The data sets below provide selected information extracted from exhibits to corporate financial reports filed with the Commission using eXtensible Business Reporting Language (XBRL).

This is a compiled datasets comprising of data from various companies' 10-K annual reports and balance sheets. The data is a longitudinal or panel data, from year 2009-2022(/23) and also consists of a few bankrupt companies to help for investigating factors. The names of the companies are given according to their Stocks. Companies divided into specific categories.

Our Financial API provides access to a vast collection of historical financial statements for over 50,000+ companies listed on major exchanges. With this powerful tool, you can easily retrieve balance sheets, income statements, and cash flow statements for any company in our extensive database. Stay informed about the financial health of various organizations and make data-driven decisions with confidence. Our API is designed to deliver accurate and up-to-date financial information, enabling you to gain valuable insights and streamline your analysis process. Experience the convenience and reliability of our company financial API today.

On an annual basis (individual hospital fiscal year), individual hospitals and hospital systems report detailed facility-level data on services capacity, inpatient/outpatient utilization, patients, revenues and expenses by type and payer, balance sheet and income statement.

Due to the large size of the complete dataset, a selected set of data representing a wide range of commonly used data items, has been created that can be easily managed and downloaded. The selected data file includes general hospital information, utilization data by payer, revenue data by payer, expense data by natural expense category, financial ratios, and labor information.

There are two groups of data contained in this dataset: 1) Selected Data - Calendar Year: To make it easier to compare hospitals by year, hospital reports with report periods ending within a given calendar year are grouped together. The Pivot Tables for a specific calendar year are also found here. 2) Selected Data - Fiscal Year: Hospital reports with report periods ending within a given fiscal year (July-June) are grouped together.

This is a dataset that requires a lot of preprocessing with amazing EDA insights for a company. A dataset consisting of sales and profit data sorted by market segment and country/region.

Tips for pre-processing: 1. Check for column names and find error there itself!! 2. Remove '$' sign and '-' from all columns where they are present 3. Change datatype from objects to int after the above two. 4. Challenge: Try removing " , " (comma) from all numerical numbers. 5. Try plotting sales and profit with respect to timeline

• 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.

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...

Snapshot img

Financial Analytics Market Size 2025-2029

The financial analytics market size is forecast to increase by USD 9.09 billion at a CAGR of 12.7% between 2024 and 2029.

The market is experiencing significant growth, driven primarily by the increasing demand for advanced risk management tools in today's complex financial landscape. With the exponential rise in data generation across various industries, financial institutions are seeking to leverage analytics to gain valuable insights and make informed decisions. However, this data-driven approach comes with its own challenges. Data privacy and security concerns are becoming increasingly prominent as financial institutions grapple with the responsibility of safeguarding sensitive financial information. Ensuring data security and maintaining regulatory compliance are essential for businesses looking to capitalize on the opportunities presented by financial analytics.
As the market continues to evolve, companies must navigate these challenges while staying abreast of the latest trends and technologies to remain competitive. Effective implementation of robust data security measures, adherence to regulatory requirements, and continuous innovation will be key to success in the market. Data visualization tools enable effective communication of complex financial data, while financial advisory services offer expert guidance on financial modeling and regulatory compliance.

What will be the Size of the Financial Analytics Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

In the dynamic market, sensitivity analysis plays a crucial role in assessing the impact of various factors on financial models. Data lakes serve as vast repositories for storing and processing large volumes of financial data, enabling advanced quantitative analysis. Financial regulations mandate strict data compliance regulations, ensuring data privacy and security. Data analytics platforms integrate statistical software, machine learning libraries, and prescriptive analytics to deliver actionable insights. Financial reporting software and business intelligence tools facilitate descriptive analytics, while diagnostic analytics uncovers hidden trends and anomalies. On-premise analytics and cloud-based analytics cater to diverse business needs, with data warehouses and data pipelines ensuring seamless data flow.
Scenario analysis and stress testing help financial institutions assess risks and make informed decisions. Data engineering and data governance frameworks ensure data accuracy, consistency, and availability. Data architecture, data compliance regulations, and auditing standards maintain transparency and trust in financial reporting. Predictive modeling and financial modeling software provide valuable insights into future financial performance. Data security measures protect sensitive financial data, safeguarding against potential breaches.

How is this Financial Analytics Industry segmented?

The financial analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Component

  Solution
  Services


Deployment

  On-premises
  Cloud


Sector

  Large enterprises
  Small and medium-sized enterprises (SMEs)


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan


  Rest of World (ROW)

By Component Insights

The solution segment is estimated to witness significant growth during the forecast period. Financial analytics solutions play a pivotal role in assessing and managing various financial risks for organizations. These tools help identify potential risks, such as credit risks, market risks, and operational risks, and enable proactive risk mitigation measures. Compliance with stringent regulations, including Basel III, Dodd-Frank, and GDPR, necessitates robust data analytics and reporting capabilities. Data visualization, machine learning, statistical modeling, and predictive analytics are integral components of financial analytics solutions. Machine learning and statistical modeling enable automated risk analysis and prediction, while predictive analytics offers insights into future trends and potential risks.

Data governance and data compliance help organizations maintain data security and privacy. Data integration and ETL processes facilitate seamless data flow between various systems, ensuring data consistency and accuracy. Time series analysis and ratio analysis offer insights into historical financial trends and performance. Customer segmentation and sensitivity analysis provide val

Access historical and point-in-time financial statements, ratios, multiples, and press releases, with LSEG's S&P Compustat Database.

Comprehensive database of over 100,000 financial filings from 8,000+ European companies

Korean Companies’ Financial Data provides important information to analyze a company’s financial status and performance. This data includes financial indicators such as revenue, expenses, assets, and liabilities. Collected from corporate financial reports and stock market data, it helps investors evaluate financial health and discover investment opportunities, essential for valuing Korean companies.

Yahoo Finance dataset provides information on top traded companies. It contains financial information on each company including stock ticker and risk scores and general company information such as company location and industry. Each record in the dataset is a unique stock, where multiple stocks can be related to the same company. Yahoo Finance dataset attributes include: company name, company ID, entity type, summary, stock ticker, currency, earnings, exchange, closing price, previous close, open, bid, ask, day range, week range, volume, and much more.

Peru ZOFRATACNA: Expenses: CA: Acquisition of Non Financial Assets data was reported at 0.000 PEN in Mar 2019. This stayed constant from the previous number of 0.000 PEN for Dec 2018. Peru ZOFRATACNA: Expenses: CA: Acquisition of Non Financial Assets data is updated quarterly, averaging 0.000 PEN from Mar 2010 (Median) to Mar 2019, with 36 observations. The data reached an all-time high of 12,182.000 PEN in Dec 2012 and a record low of 0.000 PEN in Mar 2019. Peru ZOFRATACNA: Expenses: CA: Acquisition of Non Financial Assets data remains active status in CEIC and is reported by Free Zone of Tacna. The data is categorized under Global Database’s Peru – Table PE.O005: Free Zone of Tacna: Financial Statement.

ZOFRATACNA: Income: Sales of Non Financial Assets data was reported at 92,337.810 PEN in Mar 2019. This records a decrease from the previous number of 362,898.040 PEN for Dec 2018. ZOFRATACNA: Income: Sales of Non Financial Assets data is updated quarterly, averaging 185,456.000 PEN from Mar 2007 (Median) to Mar 2019, with 43 observations. The data reached an all-time high of 14,280,617.000 PEN in Dec 2009 and a record low of 0.000 PEN in Jun 2008. ZOFRATACNA: Income: Sales of Non Financial Assets data remains active status in CEIC and is reported by Free Zone of Tacna. The data is categorized under Global Database’s Peru – Table PE.O005: Free Zone of Tacna: Financial Statement.

List of companies in the S&P 500 (Standard and Poor's 500). The S&P 500 is a free-float, capitalization-weighted index of the top 500 publicly listed stocks in the US (top 500 by market cap). The ...

Comprehensive collection of financial reports and documents for Q-Free ASA (QFR)

Lucror Analytics: Fundamental Fixed Income Data and Financial Models for High-Yield Bond Issuers

At Lucror Analytics, we deliver expertly curated data solutions focused on corporate credit and high-yield bond issuers across Europe, Asia, and Latin America. Our data offerings integrate comprehensive fundamental analysis, financial models, and analyst-adjusted insights tailored to support professionals in the credit and fixed-income sectors. Covering 400+ bond issuers, our datasets provide a high level of granularity, empowering asset managers, institutional investors, and financial analysts to make informed decisions with confidence.

By combining proprietary financial models with expert analysis, we ensure our Fixed Income Data is actionable, precise, and relevant. Whether you're conducting credit risk assessments, building portfolios, or identifying investment opportunities, Lucror Analytics offers the tools you need to navigate the complexities of high-yield markets.

What Makes Lucror’s Fixed Income Data Unique?

Comprehensive Fundamental Analysis Our datasets focus on issuer-level credit data for complex high-yield bond issuers. Through rigorous fundamental analysis, we provide deep insights into financial performance, credit quality, and key operational metrics. This approach equips users with the critical information needed to assess risk and uncover opportunities in volatile markets.

Analyst-Adjusted Insights Our data isn’t just raw numbers—it’s refined through the expertise of seasoned credit analysts with 14 years average fixed income experience. Each dataset is carefully reviewed and adjusted to reflect real-world conditions, providing clients with actionable intelligence that goes beyond automated outputs.

Focus on High-Yield Markets Lucror’s specialization in high-yield markets across Europe, Asia, and Latin America allows us to offer a targeted and detailed dataset. This focus ensures that our clients gain unparalleled insights into some of the most dynamic and complex credit markets globally.

How Is the Data Sourced? Lucror Analytics employs a robust and transparent methodology to source, refine, and deliver high-quality data:

• Public Sources: Includes issuer filings, bond prospectuses, financial reports, and market data.
• Proprietary Analysis: Leveraging proprietary models, our team enriches raw data to provide actionable insights.
• Expert Review: Data is validated and adjusted by experienced analysts to ensure accuracy and relevance.
• Regular Updates: Models are continuously updated to reflect market movements, regulatory changes, and issuer-specific developments.

This rigorous process ensures that our data is both reliable and actionable, enabling clients to base their decisions on solid foundations.

Primary Use Cases 1. Fundamental Research Institutional investors and analysts rely on our data to conduct deep-dive research into specific issuers and sectors. The combination of raw data, adjusted insights, and financial models provides a comprehensive foundation for decision-making.

1. Credit Risk Assessment Lucror’s financial models provide detailed credit risk evaluations, enabling investors to identify potential vulnerabilities and mitigate exposure. Analyst-adjusted insights offer a nuanced understanding of creditworthiness, making it easier to distinguish between similar issuers.

2. Portfolio Management Lucror’s datasets support the development of diversified, high-performing portfolios. By combining issuer-level data with robust financial models, asset managers can balance risk and return while staying aligned with investment mandates.

3. Strategic Decision-Making From assessing market trends to evaluating individual issuers, Lucror’s data empowers organizations to make informed, strategic decisions. The regional focus on Europe, Asia, and Latin America offers unique insights into high-growth and high-risk markets.

Key Features of Lucror’s Data - 400+ High-Yield Bond Issuers: Coverage across Europe, Asia, and Latin America ensures relevance in key regions. - Proprietary Financial Models: Created by one of the best independent analyst teams on the street. - Analyst-Adjusted Data: Insights refined by experts to reflect off-balance sheet items and idiosyncrasies. - Customizable Delivery: Data is provided in formats and frequencies tailored to the needs of individual clients.

Why Choose Lucror Analytics? Lucror Analytics and independent provider free from conflicts of interest. We are committed to delivering high-quality financial models for credit and fixed-income professionals. Our proprietary approach combines proprietary models with expert insights, ensuring accuracy, relevance, and utility.

By partnering with Lucror Analytics, you can: - Safe costs and create internal efficiencies by outsourcing a highly involved and time-consuming processes, including financial analysis and modelling. - Enhance your credit risk ...

Information on financial company dividend disclosure, information on financial company decision to increase capital by paid-in capital, information on financial company decision to increase capital by free of charge, information on convocation of general shareholders' meeting of financial companies, information on reporting on granting of stock options by financial companies, information on reporting on appointment/dismissal or early retirement of outside directors of financial companies, information on transfer of assets (other)_putback option disclosure, information on financial company suspension of business, information on financial company application for commencement of rehabilitation procedure, information on occurrence of cause for dissolution of financial company, information on financial company decision to reduce capital, information on commencement of management procedure of creditor banks, etc. of financial company, information on filing of lawsuits, etc. by financial company, information on listing of stocks, etc. on overseas stock market by financial company, information on delisting of stocks, etc. on overseas stock market by financial company, information on decision to issue convertible bonds by financial company, information on decision to issue bonds with new stock subscription rights by financial company, Provides information on financial company exchangeable bond issuance decisions, financial company write-off contingent capital securities issuance decisions, financial company treasury stock acquisition decisions, financial company treasury stock disposal decisions, financial company business transfer decisions, financial company acquisition of other corporations' stocks and investment securities, financial company acquisition of other corporations' stocks and investment securities, financial company acquisition of bonds related to stocks, financial company transfer of bonds related to stocks, financial company merger decisions, financial company division decisions, financial company division merger decisions, and financial company stock exchange/transfer decisions.

This dataset provides information on 898 in Russia as of June, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.

This datasets contains information about NYCHA residents’ use of: a) NYC Financial Empowerment Centers: a program that provides free, one-on-one professional financial counseling and coaching to all NYC residents. Each row in the dataset represents the number of NYCHA residents on a Borough-level who utilized this service; b) EmpoweredNYC: is an initiative to assist New Yorkers with disabilities and their families to better manage their finances and become more financially stable. Each row in the dataset represents the number of NYCHA residents on a Borough-level who utilized this service; c) Student Loan Debt clinic: is an initiative to help New Yorkers understand their student loans and how to repay them. Each row in the dataset represents the number of NYCHA residents on a Borough-level who utilized this service; and d) Ready to Rent: a program providing free one-on-one financial counseling to New Yorkers seeking to apply for affordable housing units through HPD’s Housing Connect lottery. Each row in the dataset represents the number of NYCHA residents on a Borough-level who utilized this service. The dataset is part of the annual report compiled by the Mayor’s Office of Operations as mandated by the Local Law 163 of 2016 on different services provided to NYCHA residents. See other datasets in this report by searching the keyword “Services available to NYCHA Residents - Local Law 163 (2016)” on the Open Data Portal.