[Keywords] Market include Qlik, Wolters Kluver, H.I.G. Capital, Datasift, TransUnion

Market Analysis of Internet Financial Data Terminal Services The global market for Internet financial data terminal services is projected to reach a valuation of XXX million by 2033, expanding at a CAGR of XX%. The surge in demand for real-time financial data, the proliferation of online trading platforms, and the growing adoption of cloud-based solutions drive market growth. The segment of institutional investors holds a dominant market share due to their need for comprehensive data for investment decision-making. Mobile versions of financial data terminals are gaining traction, providing investors with access to market information on the go. Key trends shaping the market include the integration of artificial intelligence (AI) for data analysis and visualization, the increasing adoption of open-source platforms, and the growing focus on data security. Major players in the market include Bloomberg, Refinitiv, FactSet, S&P, and Moody's Analytics. The Asia-Pacific region is expected to experience the fastest growth due to the rapid expansion of the financial industry in emerging economies like China and India. However, stringent data privacy regulations and competition from free data sources pose challenges to market players.

The Business Information Services market is experiencing robust growth, driven by the increasing need for data-driven decision-making across various industries. The market, estimated at $500 billion in 2025, is projected to maintain a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching approximately $850 billion by 2033. This expansion is fueled by several key factors, including the rising adoption of cloud-based solutions, the proliferation of big data analytics, and the growing demand for real-time insights. Major players like Bloomberg, Dow Jones, and Thomson Reuters are leveraging advanced technologies like artificial intelligence and machine learning to enhance their offerings and cater to the evolving needs of their clientele. Furthermore, the increasing focus on regulatory compliance across sectors is boosting the demand for comprehensive and reliable business information services. Segmentation within the market includes financial information, market research, credit information, and legal information, each contributing to the overall growth trajectory. However, the market faces certain challenges. Data security concerns and the rising costs associated with data acquisition and maintenance present hurdles for both providers and consumers. Competition is fierce, with established players constantly innovating to maintain their market share and new entrants striving to carve out a niche. The varying regulatory landscapes across different regions also influence market dynamics. Despite these challenges, the long-term outlook for the Business Information Services market remains positive, driven by the continued digital transformation across industries and the ever-increasing reliance on data for strategic decision-making. The market's expansion will likely be propelled by the growing adoption of subscription-based models and the increasing integration of business information services with other enterprise software solutions.

Baltic Dry rose to 1,663 Index Points on July 11, 2025, up 13.52% from the previous day. Over the past month, Baltic Dry's price has fallen 15.50%, and is down 16.73% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Baltic Exchange Dry Index - values, historical data, forecasts and news - updated on July of 2025.

The global financial data terminal services market is projected to grow significantly, reaching a market size of approximately XXX million by 2033. This growth is driven by increasing demand for real-time and comprehensive financial data analysis and decision-making tools among institutional investors and individual traders. The market is witnessing rapid technological advancements, such as the integration of AI and machine learning, which enhances data processing and analysis capabilities. The growing popularity of mobile versions of financial data terminals and the expansion of financial services in emerging markets are further contributing to market growth. The competitive landscape of the financial data terminal services market is dominated by established players such as Bloomberg, Refinitiv, FactSet, S&P, and Moody's Analytics. These companies offer a comprehensive suite of data, analytics, and visualization tools tailored to the specific needs of financial professionals. Regional markets are also witnessing the emergence of local players, such as Hithink Flush Information Network, East Money Information, and Wind, catering to the unique requirements of local investors. The market is characterized by ongoing innovation and collaboration, with players partnering with data providers, technology vendors, and financial institutions to deliver cutting-edge solutions and enhance customer experience.

The Data as a Service (DaaS) market is experiencing robust growth, projected to reach $20.74 billion in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 20%. This expansion is fueled by several key drivers. The increasing adoption of cloud computing and big data analytics across diverse sectors like BFSI, IT & Telecommunications, and Government is creating a surge in demand for readily available, high-quality data. Businesses are increasingly recognizing the value of leveraging external data sources to enhance decision-making, improve operational efficiency, and gain a competitive edge. Furthermore, the rising need for real-time data insights and the simplification of data access through DaaS platforms are contributing significantly to market growth. Technological advancements, such as improved data security measures and the development of more sophisticated data management tools, are also facilitating wider DaaS adoption. While data privacy regulations and concerns about data quality present potential restraints, the overall market outlook remains extremely positive. The significant investments made by major players like Bloomberg, IBM, and Oracle demonstrate the long-term viability and considerable potential of this market segment. The regional distribution of the DaaS market likely reflects global technological adoption patterns. North America and Europe, with their advanced digital infrastructure and robust regulatory frameworks, are expected to hold substantial market shares. However, the Asia-Pacific region, experiencing rapid digital transformation across numerous industries, is poised for significant growth in DaaS adoption, driven by increasing smartphone penetration and the rise of e-commerce. Emerging economies in Latin America and the Middle East and Africa also present considerable untapped potential for DaaS expansion. The forecast period of 2025-2033 will likely see continued market consolidation, with larger players strategically acquiring smaller companies to enhance their data offerings and expand their global reach. Further specialization within DaaS, catering to niche industry needs, is also anticipated. Recent developments include: September 2022: Asigra Inc., an ultra-secure backup and recovery pioneer, declared the general availability of Tigris Data Protection software with Content Disarm & Reconstruction (CDR). The addition of CDR makes Asigra the most security-forward backup and recovery software platform available, adding to its extensive suite of security features., June 2022: IMAT Solutions, a real-time healthcare data management and population health reporting solutions provider, announced the launch of a new Data-as-a-Service (DaaS) offering for health payers. The new DaaS solution meets the new Centers for Medicare & Medicaid Services (CMS) effort to transition all quality measures used in its reporting programs to digital quality measures (dQMs).. Key drivers for this market are: Growing Penetration of Data-based Decisions Among Enterprises, Transformation of Enterprises Leading to Real-time Analytics Demand. Potential restraints include: Growing Penetration of Data-based Decisions Among Enterprises, Transformation of Enterprises Leading to Real-time Analytics Demand. Notable trends are: BFSI Sector to Witness High Growth.

The global financial data terminal services market is anticipated to grow at a CAGR of XX% during the forecast period of 2025-2033. The market is set to reach a value of XXX million by 2033, up from XXX million in 2025. The rising demand for real-time financial data and the increasing adoption of cloud-based services are the primary drivers of the market's growth. Additionally, the growing need for data analytics and visualization tools to make informed investment decisions is further bolstering the market's expansion. The market is segmented based on application, including institutional investors and individual investors. In terms of types, the market is divided into mobile versions and PC versions. The key players operating in the market include Bloomberg, Refinitiv, FactSet, S&P, Moody's Analytics, ICE Data Services, Wind, Hithink Flush Information Network, East Money Information, Shanghai DZH, Beijing Compass Technology, Hundsun, and Shenzhen Fortune Trend. Geographically, North America holds a significant share of the market, followed by Europe and Asia-Pacific. The increasing adoption of advanced financial data terminal services by financial institutions and the growing number of individual investors in these regions are contributing to the market's growth.

South African monthly The FTSE/JSE All Share Index data was procured from Bloomberg and the nominal effective exchange rate (NEER) from South African Reserve Bank (SARB) database, where the data has been seasonally adjusted specifying 2015 as the base year. Volatility measures in these markets are generated through a multivaraite EGARCH model in the WinRATS software. South African monthly consumer price index (CPI) data was procured from the International Monetary Fund’s International Financial Statistics (IFS) database, where the data has been seasonally adjusted, specifying 2010 as the base year. The inflation rate is constructed by taking the year-on-year changes in the monthly CPI figures. Inflation uncertainty was generated through the GARCH model in Eviews software. The following South African macroeconomic variables were procured from the SARB: real industrial production (IP), which is used as a proxy for real GDP, real investment (I), real consumption (C), inflation (CPI), broad money (M3), the 3-month treasury bill rate (TB3) and the policy rate (R), a measure of U.S. EPU developed by Baker et al. (2016) to account for global developments available at http://www.policyuncertainty.com/us_monthly.html.

Graph and download economic data for Trade Weighted U.S. Dollar Index: Broad, Goods (DISCONTINUED) (TWEXB) from 1995-01-04 to 2020-01-01 about trade-weighted, broad, exchange rate, currency, goods, rate, indexes, and USA.

According to Cognitive Market Research, the global Financial Data Service market size will be USD 24152.5 million in 2024. It will expand at a compound annual growth rate (CAGR) of 8.50% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 9661.00 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.7% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 7245.75 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 5555.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.5% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 1207.63 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.9% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 483.05 million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.2% from 2024 to 2031.
Datafeed/API solutions are the dominant segment, as they allow seamless data integration into existing systems and platforms, making them ideal for companies requiring real-time data across multiple applications

Market Dynamics of Financial Data Service Market

Key Drivers for Financial Data Service Market

Increased Data-Driven Decision-Making to Boost Market Growth

As digital transformation sweeps through financial services, data-driven decision-making has become essential for businesses to remain competitive. Institutions, both financial and non-financial, are increasingly leveraging financial data to guide strategic investments, manage risks, and streamline operations. By utilizing real-time data and predictive analytics, companies gain actionable insights to optimize their investment portfolios and financial planning. With the enhanced capability to analyze data trends and assess market scenarios, businesses can mitigate risks more effectively, making this driver critical to the growth of the financial data service market. For instance, in September 2022, Alibaba Cloud, the digital technology and intellectual backbone of Alibaba Group, launched a comprehensive suite of Alibaba Cloud for Financial Services solutions. Comprising over 70 products, these solutions are designed to help financial services institutions of all sizes across banking, FinTech, insurance, and securities, digitalize their operations

Advancements in Analytics Technology to Drive Market Growth

The integration of advanced analytics technologies like artificial intelligence (AI) and machine learning (ML) in financial data services has significantly enhanced the accuracy and scope of market insights. AI and ML enable companies to process vast amounts of financial data, identify patterns, and make predictions, thus facilitating strategic planning and investment optimization. These technologies also allow for real-time insights, giving firms a competitive advantage in rapidly evolving markets. With continuous improvements in AI and ML, the demand for advanced data services is expected to grow, positioning this as a key driver of market expansion.

Restraint Factor for the Financial Data Service Market

High Cost of Data Services Will Limit Market Growth

The high cost of premium financial data services is a significant restraint, particularly for small and medium-sized enterprises (SMEs). Many advanced platforms and data feeds come with substantial subscription fees, limiting their accessibility to larger organizations with more considerable budgets. This cost barrier restricts smaller firms from fully integrating advanced data insights into their operations. As a result, high subscription costs prevent widespread adoption among SMEs, hindering the financial data service market’s overall growth potential.

Trends for the Financial Data Service Market

Blockchain-based Data Services as an opportunity for the market

Blockchain-based data services offer a secure, transparent, and decentralized approach to financial data management. By leveraging blockchain technology, finance data services can provide tamper-proof and auditable data storage, ensuring the integrity and accuracy of financial data. This can help...

Explore LSEG's extensive deals data catalogue, and find world leading investment banking transaction data for M&A and New Issues.

Given the contradictory empirical evidence on the relationship between green R&D expenditure and corporate Green Innovation performance (GIP), The present research study is a distinctive investigation into the moderating impacts of ESG reporting on this relationship. We utilized a data collection of 3,846, firm-year observations of A-share listed firms in China from 2016 to 2022 from CSMAR and Bloomberg databases. The firm’s Corporate GIP is assessed and measured by looking at the total quantity of green patents. Lastly, models with multiple regression analyses and fixed effects were employed. The findings show that ESG reporting has a positive and significant impact on the association between corporate GIP and green R&D expenditure, implying its compensating and supportive function in the form of green signals in green outputs. This research could help executives and lawmakers, especially in developing countries to build innovative environmental strategies for business sustainability.

This dataset is used in Master thesis on topic "The impact of upholding environmental, social and governance principles on the market value of capital-intensive companies". The full dataset consits data on Public american companies included in S&P 500 index, traded on the New York Stock Exchange. There are data on ESG-score and its components (E, S, G), as well as components of Envitonmental pillar score. Additionaly dataset includes financial data, like market capitalization, leverage, ROCE, Capex and etc. The main sources of data are Thomson Reuters Eikon and Bloomberg terminals, along with Form 10-k by SEC. The final sample consists of 52 capital-intensive companies, time horizon: 2012-2021 [520 observations in total].

Graph and download economic data for CBOE Emerging Markets ETF Volatility Index (VXEEMCLS) from 2011-03-16 to 2025-07-10 about ETF, VIX, emerging markets, volatility, stock market, and USA.

GIP and green R&D investment impacts on ESG reporting (panel data analysis with fixed effects).

This dataset is used in Master thesis on topic "The impact of upholding environmental, social and governance principles on the market value of capital-intensive companies". The full dataset consits data on Public american companies included in S&P 500 index, traded on the New York Stock Exchange. There are data on ESG-score and its components (E, S, G), as well as components of Envitonmental pillar score. Additionaly dataset includes financial data, like market capitalization, leverage, ROCE, Capex and etc. The main sources of data are Thomson Reuters Eikon and Bloomberg terminals, along with Form 10-k by SEC. The final sample consists of 52 capital-intensive companies, time horizon: 2012-2021 [520 observations in total].

Using all stocks listed in the Tokyo Stock Exchange and macroeconomic data for Japan, the dataset comprises the following series:

1. Japan_25_Portfolios_MV_PTBV: Monthly returns for 25 size-book-to-market equity portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
2. Japan_25_Portfolios_MV_PE: Monthly returns for 25 size-PE portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
3. Japan_50_Portfolios_SECTOR: Monthly returns for 50 industry portfolios. (Raw data source: Datastream database)
4. Japan_3 Factors: Fama and French three-factors (RM, SMB and HML), following the Fama and French (1993) methodology. (Raw data source: Datastream database)
5. Japan_5 Factors: Fama and French five-factors (RM, SMB, HML, RMW, and CMA), following the Fama and French (2015) methodology. (Raw data source: Datastream database)
6. Japan_NUCLEAR_Y: Instrument in years with a value of 1 when a nuclear disaster has occurred somewhere in the world and 0 otherwise. (Raw data source: Bloomberg and BBC News)
7. Japan_NUCLEAR_M: Instrument in months with a value of 1 when a nuclear disaster has occurred somewhere in the world and 0 otherwise. (Raw data source: Bloomberg and BBC News)
8. Japan_RF_M: Three-month interest rate of the Treasury Bill for Japan. (Raw data source: OECD)
9. Company data: Names and general data of the companies that constitute the sample. (Raw data source: Datastream database)
10. Number of stocks in portfolios: Number of stocks included each year in Japan_25_Portfolios_MV_PTBV, Japan_25_Portfolios_MV_PE and Japan_50_Portfolios_SECTOR. (Raw data source: Datastream database)

We have produced all return series using the following data from Datastream: (i) total return index (RI series), (ii) market value (MV series), (iii) market-to-book equity (PTBV series), (iv) total assets (WC02999 series), (v) return on equity (WC08301 series), (vi) price-to-earnings ratio (PE series), and (vii) industry (SECTOR series). We have used the generic rules suggested by Griffin, Kelly, & Nardari (2010) for excluding non-common equity securities from Datastream data. We also exclude stocks with less than twelve observations. Accordingly, our sample comprises a total number of 5,212 stocks.

REFERENCES:

Fama, E. F. and French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3–56. Fama, E. F. and French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116, 1–22. Griffin, J. M., Kelly, P., and Nardari, F. (2010). Do market efficiency measures yield correct inferences? A comparison of developed and emerging markets. Review of Financial Studies, 23, 3225–3277.

Explore the dynamic factors influencing copper prices, including global demand and supply, major consumer economies, mining operations, technological advancements in sustainable energy, and geopolitical stability. Understand how these elements affect market fluctuations and gain insights from sources like the London Metal Exchange and Bloomberg for real-time data and analysis.

Graph and download economic data for AMERIBOR Term-30 Derived Interest Rate Index (AMBOR30T) from 2021-03-15 to 2025-07-13 about AMERIBOR, 1-month, interest rate, interest, rate, indexes, and USA.

Explore the dynamics of the London Metal Exchange copper market, its influence on global economic health, and how to access live data with platforms like Bloomberg and Reuters.