Form 10-K is an annual report that provides a comprehensive analysis of the company's financial condition. The Form 10-K is comprised of several parts. These include:

Business summary:

This describes the company's operations. It would include information about business segments, products and services, subsidiaries, markets, regulatory issues, research and development, competition, and employees, among other details.

Management Discussion and Analysis:

This section allows the company to explain its operations and financial results for the past year.

Financial statements:

The financial statements would include the company's balance sheet, income statement, and cash flow statement.

Additional sections: Additional sections may discuss the company's management team and legal proceedings.

Why Form 10-K Is Important to Investors

The SEC mandates that all public companies file regular 10-Ks to keep investors aware of a company's financial condition and to allow them to have enough information before they buy or sell securities issued by that company. The 10-K can appear overly complex at first glance, complete with tables full of data and figures. However, it is so comprehensive that this filing is critical for investors to handle a company's financial position and prospects.

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

In the U.S. public companies, certain insiders and broker-dealers are required to regularly file with the SEC. The SEC makes this data available online for anybody to view and use via their Electronic Data Gathering, Analysis, and Retrieval (EDGAR) database. The SEC updates this data every quarter going back to January, 2009. For more information please see this site.

To aid analysis a quick summary view of the data has been created that is not available in the original dataset. The quick summary view pulls together signals into a single table that otherwise would have to be joined from multiple tables and enables a more streamlined user experience.

DISCLAIMER: The Financial Statement and Notes Data Sets contain information derived from structured data filed with the Commission by individual registrants as well as Commission-generated filing identifiers. Because the data sets are derived from information provided by individual registrants, we cannot guarantee the accuracy of the data sets. In addition, it is possible inaccuracies or other errors were introduced into the data sets during the process of extracting the data and compiling the data sets. Finally, the data sets do not reflect all available information, including certain metadata associated with Commission filings. The data sets are intended to assist the public in analyzing data contained in Commission filings; however, they are not a substitute for such filings. Investors should review the full Commission filings before making any investment decision.

This dataset offers a detailed collection of US-GAAP financial data extracted from the financial statements of exchange-listed U.S. companies, as submitted to the U.S. Securities and Exchange Commission (SEC) via the EDGAR database. Covering filings from January 2009 onwards, this dataset provides key financial figures reported by companies in accordance with U.S. Generally Accepted Accounting Principles (GAAP).

Dataset Features:

• Data Scope: The dataset is restricted to figures reported under US-GAAP standards, with the exception of EntityCommonStockSharesOutstanding and EntityPublicFloat.
• Currency and Units: The dataset exclusively includes figures reported in USD or shares, ensuring uniformity and comparability. It excludes ratios and non-financial metrics to maintain focus on financial data.
• Company Selection: The dataset is limited to companies with U.S. exchange tickers, providing a concentrated analysis of publicly traded firms within the United States.
• Submission Types: The dataset only incorporates data from 10-Q, 10-K, 10-Q/A, and 10-K/A filings, ensuring consistency in the type of financial reports analyzed.

Data Sources and Extraction:

This dataset primarily relies on the SEC's Financial Statement Data Sets and EDGAR APIs: - SEC Financial Statement Data Sets - EDGAR Application Programming Interfaces

In instances where specific figures were missing from these sources, data was directly extracted from the companies' financial statements to ensure completeness.

Please note that the dataset presents financial figures exactly as reported by the companies, which may occasionally include errors. A common issue involves incorrect reporting of scaling factors in the XBRL format. XBRL supports two tag attributes related to scaling: 'decimals' and 'scale.' The 'decimals' attribute indicates the number of significant decimal places but does not affect the actual value of the figure, while the 'scale' attribute adjusts the value by a specific factor.

However, there are several instances, numbering in the thousands, where companies have incorrectly used the 'decimals' attribute (e.g., 'decimals="-6"') under the mistaken assumption that it controls scaling. This is not correct, and as a result, some figures may be inaccurately scaled. This dataset does not attempt to detect or correct such errors; it aims to reflect the data precisely as reported by the companies. A future version of the dataset may be introduced to address and correct these issues.

The source code for data extraction is available here

Abstract

This dataset is a mirror of the Financial Statement and Notes Data Set (https://www.sec.gov/dera/data/financial-statement-and-notes-data-set.html) hosted by the SEC and is updated monthly.

Methodology

From this page:

%3E The Financial Statement and Notes Data Sets provide the text and detailed numeric information from all financial statements and their notes. This data is extracted from exhibits to corporate financial reports filed with the Commission using eXtensible Business Reporting Language (XBRL). As compared to the more compact Financial Statement Data Sets which provide only the numeric information from face financials, the Financial Statement and Notes Data Sets provide significantly more disclosure data. The information is presented without change from the "as filed" financial reports submitted by each registrant. The data is presented in a flattened format to help users analyze and compare corporate disclosure information over time and across registrants. The data sets also contain additional fields such as a company's Standard Industrial Classification to facilitate the data's use.

%3E DISCLAIMER: The Financial Statement and Notes Data Sets contain information derived from structured data filed with the Commission by individual registrants as well as Commission-generated filing identifiers. Because the data sets are derived from information provided by individual registrants, we cannot guarantee the accuracy of the data sets. In addition, it is possible inaccuracies or other errors were introduced into the data sets during the process of extracting the data and compiling the data sets. Finally, the data sets do not reflect all available information, including certain metadata associated with Commission filings. The data sets are intended to assist the public in analyzing data contained in Commission filings; however, they are not a substitute for such filings. Investors should review the full Commission filings before making any investment decision.

Once a month, the second-to-latest dump of data (ex: August 2022 dump is downloaded in October 2022) is downloaded from the page and then the tables are extracted and appended to the existing ones in this Redivis dataset.

Usage

Please refer to this documentation file created by the SEC, which provides documentation of scope, organization, file formats and table definitions.

This dataset is simply just the data from https://www.sec.gov/about/divisions-offices/division-economic-risk-analysis/data/financial-statement-and-notes-data-set . It used to be reported quarterly but recently it is now monthly.

The Corporate Financial Fraud project is a study of company and top-executive characteristics of firms that ultimately violated Securities and Exchange Commission (SEC) financial accounting and securities fraud provisions compared to a sample of public companies that did not. The fraud firm sample was identified through systematic review of SEC accounting enforcement releases from 2005-2010, which included administrative and civil actions, and referrals for criminal prosecution that were identified through mentions in enforcement release, indictments, and news searches. The non-fraud firms were randomly selected from among nearly 10,000 US public companies censused and active during at least one year between 2005-2010 in Standard and Poor's Compustat data. The Company and Top-Executive (CEO) databases combine information from numerous publicly available sources, many in raw form that were hand-coded (e.g., for fraud firms: Accounting and Auditing Enforcement Releases (AAER) enforcement releases, investigation summaries, SEC-filed complaints, litigation proceedings and case outcomes). Financial and structural information on companies for the year leading up to the financial fraud (or around year 2000 for non-fraud firms) was collected from Compustat financial statement data on Form 10-Ks, and supplemented by hand-collected data from original company 10-Ks, proxy statements, or other financial reports accessed via Electronic Data Gathering, Analysis, and Retrieval (EDGAR), SEC's data-gathering search tool. For CEOs, data on personal background characteristics were collected from Execucomp and BoardEx databases, supplemented by hand-collection from proxy-statement biographies.

This dataset was compiled from publicly available SEC EDGAR 10-K filings for three major companies — Apple, Tesla, and Microsoft — across fiscal years 2020 to 2022. It was curated, cleaned, and structured for ease of use in data analysis, visualization, and educational projects.

While Kaggle requires the use of the Open Database License (ODbL), this dataset is effectively shared under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

It includes manually extracted and cleaned values from annual reports to help learners and analysts:

Visualize financial growth and trends

Practice working with real-world structured financial data

Explore company performance using core financial indicators

Beginner Friendly!!

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.

This dataset contains information found in the 10-K annual reports filed by companies in the US. It comes from the SEC official website found here. I scraped the data in a jupyter notebook and kept only a few of the important financial line items (there are 300+ for some 10k reports). No 10-K/A amendments were taken into account, so some information could be incorrect. In other words, don't bet the farm on a trading model built with this data. The price data was collected from the yfinance python API.

A dataset of public corporate filings (such as annual reports, quarterly reports, and ad-hoc disclosures) for SEC CARBON,LIMITED (5304), provided by FinancialReports.eu.

In the U.S. public companies, certain insiders and broker-dealers are required to regularly file with the SEC. The SEC makes this data available online for anybody to view and use via their Electronic Data Gathering, Analysis, and Retrieval (EDGAR) database. The SEC updates this data every quarter going back to January, 2009. To aid analysis a quick summary view of the data has been created that is not available in the original dataset. The quick summary view pulls together signals into a single table that otherwise would have to be joined from multiple tables and enables a more streamlined user experience. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets.Learn more

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 SEC Form 10-K is an annual report required by the U.S. Securities and Exchange Commission (SEC), that gives a comprehensive summary of a company's financial performance.

The full contents of the SEC 10-K are available through the SEC's EDGAR database. PUDL integrates only some of the 10-K metadata and data extracted from the unstructured Exhibit 21 attachement, which describes the ownershp relationships between the parent company and its subsidiaries. This data is used to create a linkage between EIA utilities and SEC reporting companies, to better understand the relationships between utlities and their affiliates, and the resulting economic and political impacts.

This data was originally downloaded from the SEC and processed using a machine learning pipeline found here: https://github.com/catalyst-cooperative/mozilla-sec-eia Archived from https://www.sec.gov/search-filings/edgar-application-programming-interfaces

This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into Frictionless Data Packages. For additional information about this data and PUDL, see the following resources:

The PUDL Repository on GitHub

PUDL Documentation

Other Catalyst Cooperative data archives

A dataset of public corporate filings (such as annual reports, quarterly reports, and ad-hoc disclosures) for SEC co.,ltd. (081180), provided by FinancialReports.eu.

LSEG global Filings offers extensive coverage of developed and emerging markets, updated in real time. Discover the data.

United States Financial Institutions: sa: CR: LL: RT: CO: Sec by Nonfarm data was reported at 61.917 USD bn in Jun 2019. This records an increase from the previous number of 59.398 USD bn for May 2019. United States Financial Institutions: sa: CR: LL: RT: CO: Sec by Nonfarm data is updated monthly, averaging 57.691 USD bn from Jan 2015 (Median) to Jun 2019, with 54 observations. The data reached an all-time high of 61.917 USD bn in Jun 2019 and a record low of 30.497 USD bn in Jan 2015. United States Financial Institutions: sa: CR: LL: RT: CO: Sec by Nonfarm data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s United States – Table US.KB042: Balance Sheet: Foreign Related Institutions: Monthly.

This dataset is from the SEC's Financial Statements and Notes Data Set.
It was a personal project to see if I could make the queries efficient.
It's just been collecting dust ever since, maybe someone will make good use of it.
Data is up to about early-2024.
It doesn't differ from the source, other than it's compiled - so maybe you can try it out, then compile your own (with the link below).
Dataset was created using SEC Files and SQL Server on Docker.
For details on the SQL Server database this came from, see: "dataset-previous-life-info" folder, which will contain: - Row Counts - Primary/Foreign Keys - SQL Statements to recreate database tables - Example queries on how to join the data tables. - A pretty picture of the table associations. Source: https://www.sec.gov/data-research/financial-statement-notes-data-sets

Happy coding!

Korea Securities Co: Assets: Loans: Sec Purchase Under Reversed Repurchase data was reported at 3,259.850 KRW bn in Mar 2018. This records an increase from the previous number of 2,844.379 KRW bn for Dec 2017. Korea Securities Co: Assets: Loans: Sec Purchase Under Reversed Repurchase data is updated quarterly, averaging 1,241.415 KRW bn from Jun 2007 (Median) to Mar 2018, with 44 observations. The data reached an all-time high of 3,343.601 KRW bn in Sep 2017 and a record low of 121.900 KRW bn in Jun 2007. Korea Securities Co: Assets: Loans: Sec Purchase Under Reversed Repurchase data remains active status in CEIC and is reported by Financial Supervisory Service. The data is categorized under Global Database’s Korea – Table KR.KB021: Balance Sheet: Securities Companies.

The set contains data on the results of the financial activity of the SEC "CPMSD 3" in Kremenchuk, namely: financial reports of a small enterprise according to the established reporting periods, data on business trips of employees with an indication of the number of business trips and the amount of whirlpools for them, including the business trip of the head