Financial Analytics Market by Component (Services, Software), Service Type (Managed Services, Professional Services), Application, End User Industry, Deployment Model - Global Forecast 2025-2032
Description
The Financial Analytics Market was valued at USD 60.37 billion in 2024 and is projected to grow to USD 67.02 billion in 2025, with a CAGR of 11.53%, reaching USD 144.58 billion by 2032.
A forward-looking framing of how regulatory complexity, technological advances, and enterprise demand are reshaping financial analytics capabilities and priorities
The landscape for financial analytics solutions has entered a period of accelerated transformation driven by converging regulatory, technological, and commercial forces. As capital markets, payment systems, and institutional risk functions evolve, analytics platforms are increasingly judged not only by accuracy but by speed, interpretability, and adaptability. Organizations now expect analytics to be embedded in decision workflows rather than operating as standalone tools, which raises new expectations for integration, security, and governance.
Against this backdrop, executives must reconcile legacy infrastructure with the demand for cloud-native capabilities and real-time insights. Advances in machine learning and data engineering open doors to more precise risk assessments and automated compliance controls, yet they also require robust model validation, audit trails, and explainability frameworks. Concurrently, talent dynamics and vendor consolidation reshape sourcing strategies, prompting finance leaders to balance in-house development with managed and professional services. This introduction sets the stage for deeper analysis by framing the primary vectors of change and the strategic choices that market participants face as they modernize analytics capabilities.
An authoritative overview of the strategic technology, commercial, and governance shifts that are redefining competitiveness and operational resilience in financial analytics
The industry is experiencing transformative shifts that extend across technology architecture, go-to-market models, and regulatory expectations. Cloud adoption continues to migrate workloads away from monolithic on-premises deployments toward scalable, modular solutions that enable faster feature delivery and lower time-to-insight. At the same time, demand for model transparency and robust governance has elevated the importance of traceable pipelines and explainable outputs, bridging the gap between advanced analytics and compliance teams.
Commercial models are also changing; organizations increasingly adopt managed services to accelerate deployments and reduce maintenance overhead while leveraging professional services for customization and change management. The rise of open-source frameworks and interoperable APIs has fostered a richer ecosystem of partners and niche specialists, enabling rapid assembly of tailored solutions. Geopolitical dynamics and supply chain pressures further encourage regional resilience strategies and selective nearshoring for critical infrastructure. Collectively, these shifts are making agility and operational reliability the primary differentiators among solution providers, and they demand integrated strategies that couple technical modernization with organizational change management.
A strategic assessment of how tariff actions through 2025 have reshaped procurement dynamics, vendor selection criteria, and infrastructure resilience strategies for analytics buyers
The cumulative impact of the United States tariff measures announced and implemented through 2025 has introduced layered effects across procurement, vendor strategies, and cost management for firms reliant on cross-border technology and hardware supply chains. Tariffs have elevated the direct cost of imported infrastructure components and certain categories of enterprise hardware, prompting procurement teams to re-evaluate sourcing, total cost of ownership, and vendor contractual terms. In several instances, finance and technology leaders have accelerated vendor diversification and explored alternative component suppliers to mitigate margin pressure and procurement latency.
Beyond direct cost implications, tariffs have influenced deployment timelines and capital planning, encouraging cloud-first models where feasible and spurring interest in managed services that internalize hardware risk. Regulatory compliance and reporting functions have experienced increased scrutiny as organizations reprice services and adjust vendor relationships, necessitating updated documentation and audit capabilities. Meanwhile, the macroeconomic signal of persistent trade friction has reinforced strategic priorities such as supply chain resilience, contract flexibility, and scenario-based financial planning. These cumulative effects have reshaped vendor selection criteria and internal procurement governance across institutions that depend on sophisticated analytics infrastructure.
A comprehensive segmentation synthesis that connects component, deployment, application, industry, size, and service dimensions to buyer priorities and product strategy implications
Segmentation analysis reveals distinct demand patterns across product, deployment, application, industry, organization size, and service dimensions, each carrying implications for go-to-market strategy and product roadmaps. Based on component, solutions split between Services and Software, with Services encompassing Managed Services and Professional Services; the Managed Services strand includes Support And Maintenance and Training And Education, while Professional Services is organized into Consulting and Implementation. This structure means that many buyers prioritize managed offerings to reduce operational burdens while still procuring consulting for bespoke implementations and change programs.
Based on deployment model, offerings are evaluated across Cloud and On Premises, with cloud models favored for scalability and rapid innovation, and on-premises retained where data residency, latency, or regulatory imperatives dominate. Based on application, adoption focuses on Accounting And Tax Management, Compliance Management, Fraud Detection And Prevention, Payment Processing, Portfolio Management, Risk Management, Trading And Investment Management, and Wealth Management; providers that demonstrate depth across multiple applications command broader enterprise interest because they can unify analytics and reduce fragmentation.
Based on end user industry, adoption patterns vary across BFSI, Government And Defense, Healthcare, IT And Telecommunications, and Retail And ECommerce, with each sector prioritizing different functional capabilities and data governance models. Based on organization size, Large Enterprises and Small And Medium Enterprises exhibit divergent buying cycles, customization needs, and tolerance for managed versus productized solutions. Finally, based on service type, the market differentiates between Managed Services and Professional Services, echoing the earlier component segmentation and underscoring the continued importance of support and implementation capabilities alongside strategic consulting. Together, these segmentation lenses highlight where product investment, partnership strategies, and service packaging will most effectively align with buyer needs.
A nuanced regional outlook that explains how Americas, Europe Middle East & Africa, and Asia-Pacific dynamics are shaping deployment choices, regulatory planning, and partner strategies
Regional dynamics continue to influence product design, compliance approaches, and market entry strategies in distinct ways across global clusters. In the Americas, buyers often emphasize speed of integration and scalable cloud services, driven by a dense ecosystem of fintechs, established financial institutions, and a regulatory environment that balances innovation with oversight. Investment priorities tend to favor analytics that accelerate time-to-insight and enable competitive differentiation in payments, wealth management, and risk analytics.
In Europe, Middle East & Africa, regulatory fragmentation and data residency concerns elevate the importance of modular architectures and strong compliance feature sets, while public sector demand in certain markets creates niches for tailored implementations. Local partnerships and regional data centers frequently serve as critical components of go-to-market plans. In Asia-Pacific, the combination of rapid digital adoption, diverse regulatory regimes, and large addressable customer bases encourages flexible deployment models and localized productizations. Across these regions, supply chain considerations and geopolitical tensions also shape vendor strategies, with regional resilience and local sourcing emerging as decisive factors in procurement and long-term contracts.
A practical examination of competitive behavior showing how capability breadth, specialist focus, partnerships, and services orchestration determine market leadership and differentiation
Competitive dynamics among leading companies reveal a pattern of capability expansion, strategic partnerships, and selective specialization. Market leaders tend to compete on breadth of application coverage, cloud-native capabilities, and the ability to offer managed services alongside core software. Many established vendors invest heavily in interoperability, API ecosystems, and prebuilt connectors to accelerate integration with client systems and third-party data providers. At the same time, a cohort of specialist providers focuses on high-value applications such as fraud detection or portfolio optimization, leveraging domain expertise and high-frequency data feeds to deliver differentiated outcomes.
Partnerships and alliances are common, enabling firms to combine machine learning prowess with domain-specific content or regulatory expertise. Professional services organizations that provide deep implementation and change management capabilities play a critical role in large-scale transformations, with many firms augmenting their offerings through acquisitions or strategic hires. Across the competitive landscape, success increasingly depends on the ability to demonstrate measurable business outcomes, maintain rigorous governance frameworks, and provide flexible commercial models that align with enterprise procurement cycles.
High-impact, pragmatic recommendations that align governance, sourcing, procurement, partnerships, and talent investments to accelerate value capture and reduce operational risk
Industry leaders should prioritize a set of actionable steps that align technology investments with regulatory readiness and commercial agility. First, accelerate modernization of data pipelines and model governance so that analytics outputs are auditable, explainable, and easily integrated into enterprise workflows. Doing so reduces operational risk and improves stakeholder trust, while enabling incremental rollouts that deliver value early in the transformation cycle. Second, rebalance sourcing strategies by combining cloud-native products with managed services for predictable operations, and reserve professional services for strategic implementations that require deep customization.
Third, strengthen procurement playbooks to incorporate scenario planning for trade and tariff disruptions, and embed contractual protections that enable supplier flexibility. Fourth, cultivate partnerships that expand application coverage and accelerate time-to-market; alliances with data providers, systems integrators, and niche specialists can create composite solutions that meet complex buyer requirements. Fifth, invest in talent and organizational change programs to close gaps in data engineering, model validation, and domain expertise so that tools translate into better decisions. Finally, commit to modular architectures and API-first design to future-proof platforms and make incremental innovation economically viable. By executing these recommendations, leaders can reduce risk, accelerate value capture, and maintain strategic optionality.
A transparent, reproducible research methodology combining practitioner interviews, technical validation, and curated secondary evidence to underpin robust conclusions and recommendations
This research synthesizes primary and secondary inputs using a structured methodology designed to ensure analytical rigor and reproducibility. Primary engagement included interviews with senior practitioners across financial institutions, technology vendors, systems integrators, and professional services firms to surface real-world challenges, deployment patterns, and procurement criteria. These qualitative inputs were complemented by technical validations with solution architects and data scientists to assess architecture choices and model governance practices.
Secondary research encompassed public regulatory documents, vendor product literature, technical whitepapers, and credible industry commentary to triangulate trends and corroborate themes that emerged in stakeholder interviews. Findings were validated through cross-functional review cycles to ensure consistency and to surface divergent viewpoints where present. The methodology emphasizes transparency in assumptions and traceable linkages between evidence and conclusion, enabling readers to understand how insights were derived and where further inquiry may be warranted. Together, these methods produce a balanced, pragmatic view intended to inform decision-making across commercial, technical, and regulatory dimensions.
A decisive synthesis underscoring the strategic necessity of governed modernization, modular architectures, and adaptive procurement to convert analytics into sustained enterprise outcomes
The concluding synthesis reiterates that financial analytics is no longer an isolated capability but a strategic foundation for competitive advantage, risk mitigation, and regulatory compliance. Effective programs combine modern data architectures with disciplined governance and a blended sourcing approach that leverages both managed and professional services. Organizations that invest in explainability, model lifecycle management, and integration into decision workflows will extract greater business value while reducing oversight risk.
Moreover, regional and geopolitical forces, including tariff dynamics and supply chain considerations, necessitate flexible procurement strategies and contingency planning. Providers that offer modular, API-first solutions and can demonstrate measurable outcomes will enjoy sustained demand. Ultimately, the path forward requires leaders to coordinate investments across people, processes, and technology, to prioritize initiatives that deliver early wins, and to maintain strategic optionality so that they can adapt as markets and regulations evolve. This conclusion underscores the imperative for decisive, well-governed modernization programs that translate analytics potential into tangible enterprise outcomes.
Note: PDF & Excel + Online Access - 1 Year
A forward-looking framing of how regulatory complexity, technological advances, and enterprise demand are reshaping financial analytics capabilities and priorities
The landscape for financial analytics solutions has entered a period of accelerated transformation driven by converging regulatory, technological, and commercial forces. As capital markets, payment systems, and institutional risk functions evolve, analytics platforms are increasingly judged not only by accuracy but by speed, interpretability, and adaptability. Organizations now expect analytics to be embedded in decision workflows rather than operating as standalone tools, which raises new expectations for integration, security, and governance.
Against this backdrop, executives must reconcile legacy infrastructure with the demand for cloud-native capabilities and real-time insights. Advances in machine learning and data engineering open doors to more precise risk assessments and automated compliance controls, yet they also require robust model validation, audit trails, and explainability frameworks. Concurrently, talent dynamics and vendor consolidation reshape sourcing strategies, prompting finance leaders to balance in-house development with managed and professional services. This introduction sets the stage for deeper analysis by framing the primary vectors of change and the strategic choices that market participants face as they modernize analytics capabilities.
An authoritative overview of the strategic technology, commercial, and governance shifts that are redefining competitiveness and operational resilience in financial analytics
The industry is experiencing transformative shifts that extend across technology architecture, go-to-market models, and regulatory expectations. Cloud adoption continues to migrate workloads away from monolithic on-premises deployments toward scalable, modular solutions that enable faster feature delivery and lower time-to-insight. At the same time, demand for model transparency and robust governance has elevated the importance of traceable pipelines and explainable outputs, bridging the gap between advanced analytics and compliance teams.
Commercial models are also changing; organizations increasingly adopt managed services to accelerate deployments and reduce maintenance overhead while leveraging professional services for customization and change management. The rise of open-source frameworks and interoperable APIs has fostered a richer ecosystem of partners and niche specialists, enabling rapid assembly of tailored solutions. Geopolitical dynamics and supply chain pressures further encourage regional resilience strategies and selective nearshoring for critical infrastructure. Collectively, these shifts are making agility and operational reliability the primary differentiators among solution providers, and they demand integrated strategies that couple technical modernization with organizational change management.
A strategic assessment of how tariff actions through 2025 have reshaped procurement dynamics, vendor selection criteria, and infrastructure resilience strategies for analytics buyers
The cumulative impact of the United States tariff measures announced and implemented through 2025 has introduced layered effects across procurement, vendor strategies, and cost management for firms reliant on cross-border technology and hardware supply chains. Tariffs have elevated the direct cost of imported infrastructure components and certain categories of enterprise hardware, prompting procurement teams to re-evaluate sourcing, total cost of ownership, and vendor contractual terms. In several instances, finance and technology leaders have accelerated vendor diversification and explored alternative component suppliers to mitigate margin pressure and procurement latency.
Beyond direct cost implications, tariffs have influenced deployment timelines and capital planning, encouraging cloud-first models where feasible and spurring interest in managed services that internalize hardware risk. Regulatory compliance and reporting functions have experienced increased scrutiny as organizations reprice services and adjust vendor relationships, necessitating updated documentation and audit capabilities. Meanwhile, the macroeconomic signal of persistent trade friction has reinforced strategic priorities such as supply chain resilience, contract flexibility, and scenario-based financial planning. These cumulative effects have reshaped vendor selection criteria and internal procurement governance across institutions that depend on sophisticated analytics infrastructure.
A comprehensive segmentation synthesis that connects component, deployment, application, industry, size, and service dimensions to buyer priorities and product strategy implications
Segmentation analysis reveals distinct demand patterns across product, deployment, application, industry, organization size, and service dimensions, each carrying implications for go-to-market strategy and product roadmaps. Based on component, solutions split between Services and Software, with Services encompassing Managed Services and Professional Services; the Managed Services strand includes Support And Maintenance and Training And Education, while Professional Services is organized into Consulting and Implementation. This structure means that many buyers prioritize managed offerings to reduce operational burdens while still procuring consulting for bespoke implementations and change programs.
Based on deployment model, offerings are evaluated across Cloud and On Premises, with cloud models favored for scalability and rapid innovation, and on-premises retained where data residency, latency, or regulatory imperatives dominate. Based on application, adoption focuses on Accounting And Tax Management, Compliance Management, Fraud Detection And Prevention, Payment Processing, Portfolio Management, Risk Management, Trading And Investment Management, and Wealth Management; providers that demonstrate depth across multiple applications command broader enterprise interest because they can unify analytics and reduce fragmentation.
Based on end user industry, adoption patterns vary across BFSI, Government And Defense, Healthcare, IT And Telecommunications, and Retail And ECommerce, with each sector prioritizing different functional capabilities and data governance models. Based on organization size, Large Enterprises and Small And Medium Enterprises exhibit divergent buying cycles, customization needs, and tolerance for managed versus productized solutions. Finally, based on service type, the market differentiates between Managed Services and Professional Services, echoing the earlier component segmentation and underscoring the continued importance of support and implementation capabilities alongside strategic consulting. Together, these segmentation lenses highlight where product investment, partnership strategies, and service packaging will most effectively align with buyer needs.
A nuanced regional outlook that explains how Americas, Europe Middle East & Africa, and Asia-Pacific dynamics are shaping deployment choices, regulatory planning, and partner strategies
Regional dynamics continue to influence product design, compliance approaches, and market entry strategies in distinct ways across global clusters. In the Americas, buyers often emphasize speed of integration and scalable cloud services, driven by a dense ecosystem of fintechs, established financial institutions, and a regulatory environment that balances innovation with oversight. Investment priorities tend to favor analytics that accelerate time-to-insight and enable competitive differentiation in payments, wealth management, and risk analytics.
In Europe, Middle East & Africa, regulatory fragmentation and data residency concerns elevate the importance of modular architectures and strong compliance feature sets, while public sector demand in certain markets creates niches for tailored implementations. Local partnerships and regional data centers frequently serve as critical components of go-to-market plans. In Asia-Pacific, the combination of rapid digital adoption, diverse regulatory regimes, and large addressable customer bases encourages flexible deployment models and localized productizations. Across these regions, supply chain considerations and geopolitical tensions also shape vendor strategies, with regional resilience and local sourcing emerging as decisive factors in procurement and long-term contracts.
A practical examination of competitive behavior showing how capability breadth, specialist focus, partnerships, and services orchestration determine market leadership and differentiation
Competitive dynamics among leading companies reveal a pattern of capability expansion, strategic partnerships, and selective specialization. Market leaders tend to compete on breadth of application coverage, cloud-native capabilities, and the ability to offer managed services alongside core software. Many established vendors invest heavily in interoperability, API ecosystems, and prebuilt connectors to accelerate integration with client systems and third-party data providers. At the same time, a cohort of specialist providers focuses on high-value applications such as fraud detection or portfolio optimization, leveraging domain expertise and high-frequency data feeds to deliver differentiated outcomes.
Partnerships and alliances are common, enabling firms to combine machine learning prowess with domain-specific content or regulatory expertise. Professional services organizations that provide deep implementation and change management capabilities play a critical role in large-scale transformations, with many firms augmenting their offerings through acquisitions or strategic hires. Across the competitive landscape, success increasingly depends on the ability to demonstrate measurable business outcomes, maintain rigorous governance frameworks, and provide flexible commercial models that align with enterprise procurement cycles.
High-impact, pragmatic recommendations that align governance, sourcing, procurement, partnerships, and talent investments to accelerate value capture and reduce operational risk
Industry leaders should prioritize a set of actionable steps that align technology investments with regulatory readiness and commercial agility. First, accelerate modernization of data pipelines and model governance so that analytics outputs are auditable, explainable, and easily integrated into enterprise workflows. Doing so reduces operational risk and improves stakeholder trust, while enabling incremental rollouts that deliver value early in the transformation cycle. Second, rebalance sourcing strategies by combining cloud-native products with managed services for predictable operations, and reserve professional services for strategic implementations that require deep customization.
Third, strengthen procurement playbooks to incorporate scenario planning for trade and tariff disruptions, and embed contractual protections that enable supplier flexibility. Fourth, cultivate partnerships that expand application coverage and accelerate time-to-market; alliances with data providers, systems integrators, and niche specialists can create composite solutions that meet complex buyer requirements. Fifth, invest in talent and organizational change programs to close gaps in data engineering, model validation, and domain expertise so that tools translate into better decisions. Finally, commit to modular architectures and API-first design to future-proof platforms and make incremental innovation economically viable. By executing these recommendations, leaders can reduce risk, accelerate value capture, and maintain strategic optionality.
A transparent, reproducible research methodology combining practitioner interviews, technical validation, and curated secondary evidence to underpin robust conclusions and recommendations
This research synthesizes primary and secondary inputs using a structured methodology designed to ensure analytical rigor and reproducibility. Primary engagement included interviews with senior practitioners across financial institutions, technology vendors, systems integrators, and professional services firms to surface real-world challenges, deployment patterns, and procurement criteria. These qualitative inputs were complemented by technical validations with solution architects and data scientists to assess architecture choices and model governance practices.
Secondary research encompassed public regulatory documents, vendor product literature, technical whitepapers, and credible industry commentary to triangulate trends and corroborate themes that emerged in stakeholder interviews. Findings were validated through cross-functional review cycles to ensure consistency and to surface divergent viewpoints where present. The methodology emphasizes transparency in assumptions and traceable linkages between evidence and conclusion, enabling readers to understand how insights were derived and where further inquiry may be warranted. Together, these methods produce a balanced, pragmatic view intended to inform decision-making across commercial, technical, and regulatory dimensions.
A decisive synthesis underscoring the strategic necessity of governed modernization, modular architectures, and adaptive procurement to convert analytics into sustained enterprise outcomes
The concluding synthesis reiterates that financial analytics is no longer an isolated capability but a strategic foundation for competitive advantage, risk mitigation, and regulatory compliance. Effective programs combine modern data architectures with disciplined governance and a blended sourcing approach that leverages both managed and professional services. Organizations that invest in explainability, model lifecycle management, and integration into decision workflows will extract greater business value while reducing oversight risk.
Moreover, regional and geopolitical forces, including tariff dynamics and supply chain considerations, necessitate flexible procurement strategies and contingency planning. Providers that offer modular, API-first solutions and can demonstrate measurable outcomes will enjoy sustained demand. Ultimately, the path forward requires leaders to coordinate investments across people, processes, and technology, to prioritize initiatives that deliver early wins, and to maintain strategic optionality so that they can adapt as markets and regulations evolve. This conclusion underscores the imperative for decisive, well-governed modernization programs that translate analytics potential into tangible enterprise outcomes.
Note: PDF & Excel + Online Access - 1 Year
Table of Contents
190 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Implementing machine learning driven ESG scoring models to quantify environmental and social risks in investment portfolios
- 5.2. Adoption of real-time alternative data streams such as satellite imagery and social media sentiment for equity price forecasting
- 5.3. Integration of generative AI driven scenario analysis tools for dynamic bond portfolio stress testing and risk management
- 5.4. Utilizing blockchain enabled transaction analytics to enhance transparency and efficiency in cross border payments infrastructure
- 5.5. Piloting quantum computing algorithms for optimization of multi asset portfolios and complex derivatives pricing strategies
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Financial Analytics Market, by Component
- 8.1. Services
- 8.1.1. Managed Services
- 8.1.1.1. Support & Maintenance
- 8.1.1.2. Training & Education
- 8.1.2. Professional Services
- 8.1.2.1. Consulting
- 8.1.2.2. Implementation
- 8.2. Software
- 9. Financial Analytics Market, by Service Type
- 9.1. Managed Services
- 9.1.1. Support & Maintenance
- 9.1.2. Training & Education
- 9.2. Professional Services
- 9.2.1. Consulting
- 9.2.2. Implementation
- 10. Financial Analytics Market, by Application
- 10.1. Accounting & Tax Management
- 10.2. Compliance Management
- 10.3. Fraud Detection And Prevention
- 10.4. Payment Processing
- 10.5. Portfolio Management
- 10.6. Risk Management
- 10.7. Trading & Investment Management
- 10.8. Wealth Management
- 11. Financial Analytics Market, by End User Industry
- 11.1. BFSI
- 11.2. Government & Defense
- 11.3. Healthcare
- 11.4. IT & Telecommunications
- 11.5. Retail & ECommerce
- 12. Financial Analytics Market, by Deployment Model
- 12.1. Cloud
- 12.2. On Premises
- 13. Financial Analytics Market, by Region
- 13.1. Americas
- 13.1.1. North America
- 13.1.2. Latin America
- 13.2. Europe, Middle East & Africa
- 13.2.1. Europe
- 13.2.2. Middle East
- 13.2.3. Africa
- 13.3. Asia-Pacific
- 14. Financial Analytics Market, by Group
- 14.1. ASEAN
- 14.2. GCC
- 14.3. European Union
- 14.4. BRICS
- 14.5. G7
- 14.6. NATO
- 15. Financial Analytics Market, by Country
- 15.1. United States
- 15.2. Canada
- 15.3. Mexico
- 15.4. Brazil
- 15.5. United Kingdom
- 15.6. Germany
- 15.7. France
- 15.8. Russia
- 15.9. Italy
- 15.10. Spain
- 15.11. China
- 15.12. India
- 15.13. Japan
- 15.14. Australia
- 15.15. South Korea
- 16. Competitive Landscape
- 16.1. Market Share Analysis, 2024
- 16.2. FPNV Positioning Matrix, 2024
- 16.3. Competitive Analysis
- 16.3.1. SAP SE
- 16.3.2. Oracle Corporation
- 16.3.3. International Business Machines Corporation
- 16.3.4. Microsoft Corporation
- 16.3.5. SAS Institute Inc.
- 16.3.6. S&P Global Inc.
- 16.3.7. Moody’s Analytics, Inc.
- 16.3.8. Bloomberg L.P.
- 16.3.9. Refinitiv Limited
- 16.3.10. FactSet Research Systems Inc.
- 16.3.11. Workday, Inc.
- 16.3.12. Anaplan, Inc.
- 16.3.13. Fair Isaac Corporation
- 16.3.14. Teradata Corporation
- 16.3.15. Thomson Reuters Corporation
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