest income, and other gains 57 79 Net lease interest expense (10) (10) Interest differential and foreign exchange losses (1) 5 Other 3 2 Adjusted net finance expense (149) (66)
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18LSEG | 24.1% tax rate within 24 - 25% guidance for FY2026 (GBP million) 1H 2026 1H 2025 Reported income taxes 319 230 Non underlying items: Reversal in income tax on amortisation of intangibles arising from acquisition 129 150 Transactions, integration and similar costs 2 19 Other (1) - Adjusted tax 448 399 Effective tax rate 24.1% 24.0%
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19LSEG | 160.9p 174.0p 208.9p H1 2023 H1 2024 H1 2025 H1 2026 244.9p +17.2% Delivering double - digit growth in Adjusted EPS +15.0% CAGR
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20LSEG | Further reduction in non - underlying costs (GBP million) 1H 2026 1H 2025 Adjusted operating profit 2,008 1,726 Non - underlying items: Transaction costs credit / (costs) 7 (15) Integration, separation & restructuring costs (19) (53) Depreciation & amortisation of purchased intangible and other assets (568) (597) Operating profit 1,428 1,061
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21LSEG | Exceptional growth in Equity FCF 21LSEG | Operating leverage in action 3 (GBP million) 1H 2026 1H 2025 Variance Reported EBITDA 2,515 2,155 360 17% Non - cash P&L items 97 127 (30) (24%) Change in working capital (477) (500) 23 (5%) Operating cash flow 2,135 1,782 353 20% Net interest on debt and commercial paper (106) (87) (19) 22% Net taxes paid (244) (213) (31) 15% Capex (428) (424) (4) 1% Lease payments (95) (75) (20) 27% Other items 1 (57) (48) (9) 19% Equity free cash flow (FCF) 2 1,205 935 270 29% Equity free cash flow per share (p) 242 177 65 37% Equity free cash flow per share: +37% vs H1 2025 1. Includes sales commissions paid and dividends paid to non - controlling interests 2. Equity free cash flow is the cash generated before M&A, returns to shareholders and financing activities 3. Total income, Adj. EBITDA and Adj. Operating Profit (‘AOP’) reflect organic constant currency growth. FCF per share and Adj. ear nings per share (‘AEPS’) growth on a reported basis 4. Total income excluding recoveries 37.0% 17.2% 16.6% 14.1% 8.4% FCF per share AEPS AOP Adj. EBITDA Total income 4
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22LSEG | 7,598 9,319 1,205 510 2,087 329 FY 25 net debt Equity free cash flow 2025 final dividend Share buyback Other items H1 26 net debt Our strong free cash flow supports growth and shareholder returns Leverage: 1.8x Further shareholder returns in H2 2026 £m Leverage: 2.1x Dividends Interim dividend of 55p , up 17%, totalling ~£270m Share buyback Remaining £1.35bn share buyback (runs to Feb 27) 3 22LSEG | 1. Represents cash dividends paid in H1 2026 2. Consists of Tradeweb share buybacks, acquisitions and disposals of financial and other assets, other financing cashflows and FX 3. Reflecting the announced £3.0bn FY2026 buyback and running until the end of Feb 2027, less the £1.65bn of that programme comp let ed in H1 2026 Leverage is calculated as operating net debt (i.e. net debt before lease liabilities and after excluding amounts set aside fo r r egulatory and operational purposes) to adjusted EBITDA before foreign exchange gains and losses 1 2
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23LSEG | c.100bps Improvement in constant currency EBITDA margin 7.0 - 7.5% Organic, constant currency income 1 growth, including an acceleration in our subscription businesses’ organic growth 2 c.9.5% Of total income 1 £2.7 billion Well positioned to deliver 2026 guidance Revenue EBITDA Margin Capex Equity free cash flow Guidance raised Initially targeting 6.5 - 7.5% income growth Guidance raised Initially targeting 80 - 100bps margin expansion 1. Total income excluding recoveries 2. Subscription businesses consist of the Data & Analytics, FTSE Russell and Risk Intelligence divisions 3. Includes 30bps contribution from the change in the SwapClear revenue share agreement 4. Based on foreign exchange rates of £1 = $1.32 and €1.17 3 4
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24LSEG | Mid to high single digit Growth 1 in total income 2 , including acceleration in subscription businesses 3 c.150 bps Cumulative improvement in underlying EBITDA margin 2027 - 2029 c.8% Of total income 2 in 2029 Double - digit CAGR in Equity f ree cash flow per share Revenue EBITDA Margin Capex Equity free cash flow 1. Organic, constant currency 2. Total income excluding recoveries 3. Subscription businesses consist of the Data & Analytics, FTSE Russell and Risk Intelligence divisions Medium - term guidance: 2027 - 2029 Accelerating subscription growth, strong cash conversion
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25LSEG | More valuable in an AI world David Schwimmer, CEO
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26LSEG | Data & Feeds revenue 90% proprietary datasets LSEG is the enduring partner of choice in an AI world Unmatched global reach and quality of data Deeply embedded in customer workflows Content structured to enhance AI accuracy and performance LSEG standards on public data LSEG IP on public data LSEG IP on specialised data LSEG standards on specialised data Real Time 10% 10% 10% 25% 45% Integrated in leading AI distribution channels
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27LSEG | IP protection AI sovereignty Cyber risk Regulation Accuracy Token costs and ROI 27LSEG | Customers rely on us to navigate the AI landscape LSEG data supports compliance with global regulatory standards LSEG’s resilient infrastructure is built to withstand evolving cyber threats Customers trust LSEG's data and tools to support their most sensitive workflows LSEG approach is model agnostic; our data is available wherever customers want to work LSEG optimises for LLM interaction, lowering token costs for customers LSEG's trusted, auditable data improves AI accuracy and confidence in outputs
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28LSEG | Customer considerations Workspace: LSEG / MS Teams / “headless” Customer proprietary solutions Third party solutions Use case dependent Human / agentic Addressing the breadth of customers’ AI needs LSEG Everywhere Consumption Intelligence Token costs AI sovereignty Single models or orchestration (multi - cloud/multi - model) Distribution Cyber risk IP protection MCP API Feeds Data platform On - prem Content Token costs Accuracy Regulation LSEG trusted data & analytics
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29LSEG | 31% 42% 26% 16% 15% 41% 28% 14% 35% 51% Driving industry adoption of our AI - ready data via MCP connectors Live Company fundamentals IBES estimates Macroeconomics News Fixed Income Analytics Securitized Instruments Coming in H2 • Pricing • Transcripts • FTSE Indices • Lipper funds • Ownership • Officers & Directors • Filings • LPC loan data • LSE 24 data Continued strong growth in customer adoption 1 9 92 154 202 23 December 20 February 20 April 13 July Global adoption 2 Broad - based interest 2 Variety of AI channels 2 Asia EMEA US Buyside Sellside Corporate Direct Microsoft Claude Others 1. No. of customers connected or onboarding to LSEG MCP servers 2. Based on no. of customers 29 LSEG |
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30LSEG | Building transformative products: Workspace Strong progress in the roll out of Workspace AI tools with new solutions introduced Workspace AI Search o Provides faster and simpler access to Workspace data o 17,000 active users o Focus on expanding capabilities through partner workflow integrations and customer data connectivity Workspace AI Deep Research o Supports institutional - grade financial research and analysis o Powering 7,000 users; adoption quadrupled since Q1 o Priorities include expanding data coverage and enhancing earnings - related workflows New | Company Intelligence o Agent - driven, customisable company reports, helping users spend less time searching and more time executing o Built on Financial Meeting Prep. ~3,000 reports generated per week ,, Using Deep Research, I’m genuinely impressed by the quality of the results… it delivers clear insights and brings a level of transparency and ideas I hadn’t previously considered”. Banking analyst ,, I really appreciate being able to conduct complex searches in natural language extremely quickly, without compromising data accuracy and without having to switch between multiple tools ”. Insurance analyst 30 LSEG |
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31LSEG | Building a more powerful, more connected LSEG experience Continuously enhancing Workspace Establishing powerful new capabilities Workspace integration with FXall +10% increase in engagement with FX users Updated messaging function +100m Workspace messages in Q2 Ongoing system optimisation +25% faster chart loading in H1 Preqin and eVestment private markets data in Workspace +1,000 pilot customers Workspace / Tradeweb interoperability Live H2 H1 Beta Live Live Microsoft integration o Seamless workflow through Workspace, Microsoft Teams, Microsoft Copilot and Open Directory o Joint go - to - market AI strategy with access to 1.5m+ licensed Copilot users in top 50 customers o Building momentum in Open Directory: 20+ customers onboarded; expansion opportunities across 40k+ Workspace Messenger and TORA users
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32LSEG | 32LSEG | AI - ready data via bulk feed / streaming AI - ready data via existing API or MCP Workspace AI Search Workspace AI Deep Research Commercial model Dataset - specific AI licence Expands existing data subscription model Dataset - specific AI licence Consumption tiers to capture value as usage scales Standard Workspace licence with fair use cap Supports value - based annual price review and upsell Premium Workspace add - on Usage - linked tiers based on query frequency LSEG cost drivers Cloud usage Data platform fee Token use Monetising our data with AI AI - ready data distribution AI workflow products
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33LSEG | Case study 1 Reimagining wealth and relationship management through AI AI collaboration Building AI - powered knowledge and intelligence platforms: 1. For relationship managers to prepare for client meetings, combining internal regulatory, product and financial content with LSEG News and market data to generate investment insights 2. For Banking and Capital Markets teams, combining internal CRM data with LSEG News and historical pricing to surface deal intelligence and support client engagement Empowering wealth advisors through MCP - based access to LSEG News, Fundamentals and Ownership data to enhance research synthesis and product discovery for enhanced client engagement. Data sets used / requested • News • Company fundamentals • Ownership Delivery mechanism • MCP • API Commercial model • AI application licence • MCP capability licence with consumption element Top 5 Banking client Existing relationship Longstanding strategic LDA client with broad adoption of LSEG solutions across Banking and Wealth businesses
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34LSEG | Case study 2 Powering next generation investment workflows AI collaboration Combining LSEG entity, symbology and ownership data with internal intelligence and other sources to enhance data interoperability and underpin three initial use cases: 1. LSEG Risk Intelligence Agent - detects emerging threats and potential portfolio impacts through continuous monitoring and intelligence 2. LSEG Counter Party Agent - helps middle office managers identify key intelligence on credit risk factors using LSEG’s quantitative risk analytics. 3. C Level Dashboard - delivers portfolio intelligence and expanding demand for premium data through AI - ready entitlements Data sets used / requested • Verified Entity Data as a Service (VEDaaS) • World-Check • Reuters News • StarMine Models • Adverse Media Delivery mechanism • MCP • API Commercial model • AI application licence • Risk Intelligence AI licence • MCP capability licence with consumption element Sovereign Wealth Fund Existing relationship Strategic buyside client with extensive use of LSEG content and data services across investment workflows 3.
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35LSEG | Case study 3 Transforming treasury workflows with AI AI collaboration Modernising FX hedging workflows through AI - powered models combining market, macroeconomic and news data. Leveraging structured and unstructured LSEG content to deliver explainable hedge recommendations and treasury insights. Data sets used / requested • FX forwards & spots • Volume surfaces • IR curves • Reuters News • Macroeconomics Delivery mechanism • MCP • API • Workspace Commercial model • AI application licence • MCP capability licence with consumption element Global Industrial Leader Existing relationship Longstanding LDA client with established FX, treasury and analytics workflows, now expanding into AI use cases
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36LSEG | Deep customer relationships Embedded, regulated workflows Trusted, proprietary data and intelligence Open, flexible approach Rapidly - expanding distribution LSEG is the enduring partner of choice in an AI world
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37LSEG | Delivering on our strategy for growth Broad - based growth; improving guidance Driving adoption of AI solutions Unprecedented pace of innovation in Markets Strong returns to shareholders Delivering on our strategy for growth
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38LSEG | Q&A
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39LSEG | Appendix 1 Five myths about AI and our business
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40LSEG | AI models cannot recreate what we provide ~90% of LSEG’s data sets are underpinned by real - time market data, proprietary IP, exclusive licences and specialist contributor content, supported by decades of domain expertise, rigorous governance and quality controls, not public - domain information that can be scraped or replicated. LLMs are probabilistic; many financial workflows need deterministic outputs In areas such as trading, risk, valuation and compliance, customers require precise, explainable, repeatable and auditable data and analytics, not a model’s best estimate. Our metadata and semantic structure make AI more efficient and cheaper to run Decades of tagging, identifiers and data standardisation help models find, interpret and connect information faster, reducing reliance on broad searches across unstructured data and lowering token consumption. Trusted LSEG data makes AI more valuable to institutional clients Grounding LLMs in curated, permissioned LSEG data sets drives real accuracy, reduces hallucination risk and gives customers greater confidence to use AI in highly regulated financial workflows. LSEG’s data composition Value of careful and diligent data curation 10% 10% 10% 25% 45% LSEG standards on public data LSEG IP on public data LSEG standards of specialised data sources LSEG IP on specialised data Real time Sourcing Creates decades of data history across financial services Cleansing & validation Ensures accuracy, timeliness, completeness Normalising & mastering Establishes a single, authoritative and consistent dataset Concordance & tagging Adds extensive metadata, making datasets navigable Distribution Delivers consistent data regardless of channel or format Data & Feeds revenue Myth 1 Reality Proprietary financial data cannot be replicated, and trusted data becomes increasingly critical as AI adoption scales. “AI models will recreate our data and disintermediate LSEG”
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41LSEG | We have already invested ahead of the market LSEG has historically invested over 10% of revenue into capex, more than double the intensity of most peers, giving us a strong technology, data and cloud foundation as AI adoption accelerates. AI - related costs are factored into our model and medium - term guidance Some cloud and token costs will increase, but these will be partly offset by efficiencies elsewhere, including engineering insourcing, automation and higher productivity across the organisation. Usage - driven costs can be reflected in customer economics Where customers use LSEG data through partner LLMs, token costs sit with the customer’s AI platform relationship; where token or cloud costs relate to our own AI products, our commercial models are designed to align charges with underlying usage, value delivered and associated costs. Capex is coming down, but will remain intentionally elevated As the spend required to fix the technical debt of the acquired Refintiv estate falls away, capacity is created for additional investment. Our guidance for high - single - digit capex intensity reflects this trend, while also recognising that innovation in data, cloud and AI requires sustained investment. LSEG capex intensity vs peers 1 10.2% 7.7% 5.8% 4.7% 4.7% 4.4% 4.1% 1.2% LSEG Exchange operator 1 Data provider 1 Exchange operator 2 Data provider 2 Data provider 3 Index provider 1 Index provider 2 Myth 2 “LSEG capex and opex will need to rise with AI adoption” Reality LSEG enters the AI era from a position of investment strength, not investment catch - up . LSEG capex intensity over time 13.0% 12.9% 11.3% 10.2% 8.9% 2022 2023 2024 2025 H1'26 1. Capex intensity comparison based on FY25 company filings. Metrics reflect consensus estimates if not reported by company.
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42LSEG | Headcount decline is not a new trend in the financial sector Automation has been reducing trading and research roles for years, but this has not prevented market data and workflow providers from growing. Our commercial model is now less exposed to seat count Commercial models have evolved over time. Our enterprise - wide LDA agreements, which now account for almost 20% of D&A revenues, are one example of this shift. Alongside this, data, analytics and other solutions are monetised through a range of subscription, tiered and usage - based models that are largely independent of seat counts, leaving only a small portion of revenues directly linked to industry headcount. The value is shifting from seats to data consumption and workflow activity Customers may use fewer screens over time, but AI agents consume significantly more data than human users, reinforcing demand for trusted data, analytics and embedded workflow tools across regulated financial workflows where LSEG remains deeply integrated. LSEG has grown despite declining desktop volumes Financial desktop seats have historically declined by c. 1% per year, yet LSEG has successfully grown Workflows revenue for the last three years. While seat count declines, industry data spend ramps up 1 (26%) 114% (40%) (20%) 0% 20% 40% 60% 80% 100% 120% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Cumulative headcount growth Cumulative growth in segment spend 6% 8% 9% 16% 18% Dec-22 Dec-23 Dec-24 Dec-25 Jun-26 Myth 3 1. Headcount based on Coalition Index from Crisil Coalition Greenwich; segment spend per Burton Taylor Financial Market Data & Analysis reports. “Industry headcount will decline, impacting LSEG’s Workflows revenue” Reality Demand for data and workflows continues to grow despite industry headcount trends. LDA’s contribution to D&A ASV
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43LSEG | Wealth & Academia Investment Banking & Consulting Trading AI is not a like-for-like cheaper substitute for desktop LSEG desktop pricing has a very wide range depending on user type. Trading customers with regulated and embedded workflows are the highest-value, and not at risk of disintermediation. Price per user can be lower than an AI equivalent once LLM subscriptions, token usage and licensed financial data are included. Core desktop workflows remain highly defensible Around 70% of Workflows revenue is linked to trading-related workflows, where users rely on auditable data, regulated environments, execution connectivity and deep workflow integration - capabilities not replicated by standalone AI interfaces. We are actively investing to keep Workspace at the forefront of workflow innovation We are embedding AI directly into Workspace, enabling customers to access the latest AI capabilities within their trusted desktop environment. AI Search and Deep Research bring natural language discovery, insight generation and complex financial analysis into existing workflows, reinforcing Workspace’s relevance, utility and appeal for sophisticated financial professionals. Our “headless” approach – delivering the data and intelligence of Workspace into customer environments – grows our market opportunity. We monetise trusted data regardless of interface AI interfaces do not remove the need for proprietary data. Whether customers consume our content through Workspace, MCP, APIs, Cloud, partner platforms or their own proprietary solutions, LSEG data remains essential and the commercial models we put in place capture this value. Workflows revenue composition 10% 5% 15% 20% 50% 70% Invest. Mgmt. Wealth Mgmt. Investment Bankers Non-desktop trading revenue Trading Myth 4 “Desktop usage will migrate to MCP, diluting revenue” Reality LSEG achieves value regardless of interface, while core workflow solutions continue to deliver differentiated value. Workspace pricing reflects workflow complexity1 1. Representation of annual charge per user type; not to scale.
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44LSEG | Unbundling reduces AI’s accuracy and efficiency AI can process large volumes of information across asset classes, geographies and content types; but breaking data sets into narrower, disconnected feeds limits the model’s ability to reason across information, increases token costs and weakens the quality of the output. Fragmented data creates friction for AI and heightens cyber risk Licensing multiple niche providers with different taxonomies, identifiers and metadata layers increases complexity and token consumption, and can degrade model performance. Newer entrants also increase risk for customers, who value the security and institutional knowledge of a provider like LSEG. Competition remains based on quality , breadth and trust The market for financial data provision has always been competitive. MCP makes access easier, but it does not change what customers value: comprehensive, trusted, AI- ready data that improves outcomes, an area where LSEG is strongly positioned. AI is already driving cross-sell opportunities across Data & Analytics, with further potential across the Group as MCP coverage expands. Consistent metadata is a major advantage LSEG’s identifiers, tagging and semantic structure act as a map for AI models, helping them interpret, link and retrieve information more accurately and with lower token consumption across millions of instruments and content types. Fragmented data feeds from multiple providersMyth 5 “MCP will reduce switching costs, leading to feed unbundling and deflation” Reality MCP lowers access barriers, but competitive advantage shifts to providers whose structured content helps AI deliver better results at lower cost. Access to LSEG’s data platform Provider A Company fundamentals Provider B Pricing Provider C ESG Data Provider D News Inconsistent metadata layers AI Company data News Deals & ownership Analytics Pricing Commodity data Macro And more! Multiple IDs One consistent semantic layer Multiple taxonomies More reconciliation Identifiers Metadata Tagging Taxonomy AI Better reasoning Higher accuracy Greater trust Weaker context Lower confidence Higher token costs
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45LSEG | Appendix 2 The regulatory ecosystem for financial data
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46LSEG | The regulatory ecosystem for financial data (1/5) Regulatory driver / area Key regulators / frameworks Why this drives demand for trusted data Why customers rely on LSEG LSEG products / embedded regulatory value* AML, KYC, sanctions & financial crime FATF, AMLA, FinCEN, FCA, OFAC, OFSI, national FIUs; AMLR, AMLDs, FATF Recommendations, Global sanctions regimes Regulated firms need to identify customers, sanctioned parties, beneficial owners, PEPs, adverse media and financial crime risk indicators Customers require curated, maintained and explainable data with provenance, auditability, screening logic and ongoing monitoring World - Check sanctions datasets, PEP data, adverse media, beneficial ownership, EDD reports Corporate transparency, beneficial ownership & entity identification FATF, AMLA, FinCEN, FCA, OFAC, OFSI, national FIUs; AMLR, AMLDs, FATF Recommendations, Global sanctions regimes Firms need reliable entity, ownership and control information for onboarding, risk management, AML, sanctions and reporting Public data can be fragmented, outdated or inconsistent; customers need verified, standardised and linked entity data World - Check, LEI, PermID, hierarchy data, beneficial ownership datasets Trading, best execution & market transparency ESMA, FCA, SEC, CFTC, IOSCO; MiFID II/MiFIR, SEC/CFTC market rules Trading and investment firms need accurate, timely and resilient data for execution, pricing, valuation and transparency obligations Regulated workflows depend on timely, licensed, consistent and operationally resilient market/reference data Real - Time, Workspace , exchange data, market news, analytics Workspace, Autex Trade Route, Trade Notification and Deal Tracker are integrated trading workflow services supporting execution, post - trade transparency, compliance monitoring and operational risk reduction. Workspace combines real - time market data, Reuters News, analytics and execution tools. *Products in bold are critical ICT services under DORA in the EU
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47LSEG | Regulatory driver / area Key regulators / frameworks Why this drives demand for trusted data Why customers rely on LSEG LSEG products / embedded regulatory value* Transaction, regulatory reporting & data standardisation ESMA, FCA, SEC, CFTC, EBA, ECB, ASIC, MAS; MiFIR, EMIR, SFTR, Dodd - Frank, LEI/ISO standards Firms need structured, standardised and reconcilable data for transaction reporting, regulatory reporting and supervisory submissions Reporting requires high - quality identifiers, symbology, instrument data, entity data and control - ready datasets Reference Data, LEI, venue and issuer datasets DataScope Select and DataScope Plus are validated pricing and reference - data platforms supporting security masters, valuation, regulatory reporting and compliance. They provide legal entity data, regulatory attributes (e.g. MiFID II, SFTR), audit trails, APIs and bulk delivery. Benchmark administration & benchmark usage FCA, ESMA, IOSCO, SEC, CFTC; UK BMR, EU BMR, IOSCO Benchmark Principles Benchmark users rely on independently governed indices and transparent methodologies to construct investment products, measure performance and support investment decision - making. Customers require benchmark integrity, methodology governance, oversight, transparency and resilience, together with reliable operational delivery of benchmark data into production investment processes. FTSE Russell Indices, FTSE UK Index Series, Russell US Indices, FTSE Fixed Income Indices, benchmark administration. FTSE Russell provides BMR/IOSCO - aligned benchmark governance, methodology and operational resilience; Availability on Workspace and Datastream offers efficient delivery options coupled with broader investment workflow integration. The regulatory ecosystem for financial data (2/5) *Products in bold are critical ICT services under DORA in the EU
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48LSEG | Regulatory driver / area Key regulators / frameworks Why this drives demand for trusted data Why customers rely on LSEG LSEG products / embedded regulatory value* Investment Management, Fiduciary Duties & Product Governance FCA, ESMA, SEC, IOSCO; UCITS, AIFMD, Investment Company Act, MiFID product governance Asset managers and institutional investors need reliable benchmark, fund, portfolio, ESG, market and reference data Investment decisions and client disclosures require trusted datasets, analytics, licensing and consistent methodologies FTSE Russell Indices, Lipper, Workspace , portfolio analytics, benchmark licensing, investment datasets Workspace, Datastream and Lipper underpin investment workflows including portfolio construction, benchmarking, research, client reporting and fund analytics. Lipper supports fund selection, due diligence and regulatory reporting. Prudential supervision, capital, liquidity & stress testing BCBS, FSB, ECB, EBA, PRA, Federal Reserve, OCC, APRA, MAS; Basel III, CRR/CRD, PRA Rulebook Banks need robust data for capital adequacy, liquidity, risk management, stress testing, recovery planning and supervisory engagement Supervisory processes require historical depth, methodology consistency, quality controls and defensible data lineage Datastream, Workspace , yield curves, macroeconomic data, pricing data, company fundamentals, risk analytics Datastream provides 120+ years of macroeconomic and cross - asset history for stress testing, scenario analysis and quantitative research. Real - Time services provide resilient market data for supervisory risk processes. The regulatory ecosystem for financial data (3/5) *Products in bold are critical ICT services under DORA in the EU
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49LSEG | Regulatory driver / area Key regulators / frameworks Why this drives demand for trusted data Why customers rely on LSEG LSEG products / embedded regulatory value* Valuation, pricing & model risk governance PRA, ECB, EBA, SEC, Federal Reserve, IOSCO; IFRS 13, prudent valuation rules, model risk guidance Firms need reliable pricing and valuation inputs for fair value, IPV, model validation, collateral and risk controls Customers need controlled, consistent and explainable pricing inputs suitable for governance, audit and model oversight Pricing services, evaluated pricing, yield curves, reference data, market data, analytics via Workspace and LSEG Data Platform DataScope , Pricing Services and Real - Time services provide evaluated pricing, corporate actions, reference data, audit trails and resilient data delivery supporting fair value, IPV and model governance. Financial market infrastructure & market integrity CPMI - IOSCO, Bank of England, ECB, ESMA, SEC, CFTC; PFMI, EMIR, CSDR, MIFID II/MIFIR Exchanges, CCPs, CSDs and market participants require high - integrity data to support trading, clearing, settlement and valuation Critical market functions require resilient, timely, governed and auditable market and reference data Real - Time services, London Stock Exchange market data, Turquoise secondary market data, pricing services, reference data, datasets supporting trading, clearing and settlement Operational resilience, outsourcing & critical third - party risk ESAs, DORA Lead Overseers, FCA, PRA, Bank of England, ECB, Federal Reserve, MAS, APRA; DORA, UK Operational Resilience Regime, outsourcing guidelines Regulated firms must assess resilience, cyber, concentration risk and oversight of critical data and technology providers Customers need confidence in provider governance, resilience, auditability, service continuity and supervisory engagement World - Check, Workspace, DataScope, Datastream, Real - Time services, Lipper, Autex and Trade Notification are examples of services treated as critical by EU customers under DORA with SLAs, disaster recovery, cross - region failover and DORA - aligned operational resilience. The regulatory ecosystem for financial data (4/5) *Products in bold are critical ICT services under DORA in the EU
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50LSEG | Regulatory driver / area Key regulators / frameworks Why this drives demand for trusted data Why customers rely on LSEG LSEG products / embedded regulatory value* Privacy, data protection & data governance UK ICO, EDPB, EU DPAs, CCPA; GDPR Personal data within screening, adverse media, ownership and compliance datasets must be collected, maintained and used lawfully Customers require assurance around lawful collection, governance, transparency, rights handling, data stewardship and privacy controls World - Check, privacy governance, legal review, transparency and rights processes ESG, sustainable finance, climate & corporate disclosure ISSB, IOSCO, FCA, ESMA, SEC, EBA, ECB; ISSB standards, SFDR, CSRD/ESRS, EU Taxonomy, UK SDR Investors and firms need structured sustainability, climate and ESG data for disclosure, risk management and investment products Customers need comparable, governed and methodology - driven sustainability data, not merely summarised public disclosures FTSE Russell ESG Index Series, Sustainable Finance & Investment datasets, ESG analytics, climate datasets, sustainability reference data, accessed through LSEG products including Workspace, Lipper and Datastream to support customer research, portfolio analysis and sustainability disclosure workflows. The regulatory ecosystem for financial data (5/5) *Products in bold are critical ICT services under DORA in the EU
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51LSEG | Appendix 3 Additional financial tables
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52LSEG | H1 2026 condensed consolidated income statement (GBP million) H1 2026 P&L Transaction, integration and separation costs Depreciation, amortisation and impairment of assets Non - underlying finance expense Non - underlying tax Non - underlying loss attributable to non - controlling interest H1 2026 adjusted P&L Total income 4,985 4,985 Cost of sales (576) (576) Operating expenses (1,894) 12 (1,882) EBITDA 2,515 12 2,527 EBITDA margin 1 52.4% 52.7% Depreciation, amortisation and impairment (1,087) 568 (519) Operating profit 1,428 12 568 2,008 Net finance expense (150) 1 (149) Taxation (319) (129) (448) Non - controlling interest (145) (49) (194) Net income attributable to equity holders 814 12 568 1 (129) (49) 1,217 1. EBITDA margin calculated as EBITDA / Total income excluding £186 million of recoveries
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53LSEG | Net debt profile – by currency (GBP million) Total USD EUR GBP Other 2026 Bonds 604 604 2027 Bonds 1,396 451 945 2028 Bonds 1,631 752 430 396 53 2029 Bonds 1,550 1,292 258 2030 Bonds 1,178 615 497 66 2031 Bonds 1,363 936 427 2032 Bonds 628 488 140 2033 Bonds 427 427 2034 Bonds 558 558 2035 Bonds 42 42 2036 Bonds 740 740 2037 Bonds 24 24 2041 Bonds 558 558 Bonds 10,699 6,506 2,487 1,381 325 Commercial Paper 2,206 1,534 532 140 Other (8) (1) (7) Leases 614 249 35 234 96 Borrowings and lease liabilities 13,511 8,288 3,054 1,748 421 Cash and cash equivalents (4,056) (1,906) (703) (1,129) (318) Net derivative financial (assets) / liabilities (136) (80) (55) (18) 17 Net debt 9,319 6,302 2,296 601 120 Less lease liabilities (614) (249) (35) (234) (96) Regulatory and operational amounts 1,277 141 582 547 7 Operating net debt 9,982 6,194 2,843 914 31 Operating net debt as of 30 June 2026 Note: currency split reported on a post - swap basis
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54LSEG | Net debt profile – fixed vs floating (GBP million) Total Fixed rate Floating rate N/A 2026 Bonds 604 604 2027 Bonds 1,396 1,396 2028 Bonds 1,631 1,235 396 2029 Bonds 1,550 1,550 2030 Bonds 1,178 563 615 2031 Bonds 1,363 1,363 2032 Bonds 628 140 488 2033 Bonds 427 427 2034 Bonds 558 558 2035 Bonds 42 42 2036 Bonds 740 740 2037 Bonds 24 24 2041 Bonds 558 558 Bonds 10,699 8,038 2,661 Commercial Paper 2,206 2,206 Other (8) (8) Leases 614 614 Borrowings and lease liabilities 13,511 8,030 4,867 614 Cash and cash equivalents (4,056) (4,056) Net derivative financial (assets) / liabilities (136) 9 (145) Net debt 9,319 8,039 666 614 Less lease liabilities (614) (614) Regulatory and operational amounts 1,277 1,277 Operating net debt 9,982 8,039 1,943 - Operating net debt as of 30 June 2026