Financial Times Interactive Data LLC offers a vast repository of economic and financial data, providing valuable insights into global markets and trading. With a focus on delivering timely and accurate information, the company has established itself as a go-to source for financial institutions, investors, and researchers seeking to stay ahead of the curve.

our vast database is comprised of historic financial statements, economic indicators, and proprietary data from leading sources, including government agencies, regulatory bodies, and industry associations. By providing access to this trove of information, Financial Times Interactive Data LLC enables its clients to make informed decisions, identify trends, and uncover new opportunities in the rapidly evolving world of finance.

Success.ai offers a cutting-edge solution for businesses and organizations seeking Company Financial Data on private and public companies. Our comprehensive database is meticulously crafted to provide verified profiles, including contact details for financial decision-makers such as CFOs, financial analysts, corporate treasurers, and other key stakeholders. This robust dataset is continuously updated and validated using AI technology to ensure accuracy and relevance, empowering businesses to make informed decisions and optimize their financial strategies.

Key Features of Success.ai's Company Financial Data:

Global Coverage: Access data from over 70 million businesses worldwide, including public and private companies across all major industries and regions. Our datasets span 250+ countries, offering extensive reach for your financial analysis and market research.

Detailed Financial Profiles: Gain insights into company financials, including revenue, profit margins, funding rounds, and operational costs. Profiles are enriched with key contact details, including work emails, phone numbers, and physical addresses, ensuring direct access to decision-makers.

Industry-Specific Data: Tailored datasets for sectors such as financial services, manufacturing, technology, healthcare, and energy, among others. Each dataset is customized to meet the unique needs of industry professionals and analysts.

Real-Time Accuracy: With continuous updates powered by AI-driven validation, our financial data maintains a 99% accuracy rate, ensuring you have access to the most reliable and up-to-date information available.

Compliance and Security: All data is collected and processed in strict adherence to global compliance standards, including GDPR, ensuring ethical and lawful usage.

Why Choose Success.ai for Company Financial Data?

Best Price Guarantee: We pride ourselves on offering the most competitive pricing in the industry, ensuring you receive unparalleled value for comprehensive financial data.

AI-Validated Accuracy: Our advanced AI algorithms meticulously verify every data point to ensure precision and reliability, helping you avoid costly errors in your financial decision-making.

Customized Data Solutions: Whether you need data for a specific region, industry, or type of business, we tailor our datasets to align perfectly with your requirements.

Scalable Data Access: From small startups to global enterprises, our platform caters to businesses of all sizes, delivering scalable solutions to suit your operational needs.

Comprehensive Use Cases for Financial Data:

1. Strategic Financial Planning:

Leverage our detailed financial profiles to create accurate budgets, forecasts, and strategic plans. Gain insights into competitors’ financial health and market positions to make data-driven decisions.

1. Mergers and Acquisitions (M&A):

Access key financial details and contact information to streamline your M&A processes. Identify potential acquisition targets or partners with verified profiles and financial data.

1. Investment Analysis:

Evaluate the financial performance of public and private companies for informed investment decisions. Use our data to identify growth opportunities and assess risk factors.

1. Lead Generation and Sales:

Enhance your sales outreach by targeting CFOs, financial analysts, and other decision-makers with verified contact details. Utilize accurate email and phone data to increase conversion rates.

1. Market Research:

Understand market trends and financial benchmarks with our industry-specific datasets. Use the data for competitive analysis, benchmarking, and identifying market gaps.

APIs to Power Your Financial Strategies:

Enrichment API: Integrate real-time updates into your systems with our Enrichment API. Keep your financial data accurate and current to drive dynamic decision-making and maintain a competitive edge.

Lead Generation API: Supercharge your lead generation efforts with access to verified contact details for key financial decision-makers. Perfect for personalized outreach and targeted campaigns.

Tailored Solutions for Industry Professionals:

Financial Services Firms: Gain detailed insights into revenue streams, funding rounds, and operational costs for competitor analysis and client acquisition.

Corporate Finance Teams: Enhance decision-making with precise data on industry trends and benchmarks.

Consulting Firms: Deliver informed recommendations to clients with access to detailed financial datasets and key stakeholder profiles.

Investment Firms: Identify potential investment opportunities with verified data on financial performance and market positioning.

What Sets Success.ai Apart?

Extensive Database: Access detailed financial data for 70M+ companies worldwide, including small businesses, startups, and large corporations.

Ethical Practices: Our data collection and processing methods are fully comp...

Francis Financial is a reputable financial services company that provides a range of products and services to its clients. The company's data holdings are vast and varied, encompassing financial market data, economic trends, and industry insights. With a strong focus on serving its clients' needs, Francis Financial's data repository is a treasure trove of valuable information for anyone looking to gain a deeper understanding of the financial world.

From company reports and financial statements to market analysis and industry news, Francis Financial's data collection is a comprehensive archive of important financial information. By leveraging this data, users can gain valuable insights into market trends, spot emerging patterns, and make informed decisions. With its extensive data holdings and commitment to providing high-quality information, Francis Financial is an important player in the financial data landscape.

Financial Data Services Market size was valued at USD 23.3 Billion in 2023 and is projected to reach USD 42.6 Billion by 2031, growing at a CAGR of 8.1% during the forecast period 2024-2031.Global Financial Data Services Market DriversThe market drivers for the Financial Data Services Market can be influenced by various factors. These may include:The need for real-time analytics is growing: Real-time analytics are becoming more and more necessary in the financial sector due to the acceleration of data consumption. To reduce risks, make wise decisions, and enhance customer service, organizations need quick insights. Stakeholders are giving priority to solutions that enable quick data processing and analysis due to the increase in market volatility and complexity. The need for sophisticated analytical skills is driving providers of financial data services to modernize their products. As companies come to realize that using real-time data is crucial for keeping a competitive edge in a fast-paced financial climate, the competition among them to provide timely insights also boosts market growth.Growing Machine Learning and AI Adoption: Data analysis has been profoundly changed by the incorporation of AI and machine learning technology into financial data services. By enabling predictive analytics, these technologies help financial organizations make better decisions and reduce risk. Businesses can find trends that were previously invisible by automating data processing operations. This leads to more precise forecasts and improved investment plans. Furthermore, sophisticated algorithms are flexible enough to adjust to shifting circumstances, keeping organizations flexible. The increasing intricacy of financial markets necessitates the use of AI and machine learning, which in turn drives demand for sophisticated financial data services and promotes innovation in the sector.Global Financial Data Services Market RestraintsSeveral factors can act as restraints or challenges for the Financial Data Services Market. These may include:Difficulties in Regulatory Compliance: Regulations controlling data management, privacy, and financial transactions place heavy restrictions on the financial data services market. Regulations like the GDPR, CCPA, and banking industry standards like Basel III and SOX must all be complied with by organizations. Complying with these requirements frequently necessitates a significant investment in staff and compliance systems, which can be taxing, especially for smaller businesses. Regulations are dynamic, and different locations have different needs, which adds to the complexity and expense. Noncompliance not only results in monetary fines but also has the potential to harm an entity's image, so impeding market expansion.Dangers to Data Security: Threats to data security are a major impediment to the financial data services market. Because they manage sensitive data, financial institutions are often the targets of cyberattacks. Breach can lead to significant monetary losses, legal repercussions, and long-term harm to one's image. Although they can greatly increase operating expenses, investments in strong security measures like encryption, safe access protocols, and continual monitoring are crucial. Moreover, the dynamic strategies employed by cybercriminals need continuous adjustment, placing a burden on resources and detracting from the main operations of businesses. The evolution of security threats poses a challenge to preserving consumer trust, hence impeding industry expansion.

Market Size statistics on the Financial Data Service Providers industry in the US

Thomson Financial Software, a leading provider of financial research and analysis, has been a trusted source for business and market intelligence since its establishment in 1993. As a respected name in the industry, Thomson Financial Software offers a vast repository of financial data, covering a range of topics including economic trends, company profiles, and market research.

With years of expertise in the financial sector, Thomson Financial Software has built a reputation for delivering accurate and reliable data, making it a go-to destination for professionals seeking to stay informed about the financial markets. By leveraging its extensive network of financial institutions and industry experts, Thomson Financial Software provides in-depth insights into the global financial landscape, making it an invaluable resource for anyone seeking to stay ahead of the curve in the rapidly changing financial world.

Financial Data Feeds Market Outlook

According to our latest research, the global Financial Data Feeds market size reached USD 8.3 billion in 2024, driven by rapid digital transformation and increasing reliance on real-time analytics across financial sectors. The market is projected to expand at a robust CAGR of 8.7% from 2025 to 2033, culminating in a forecasted value of USD 17.3 billion by 2033. This strong growth trajectory is underpinned by the surging demand for accurate, timely, and comprehensive data to support trading, risk management, and regulatory compliance activities worldwide. As per our latest research, the proliferation of algorithmic trading, increasing regulatory requirements, and the rise of cloud-based solutions are significant growth drivers for the Financial Data Feeds market.

One of the primary growth factors fueling the Financial Data Feeds market is the exponential rise in algorithmic and high-frequency trading. Financial institutions, asset managers, and hedge funds are increasingly leveraging sophisticated trading algorithms that require ultra-low latency, real-time data feeds to make split-second decisions. The competitive edge in today’s trading landscape is often determined by the speed and accuracy of data acquisition, analysis, and execution. This has led to a greater reliance on real-time and historical data feeds, compelling vendors to innovate and offer solutions that can handle vast data volumes with minimal latency. Additionally, the growing adoption of machine learning and artificial intelligence in trading strategies further amplifies the need for high-quality, granular data feeds, making this segment a cornerstone of market expansion.

Another significant growth driver is the tightening regulatory environment across global financial markets. Regulatory bodies such as the SEC, ESMA, and MAS are enforcing stringent compliance and reporting standards, necessitating robust data management and transparency. Financial institutions must now source, process, and report vast amounts of reference and transactional data accurately and promptly to meet these mandates. This has led to increased investment in advanced financial data feed solutions that support compliance and regulatory reporting. Furthermore, the complexity of cross-border transactions and the emergence of new asset classes, including cryptocurrencies, have escalated the demand for diverse and comprehensive data feeds, propelling market growth.

The ongoing digital transformation within the financial sector is also a pivotal factor driving the Financial Data Feeds market. As financial institutions migrate to cloud-based infrastructures and embrace digital-first strategies, the demand for flexible, scalable, and cost-efficient data delivery models has surged. Cloud-based data feeds offer significant advantages in terms of scalability, accessibility, and integration with other digital tools and platforms, enabling organizations to respond quickly to market shifts and customer needs. The integration of data feeds with advanced analytics, portfolio management, and risk assessment platforms is enabling financial firms to derive actionable insights, optimize decision-making, and enhance overall operational efficiency. This digital evolution is expected to further accelerate market growth in the coming years.

From a regional perspective, North America continues to dominate the Financial Data Feeds market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The region’s leadership is attributed to the presence of major financial hubs, advanced technological infrastructure, and a high concentration of market participants. However, Asia Pacific is emerging as the fastest-growing region, with a notable CAGR driven by rapid financial sector development, regulatory modernization, and increasing adoption of digital trading platforms. Meanwhile, Europe is witnessing steady growth due to evolving regulatory frameworks and the rising importance of sustainable finance and ESG reporting. Latin America and the Middle East & Africa are also experiencing gradual growth, spurred by ongoing financial sector reforms and increased foreign investment.

TD: TA: Federal Funds Sold & Reverse Repurchase Agreements data was reported at 7,000,000.000 USD th in Dec 2019. This records an increase from the previous number of 1,500,000.000 USD th for Sep 2019. TD: TA: Federal Funds Sold & Reverse Repurchase Agreements data is updated quarterly, averaging 80,000.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 7,000,000.000 USD th in Dec 2019 and a record low of 0.000 USD th in Jun 2019. TD: TA: Federal Funds Sold & Reverse Repurchase Agreements data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB062: Financial Data: Federal Deposit Insurance Corporation: TD Bank.

Dataset

This dataset was created by Kumagawa AN

Contents

• Data from Dec 1989 to Dec 2020.
• Includes Income Statement, Balance Sheet, and Cashflow statement.
• Adjusted for restatements.
• Includes valuation metrics such as enterprise valuation and market capitalization.
• Over 30 ratios such as p/e ratio, EBITDA/sales, gross margin etc..
• Standardized categories for comparison between companies.

This dataset offers a detailed and organized set of financial data, enabling users to analyze company performance, conduct stock market research, and develop predictive models. It spans multiple financial aspects, such as annual and quarterly profit and loss statements, balance sheets, cash flow data, financial ratios, and market prices.

The data is structured to support time-series analysis, with datasets covering financial metrics at T0 (financial statements) and T1 (market prices).

This makes it particularly useful for applications requiring cross-temporal insights or forecasting.

Between 2008 and 2024, the most significant data breach in the financial industry worldwide was detected in 2019 in the United States at the First American Financial Corporation. This data breach caused the leakage of 885 million financial and personal records. The financial industry is one of the most targeted sectors by cyberattacks that lead to data breaches. However, cyber-attacks are not the only reason for a data breach. Sometimes data compromise occurs due to other reasons, such as system errors.

Financial Data Quality Platform Market Outlook

According to our latest research, the global Financial Data Quality Platform market size reached USD 2.8 billion in 2024, with a robust compound annual growth rate (CAGR) of 14.2% projected through the forecast period. By 2033, the market is expected to achieve a value of USD 8.4 billion, driven by the increasing complexity of financial transactions, rising regulatory scrutiny, and the critical need for reliable, high-quality data in decision-making processes. As organizations across industries prioritize data accuracy and compliance, the demand for advanced financial data quality platforms is accelerating at an unprecedented pace.

One of the primary growth factors for the Financial Data Quality Platform market is the intensifying regulatory landscape in the financial sector. With global regulatory bodies such as the SEC, FCA, and ESMA imposing stringent data governance and reporting requirements, financial institutions are under immense pressure to ensure the integrity and accuracy of financial data. Non-compliance can result in hefty fines, reputational damage, and operational disruptions. Consequently, organizations are investing in comprehensive data quality platforms that offer automated data validation, real-time monitoring, and robust audit trails. These solutions not only help meet regulatory mandates but also enhance operational efficiency by reducing manual intervention and minimizing errors in financial reporting.

Another significant driver is the exponential growth in data volume and complexity, fueled by the proliferation of digital financial services, cross-border transactions, and the adoption of advanced analytics. As financial organizations integrate diverse data sources, including legacy systems, cloud-based applications, and third-party data feeds, the risk of data inconsistencies and inaccuracies escalates. Financial data quality platforms address these challenges by providing end-to-end data cleansing, enrichment, and reconciliation capabilities. This ensures that decision-makers have access to accurate, timely, and consistent data for risk management, strategic planning, and customer engagement. The adoption of artificial intelligence and machine learning in these platforms further enhances their ability to detect anomalies, predict data quality issues, and automate remediation processes.

Additionally, the growing emphasis on digital transformation and customer-centric strategies in sectors such as banking, insurance, and asset management is propelling the adoption of financial data quality platforms. Organizations recognize that high-quality data is foundational to delivering personalized financial products, optimizing customer experiences, and gaining a competitive edge. As a result, there is a marked increase in investments in data quality initiatives, often as part of broader digital transformation projects. Vendors are responding by offering scalable, cloud-based platforms that integrate seamlessly with existing IT infrastructures and support real-time data quality monitoring across multiple business units and geographies.

From a regional perspective, North America continues to dominate the Financial Data Quality Platform market in 2024, accounting for approximately 38% of the global market share, followed closely by Europe and the Asia Pacific. The strong presence of leading financial institutions, advanced IT infrastructure, and proactive regulatory frameworks in these regions are key contributors to market growth. Meanwhile, emerging markets in Asia Pacific and Latin America are witnessing rapid adoption of financial data quality solutions, driven by the expansion of digital banking, increasing regulatory compliance requirements, and growing investments in financial technology. As these regions continue to mature, they are expected to offer significant growth opportunities for both established and emerging market players.

Component Analysis

The Component segment of the Financial Data Quality Platform market is primarily divided into Software and Services. Software solutions form the backbone of the market, providing essential features such as data profiling, validation, cleansing, matching, and monitoring. These platforms are increasingly leveraging artificial intelligence and machine learning to automate data quality processes, ide

NCUA: State: Saving: Others data was reported at 279,526,899.289 USD th in Mar 2018. This records an increase from the previous number of 275,858,532.584 USD th for Dec 2017. NCUA: State: Saving: Others data is updated quarterly, averaging 219,186,197.512 USD th from Mar 2005 (Median) to Mar 2018, with 53 observations. The data reached an all-time high of 279,526,899.289 USD th in Mar 2018 and a record low of 129,881,556.883 USD th in Mar 2005. NCUA: State: Saving: Others data remains active status in CEIC and is reported by National Credit Union Administration. The data is categorized under Global Database’s USA – Table US.KB019: Financial Data: National Credit Union Administration: State Institutions.

According to a June 2025 survey in the United States, millennials were more likely to think that consumers should have the right to share their bank account or credit card information with other financial tools and services. Roughly eight in 10 respondents of this age category stated they believed so. In comparison, 67 percent of Boomers, those aged 61 to 79 years old, said it was a good idea.

STT: LC: EC: BE: Surplus data was reported at 12,863,000.000 USD th in Dec 2019. This records an increase from the previous number of 12,848,000.000 USD th for Sep 2019. STT: LC: EC: BE: Surplus data is updated quarterly, averaging 10,124,588.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 13,232,098.000 USD th in Sep 2018 and a record low of 561,973.000 USD th in Dec 2000. STT: LC: EC: BE: Surplus data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB063: Financial Data: Federal Deposit Insurance Corporation: State Street Bank & Trust.

NCUA: All Inst: Non Interest Expense: Office Operation Expense data was reported at 1,979,761.786 USD th in Mar 2018. This records a decrease from the previous number of 7,607,406.853 USD th for Dec 2017. NCUA: All Inst: Non Interest Expense: Office Operation Expense data is updated quarterly, averaging 3,496,166.905 USD th from Mar 2005 (Median) to Mar 2018, with 53 observations. The data reached an all-time high of 7,607,406.853 USD th in Dec 2017 and a record low of 1,085,830.066 USD th in Mar 2005. NCUA: All Inst: Non Interest Expense: Office Operation Expense data remains active status in CEIC and is reported by National Credit Union Administration. The data is categorized under Global Database’s USA – Table US.KB017: Financial Data: National Credit Union Administration: All Institutions.

JPMC: TA: Depository Institutions: Interest-Bearing Balances data was reported at 242,616,000.000 USD th in Dec 2019. This records an increase from the previous number of 236,129,000.000 USD th for Sep 2019. JPMC: TA: Depository Institutions: Interest-Bearing Balances data is updated quarterly, averaging 66,639,000.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 485,259,000.000 USD th in Mar 2015 and a record low of 6,608,000.000 USD th in Dec 2000. JPMC: TA: Depository Institutions: Interest-Bearing Balances data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB054: Financial Data: Federal Deposit Insurance Corporation: JPMorgan Chase Bank.

STT: Memo: Quarterly Average Assets data was reported at 241,756,000.000 USD th in Dec 2019. This records an increase from the previous number of 239,743,000.000 USD th for Sep 2019. STT: Memo: Quarterly Average Assets data is updated quarterly, averaging 161,702,994.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 282,172,192.000 USD th in Jun 2015 and a record low of 62,922,121.000 USD th in Dec 2000. STT: Memo: Quarterly Average Assets data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB063: Financial Data: Federal Deposit Insurance Corporation: State Street Bank & Trust.

NCUA: All Inst: Assets: Inv: Total MCSD & PIC in Corp Credit Unions data was reported at 1,282,446.517 USD th in Jun 2018. This records an increase from the previous number of 1,280,255.124 USD th for Mar 2018. NCUA: All Inst: Assets: Inv: Total MCSD & PIC in Corp Credit Unions data is updated quarterly, averaging 1,496,678.752 USD th from Mar 2005 (Median) to Jun 2018, with 54 observations. The data reached an all-time high of 3,542,902.634 USD th in Mar 2008 and a record low of 1,048,642.965 USD th in Sep 2010. NCUA: All Inst: Assets: Inv: Total MCSD & PIC in Corp Credit Unions data remains active status in CEIC and is reported by National Credit Union Administration. The data is categorized under Global Database’s USA – Table US.KB044: Financial Data: National Credit Union Administration: All Institutions.