--- # LATEST: https://huggingface.co/datasets/CyberMax-tools/riskroll-sec-10k-10q-sections/blob/main/latest.json (data date, refresh cadence, fresh API, licence links; also LATEST.md) # API (fresh data): https://data.cybermaxtools.com/buy/insidewell?s=hf-file-riskroll-sec-10k-10q-sections # Licence: cc0-1.0 (open, unchanged); commercial licence + support: https://data.cybermaxtools.com/buy/dataset-license?s=hf-file-riskroll-sec-10k-10q-sections license: cc0-1.0 pretty_name: 'Riskroll: SEC 10-K & 10-Q Risk Factors, MD&A and Market Risk Text (clean, by section)' language: - en tags: - finance - sec - edgar - 10-k - 10-q - risk-factors - mdna - annual-reports - financial-nlp - rag - text - corporate-filings - cybersecurity - cybermax task_categories: - text-classification - summarization - question-answering - text-retrieval size_categories: - 1K ![Riskroll: Read every new 10-K risk section in one place](https://cybermax-tools-cybermax.static.hf.space/brand/riskroll/banner.png) > **Need it fresh, filtered or via API?** This free file is a snapshot (10-K/10-Q sections up to the last refresh), last updated **2026-09-24**. > - **[Insidewell on Apify](https://data.cybermaxtools.com/buy/insidewell?s=hf-riskroll-sec-10k-10q-sections)** ($0.004 per insider transaction): pulls today's SEC Form 4 trades for your own watchlist, filtered by buy/sell and size, with cluster-buy alerts on a schedule. > - Using it at work? **[Commercial license + support](https://data.cybermaxtools.com/buy/dataset-license?s=hf-riskroll-sec-10k-10q-sections)** (from $49/year): invoice, PDF licence certificate, named support, freshness and availability commitments and an SLA; the data stays free and open for everyone. > - **[Get an email when this dataset updates](https://data.cybermaxtools.com/notify?ds=riskroll-sec-10k-10q-sections&s=hf-riskroll-sec-10k-10q-sections)**: free, double opt-in, unsubscribe any time. > - **[CyberMax Store](https://cybermaxtools.com/store/?utm_source=huggingface&utm_medium=dataset&utm_campaign=riskroll-sec-10k-10q-sections)**: every CyberMax data product, API plan and weekly brief in one place. > > *Information only, not investment advice.* The parts of annual and quarterly reports that analysts, researchers and LLM pipelines actually read, cut out of each filing and cleaned: **Risk Factors (Item 1A), Management's Discussion and Analysis (MD&A), Quantitative and Qualitative Disclosures About Market Risk, Cybersecurity (Item 1C) and Business (Item 1)**, one row per filing × section, for every 10-K and 10-Q filed with the SEC. New filings are added as they come in, so the corpus grows month by month. This build (see `meta.json`): **2,098 filings** (10-K, 10-Q and amendments) filed 2026-08-12 to 2026-09-23 (plus one filing dated 2026-02-23 that EDGAR indexed in September; 1,858 10-Q, 170 10-K, 67 amendments, 3 transition reports; the tail of the Q2 10-Q season plus fiscal-June annual reports), **5,245 sections**: 1,886 MD&A, 1,560 Risk Factors, 1,441 Market Risk, 185 Business and 173 Cybersecurity, 20.4 million words in total. 1,979 of the filings have at least one section (Part III-only amendments and exhibit-only filings have none, by design; 63 filings from the 12–14 Aug peak couldn't be fetched because SEC was throttling and are marked `sec_fetch_failed`; see `filings`). Why this and not the popular EDGAR corpora? The best-known 10-K section corpus on Hugging Face (EDGAR-CORPUS) was last updated in July 2023 and has annual reports only; full-filing dumps leave the section splitting to you. This one starts with 2026 filings, includes 10-Qs (quarterly MD&A and risk-factor updates) and the new Item 1C cybersecurity disclosures, and keeps adding filings. ![Riskroll: product image 1](https://cybermax-tools-cybermax.static.hf.space/brand/riskroll/image-1-output.png) ![Riskroll: product image 2](https://cybermax-tools-cybermax.static.hf.space/brand/riskroll/image-2-inside.png) ![Riskroll: product image 3](https://cybermax-tools-cybermax.static.hf.space/brand/riskroll/image-3-savings.png) ## Use it ```python from datasets import load_dataset ds = load_dataset("CyberMax-tools/riskroll-sec-10k-10q-sections", "sections", split="train") # Every risk-factor section that mentions tariffs risky = ds.filter(lambda r: r["section"] == "risk_factors" and "tariff" in r["text"].lower()) print(len(risky), risky[0]["company_name"], risky[0]["filing_url"]) ``` DuckDB, straight from the Hub: ```sql SELECT ticker, company_name, form_type, filed_date, n_words FROM 'hf://datasets/CyberMax-tools/riskroll-sec-10k-10q-sections/data/sections-*.parquet' WHERE section = 'cybersecurity' ORDER BY n_words DESC LIMIT 20; ``` Good for: RAG over company filings, risk-factor change tracking (compare a company's 10-K with its next 10-Qs), classifier and summarizer training/evaluation, sector-wide risk themes (AI, tariffs, cyber incidents, rates), and giving an AI agent the "why" behind the numbers. ## Configs and columns **`sections`** (default, one row per filing × section): `accession_number`, `form_type`, `filed_date`, `period_of_report`, `cik`, `ticker`, `company_name`, `section` (`risk_factors`, `mdna`, `market_risk`, `cybersecurity`, `business`), `item` (`1A`, `7`, `7A`, `1C`, `1` for 10-K; `II-1A`, `I-2`, `I-3` for 10-Q), `text`, `n_chars`, `n_words`, `filing_url` (EDGAR index page), `document_url` (the primary document the text came from). **`filings`** (one row per 10-K/10-Q filing in the window): the same identifiers plus `sections_found` and `status` (`ok`, `no_sections_found`, `no_html_primary_document`, `sec_fetch_failed`), so you can see exactly what was and wasn't extracted. How the text is made: the filing's primary HTML document is converted to text line by line (tables kept as `cell | cell` rows, page numbers and "Table of Contents" lines dropped). A section runs from its Item heading to the next Item heading; when a heading appears more than once (table of contents, cross-references), the occurrence with the longest body is used. Nothing is paraphrased or summarized. Smaller reporting companies often write "not required" under Market Risk; those short sections are kept as filed. Parsing is heuristic, so a small share of filings with unusual layouts can have a section missing or cut early; check `document_url` when it matters. ## Refresh New filings are added weekly from the SEC's daily indexes; files are per filing month (`data/sections-YYYY-MM.parquet`). `meta.json` has the latest build's window and counts. ## Licence SEC EDGAR filings are US government public records, free of copyright restrictions; this compilation is released under **CC0 1.0**. Compiled by **CyberMax**. Not affiliated with or endorsed by the SEC. Not investment advice. ## Also from CyberMax - [Insidewell: SEC Form 4 insider trading tracker](https://apify.com/cybermax/sec-insider-tracker): insider buys and sells for any watchlist of tickers, with cluster-buy flags, on demand or on a schedule, callable by AI agents over MCP. - Free dataset: [Figurewell: SEC XBRL financial statements and key metrics](https://huggingface.co/datasets/CyberMax-tools/figurewell-sec-xbrl-financials), the numbers for the same companies (join on `accession_number` = `adsh`, or on `ticker`). - Free dataset: [Eventwren: SEC 8-K material events by Item](https://huggingface.co/datasets/CyberMax-tools/eventwren-sec-8k-events). - Free dataset: [SEC Form 4 insider transactions, latest 5 EDGAR days](https://huggingface.co/datasets/CyberMax-tools/sec-form4-insider-transactions). - More tools for AI agents and data teams: https://apify.com/cybermax ## More free from CyberMax - [All free CyberMax demos & datasets](https://huggingface.co/spaces/CyberMax-tools/cybermax) - [Figurewell: SEC XBRL Financial Statements & Key Metrics (every US filer, latest 4 quarters)](https://huggingface.co/datasets/CyberMax-tools/figurewell-sec-xbrl-financials) - [Eventwren: SEC 8-K Material Events by Item (latest EDGAR filings)](https://huggingface.co/datasets/CyberMax-tools/eventwren-sec-8k-events) - [Insidewell: SEC Insider Trades](https://huggingface.co/spaces/CyberMax-tools/sec-insider-trades) ## Quickstart notebook Load this dataset with pandas and see real outputs in the [quickstart notebook](https://huggingface.co/datasets/CyberMax-tools/riskroll-sec-10k-10q-sections/blob/main/notebooks/quickstart.ipynb).