Standardized financial data on over 12 million global private companies.
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:
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.
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.
Evaluate the financial performance of public and private companies for informed investment decisions. Use our data to identify growth opportunities and assess risk factors.
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.
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...
Standardized North American and global company financials and market data for active and inactive publicly-traded companies.
Our comprehensive and advanced database is completed with all the information you need, with up to >1.5 million company financial records at your disposal. This allows you to easily perform company search on company profile and company directory, with 99% coverage in Malaysia.
Our database also contains company profiles on private limited or limited companies globally, including information such as shareholders and financial accounts can be accessed instantly.
Standardized and As Reported financial data for global public companies as well as thousands of private companies and private companies with public debt.
Success.ai’s Company Financial Data for Banking & Capital Markets Professionals in the Middle East offers a reliable and comprehensive dataset designed to connect businesses with key stakeholders in the financial sector. Covering banking executives, capital markets professionals, and financial advisors, this dataset provides verified contact details, decision-maker profiles, and firmographic insights tailored for the Middle Eastern market.
With access to over 170 million verified professional profiles and 30 million company profiles, Success.ai ensures your outreach and strategic initiatives are powered by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution empowers your organization to build meaningful connections in the region’s thriving financial industry.
Why Choose Success.ai’s Company Financial Data?
Verified Contact Data for Financial Professionals
Targeted Insights for the Middle East Financial Sector
Continuously Updated Datasets
Ethical and Compliant
Data Highlights:
Key Features of the Dataset:
Decision-Maker Profiles in Banking & Capital Markets
Advanced Filters for Precision Targeting
Firmographic and Leadership Insights
AI-Driven Enrichment
Strategic Use Cases:
Sales and Lead Generation
Market Research and Competitive Analysis
Partnership Development and Vendor Evaluation
Recruitment and Talent Solutions
Why Choose Success.ai?
Discover verified Company Financial Data with Success.ai. Includes profiles of CFOs, financial analysts, and corporate treasurers with work emails and phone numbers. Continuously updated and AI-validated. Best price guaranteed.
Detailed and standardized financial data on Japanese public companies.
Transform Unstructured Financial Docs into Actionable Insights Harness proprietary AI models to extract, validate, and standardize financial data from any document format, including scanned images, handwritten notes, or multi-language PDFs. Unlike basic OCR tools, our solution handles complex layouts, merged cells, poor quality PDFs and low-quality scans with industry-leading precision.
Key Features Universal Format Support: Extract data from scanned PDFs, images (JPEG/PNG), Excel, Word, and any other handwritten documents.
AI-Driven OCR & LLM Standardization:
Convert unstructured text into standardized fields (e.g., "Net Profit" → ISO 20022-compliant tags).
Resolve inconsistencies (e.g., "$1M" vs. "1,000,000 USD") using context-aware LLMs.
100+ Language Coverage: Process financial docs in Arabic, Bulgarian, and more with automated translation.
Up to 99% Accuracy: Triple-validation via AI cross-checks, rule-based audits, and human-in-the-loop reviews.
Prebuilt Templates: Auto-detect formats for common documents (e.g., IFRS-compliant P&L statements, IRS tax forms).
Data Sourcing & Output Supported Documents: Balance sheets, invoices, tax filings, bank statements, receipts and more. Export Formats: Excel, CSV, JSON, API, PostgreSQL, or direct integration with tools like QuickBooks, SAP.
Use Cases 1. Credit Risk Analysis: Automate financial health assessments for loan approvals and vender analysis.
Audit Compliance: Streamline data aggregation for GAAP/IFRS audits.
Due Diligence: Verify company legitimacy for mergers, investments, acquisitions, or partnerships.
Compliance: Streamline KYC/AML workflows with automated financials check.
Invoice Processing: Extract vendor payment terms, due dates, and amounts.
Technical Edge 1. AI Architecture: Leverages proprietary algorithm which combines vision transformers and OCR pipelines for layout detection, LLM models for context analysis, and rule-based validation.
Security: SOC 2 compliance, and on-premise storage options.
Latency: Process as much as 10,000 pages/hour with sub-60-second extractions.
Pricing & Trials Pay-as-you-go (min 1,000 docs/month).
Enterprise: Custom pricing for volume discounts, SLA guarantees, and white-glove onboarding.
Free Trial Available
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
The dataset supports an existing published research. The data includes the textual analysis variables used. Details of the variables and data collection process is reported in the published article. Abstract below:AbstractIn this study, I examine variations in the textual complexity of annual report narrative disclosures using the Fog Readability Index and Fin-Neg word list Tone Index given year and industry effects. I analyse accounting narrative Readability and Tone based on firm years, associations between the two narrative measures, and industry data. Tests of the relationship between Readability and Tone show that negative narratives have higher Readability scores, supporting the obfuscation hypothesis that bad news tends to be more difficult to read. A year analysis shows that the negative relationship between Readability and Tone increases in significance over time (2006–2011). An industry analysis shows that the observed obfuscation tends to persist in basic materials; consumer services; financial; technology; and utilities industries. This study shows that considering the effect of variations between industry and firm years can inform annual report textual complexity research and associated empirical analyses.
The global big data and business analytics (BDA) market was valued at 168.8 billion U.S. dollars in 2018 and is forecast to grow to 215.7 billion U.S. dollars by 2021. In 2021, more than half of BDA spending will go towards services. IT services is projected to make up around 85 billion U.S. dollars, and business services will account for the remainder. Big data High volume, high velocity and high variety: one or more of these characteristics is used to define big data, the kind of data sets that are too large or too complex for traditional data processing applications. Fast-growing mobile data traffic, cloud computing traffic, as well as the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the increasing volume and complexity of data sets. For example, connected IoT devices are projected to generate 79.4 ZBs of data in 2025. Business analytics Advanced analytics tools, such as predictive analytics and data mining, help to extract value from the data and generate business insights. The size of the business intelligence and analytics software application market is forecast to reach around 16.5 billion U.S. dollars in 2022. Growth in this market is driven by a focus on digital transformation, a demand for data visualization dashboards, and an increased adoption of cloud.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Russia Goldman Sachs: Interest Receivable data was reported at 47,053.000 RUB th in 2016. This records an increase from the previous number of 40,031.000 RUB th for 2015. Russia Goldman Sachs: Interest Receivable data is updated yearly, averaging 40,421.500 RUB th from Dec 2007 (Median) to 2016, with 10 observations. The data reached an all-time high of 90,738.000 RUB th in 2012 and a record low of 1,295.000 RUB th in 2007. Russia Goldman Sachs: Interest Receivable data remains active status in CEIC and is reported by Company Financial Statement. The data is categorized under Russia Premium Database’s Financial Market – Table RU.ZF004: Company Financial Data: Goldman Sachs.
Access 170M+ verified company financial data with Success.ai’s B2B Contact Data for European financial professionals. Includes work emails, phone numbers, and continuously updated datasets. Best price guaranteed.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
The dataset contains the annual report of US public firms filing with the SEC EDGAR system. Each annual report (10K filing) is broken into 20 sections. Each section is split into individual sentences. Sentiment labels are provided on a per filing basis from the market reaction around the filing data. Additional metadata for each filing is included in the dataset.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Russia NTV Broadcasting Company: Other Operating Revenue data was reported at 2,452,033.000 RUB th in 2016. This records a decrease from the previous number of 5,565,534.000 RUB th for 2015. Russia NTV Broadcasting Company: Other Operating Revenue data is updated yearly, averaging 1,172,361.000 RUB th from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 5,565,534.000 RUB th in 2015 and a record low of 5,288.000 RUB th in 2001. Russia NTV Broadcasting Company: Other Operating Revenue data remains active status in CEIC and is reported by Company Financial Statement. The data is categorized under Russia Premium Database’s Transport and Telecommunications Sector – Table RU.TJ005: Company Financial Data: TV: NTV Broadcasting Company.
https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy
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 associated with 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.
Impact of Covid-19 on the Financial Data Service Market
Covid-19 significantly impacted the Financial Data Service Market as companies increasingly relied on accurate data analytics for rapid decision-making amid market volatility. During the pandemic, financial data providers observed heightened demand for real-time and historical data to model economic scenarios and assess risks accurately. This shift spurred technological advancements a...
Financial statement filings from banks and credit unions.
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Graph and download economic data for Quarterly Financial Report: U.S. Corporations: All Manufacturing: Net Sales, Receipts, and Operating Revenues (QFR101MFGUSNO) from Q4 2000 to Q4 2024 about operating, receipts, revenue, finance, corporate, Net, sales, manufacturing, industry, and USA.
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Graph and download economic data for Nonfinancial Corporate Business; Revenue from Sales of Goods and Services, Excluding Indirect Sales Taxes (FSIs), Transactions (BOGZ1FA106030005A) from 1946 to 2023 about sales taxes, revenue, transactions, nonfinancial, tax, business, sales, goods, services, and USA.
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Uncover historical ownership history and changes over time by performing a reverse Whois lookup for the company Financial-Data-Managements-Inc..
Standardized financial data on over 12 million global private companies.