Standardized financial data on over 12 million global private companies.

Standardized North American and global company financials and market data for active and inactive publicly-traded companies.

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.

Standardized and As Reported financial data for global public companies as well as thousands of private companies and private companies with public debt.

These reports collect selected financial information for direct or indirect foreign subsidiaries of U.S. state member banks (SMBs), Edge and agreement corporations, and bank holding companies (BHCs). The FR 2314 consists of a balance sheet and income statement; information on changes in equity capital, changes in the allowance for loan and lease losses, off-balance-sheet items, and loans; and a memoranda section. The FR 2314S collects four financial data items for smaller, less complex subsidiaries. (Note: The Report of Condition for Foreign Subsidiaries of U.S. Banking Organizations, FR 2314a and FR 2314c have been replaced by the FR 2314 and FR 2314S. and the FR 2314b has been discontinued.

The dataset included with this article contains three files describing and defining the sample and variables for VAT impact, and Excel file 1 consists of all raw and filtered data for the variables for the panel data sample. Excel file 2 depicts time-series and cross-sectional data for nonfinancial firms listed on the Saudi market for the second and third quarters of 2019 and the third and fourth quarters of 2020. Excel file 3 presents the raw material of variables used in measuring the company's profitability of the panel data sample

The financial reports for the Department assist assessments of forecast financial performance, and its use of the parliamentary authority for resources.The tables in the spreadsheet display financial performance data via the comprehensive operating statement, the balance sheet, the cash flow statement, the statement of changes in equity, administered items statements, and payments on behalf of the State (where applicable).The datasets should be read in conjunction with Budget Paper No. 3 Service Delivery which provides an overview of the goods and services funded by the Government and delivered by departments in the coming financial year.

Dataset

This dataset was created by chadchiu

Contents

The Savings Association Holding Company Report (FR LL-(b)11) collects from certain savings and loan holding companies (SLHCs) information about their Securities and Exchange Commission (SEC) filings, reports, financial statements, and other exhibits that the Board requires. The Board uses this data to analyze the financial condition of respondent SLHCs, and assess regulatory compliance. The FR LL-(b)11 is filed quarterly based on the institution’s fiscal year, and also when there has been a material change in any of the information reported. The fourth quarter report also includes audited financial statements.

Dataset

This dataset was created by Metheus_Kim

Contents

JANIS consists of individual financial statements of non-financial corporations which are provided from several sources: financial statements received by the Deutsche Bundesbank in the context of the credit assessment and from public sources like the Bundesanzeiger.

The Financial Statements of U.S. Nonbank Subsidiaries of U.S. Holding Companies (FR Y-11; FR Y-11S) reporting forms collect financial information for individual nonfunctional regulated U.S. nonbank subsidiaries of domestic holding companies, which is essential for monitoring the subsidiaries' potential impact on the condition of the holding company or its subsidiary banks. Holding companies file the FR Y-11 on a quarterly or annual basis or the FR Y-11S on an annual basis, predominantly based on whether the organization meets certain asset size thresholds. The FR Y-11 data are used with other holding company data to assess the condition of holding companies that are heavily engaged in nonbanking activities and to monitor the volume, nature, and condition of their nonbanking operations.

Financial statement filings from banks and credit unions.

Financial industries are the most important users of derivatives. Thus, derivative accounting should be of economic significance to bank holding companies. Moreover, bank holding companies are required by law to provide detailed information on derivative holdings in a uniform format through regulatory filing (Quarterly FR-Y9C reports filed with the Federal Reserve Bank). The sample used in this study covers bank holding companies during the period from 2001 through 2005. The sample period is restricted up to 2005 because the key variable in this study that captures the hedging derivatives’ impact on income was only included in the FR-Y9C reports during this period. Bank holding companies in my sample must meet the following criteria: (1) quarterly financial statement data are available through COMPUSTAT, (2) stock return data are available through CRSP, and (3) the bank holding company filed FR-Y9C reports with the Federal Reserve Bank during the sample period, (4) This selection procedure yields a final sample of 168 unique bank holding companies

Content

Provides summary of allocable income from quarterly financial statements.

Context

This is a dataset hosted by the World Bank. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore World Bank's Financial Data using Kaggle and all of the data sources available through the World Bank organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

This dataset is distributed under Creative Commons Attribution 3.0 IGO

This table contains 1659 series, with data for years 1980 - 1998 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Industry (33 items: Total, all industries;Total, non-financial industries;Food (including food retailing);Beverages and tobacco; ...); Balance sheet and income statement components (93 items: Total assets;Cash and deposits;Accounts receivable and accrued revenue;Inventories; ...).

This document is part of the source library for NRGI's National Oil Company Database, an open database of facts and figures on more than 70 national oil companies worldwide. See the full database at https://nationaloilcompanydata.org/.

Success.ai’s Company Financial Data for European Financial Professionals provides a comprehensive dataset tailored for businesses looking to connect with financial leaders, analysts, and decision-makers across Europe. Covering roles such as CFOs, accountants, financial consultants, and investment managers, this dataset offers verified contact details, firmographic insights, and actionable professional histories.

With access to over 170 million verified professional profiles, Success.ai ensures your outreach, market research, and partnership strategies are driven by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution is indispensable for navigating the fast-paced European financial landscape.

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   • Includes financial professionals from key markets such as the United Kingdom, Germany, France, Italy, and the Netherlands.
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   • Real-time updates capture changes in professional roles, company structures, and market conditions.
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4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

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• Leadership Insights: Connect with CFOs, financial controllers, and investment managers driving financial strategies.

Key Features of the Dataset:

1. Comprehensive Financial Professional Profiles

   • Identify and connect with key players in finance, including financial analysts, accountants, and consultants.
   • Target professionals responsible for budgeting, investment strategies, regulatory compliance, and financial planning.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (banking, fintech, asset management), geographic location, or job function.
   • Tailor campaigns to align with specific financial needs, such as software solutions, advisory services, or compliance tools.

3. Regional and Industry Insights

   • Leverage data on European financial trends, regulatory challenges, and market opportunities.
   • Refine your approach to align with industry-specific demands and geographic preferences.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Lead Generation

   • Design targeted campaigns to promote financial software, advisory services, or compliance solutions to European financial professionals.
   • Use verified contact data for multi-channel outreach, including email, phone, and social media.

2. Partnership Development and Collaboration

   • Build relationships with financial firms, fintech companies, and investment organizations exploring strategic partnerships.
   • Foster collaborations that enhance financial efficiency, innovation, or regulatory compliance.

3. Market Research and Competitive Analysis

   • Analyze financial trends across Europe to refine product offerings, marketing strategies, and business expansion plans.
   • Benchmark against competitors to identify growth opportunities and emerging demands.

4. Recruitment and Talent Acquisition

   • Target HR professionals and hiring managers recruiting for financial roles, from analysts to CFOs.
   • Provide workforce optimization platforms or training solutions tailored to the financial sector.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality financial data at competitive prices, ensuring strong ROI for your marketing, sales, and partnership initiatives.

2. Seamless Integration

   • Integrate verified financial data into CRM systems, analytics tools, or marketing platforms via APIs or downloadable formats, streamlining workflows and enhancing productivity.

3. Data Accuracy with AI Validation

   • Rely on 99% accuracy to guide data-driven decisions, refine targeting, and boost conversion rates in financial ca...

JANIS consists of individual financial statements of non-financial corporations which are provided from several sources: financial statements received by the Deutsche Bundesbank in the context of the credit assessment and from public sources like the Bundesanzeiger.

Content

Provides data from the IBRD Statement of Income for the fiscal years ended June 30, 2013, June 30, 2012 and June 30, 2011. The values are expressed in millions of U.S. Dollars. Where applicable, changes have been made to certain line items on FY 2012 income statement to conform with the current year's presentation, but the comparable prior years' data sets have not been adjusted to reflect the reclassification impact of those changes.

Context

This is a dataset hosted by the World Bank. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore World Bank's Financial Data using Kaggle and all of the data sources available through the World Bank organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

This dataset is distributed under a Creative Commons Attribution 3.0 IGO license.

Cover photo by Matt Artz on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

This dataset is distributed under Creative Commons Attribution 3.0 IGO