# CFTC Enforcement Actions Scraper (`automation-lab/cftc-enforcement-actions-scraper`) Actor Monitor CFTC enforcement actions, penalties, respondents, press releases, and linked orders for compliance research and due diligence. - **URL**: https://apify.com/automation-lab/cftc-enforcement-actions-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.02 / 1,000 enforcement action saveds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## CFTC Enforcement Actions Scraper Extract CFTC enforcement actions, press releases, respondents, penalties, and linked legal orders from the public Commodity Futures Trading Commission website. Use it to monitor regulatory action in futures, derivatives, commodities, retail commodity transactions, whistleblower awards, and related CFTC enforcement programs. ### What does CFTC Enforcement Actions Scraper do? CFTC Enforcement Actions Scraper collects structured records from the public CFTC enforcement actions index. It saves each enforcement action as a dataset item with the action date, title, CFTC release URL, release number, linked order documents, monetary amounts, respondent names when parseable, and press release summary text. The actor follows the CFTC year filter pages and can optionally open each press release detail page for richer text and amount extraction. ### Who is it for? - โš–๏ธ Compliance teams tracking CFTC enforcement trends. - ๐Ÿฆ Commodity, futures, swaps, and derivatives risk teams. - ๐Ÿ”Ž Due diligence analysts checking companies and individuals for regulatory history. - ๐Ÿง‘โ€โš–๏ธ Law firms monitoring new enforcement orders and settlements. - ๐Ÿ“Š Researchers building enforcement action timelines or penalty datasets. - ๐Ÿ“ฐ Journalists watching new CFTC press releases. ### Why use this scraper? The CFTC website is public, but manual monitoring is repetitive. This actor turns the enforcement index into exportable JSON, CSV, Excel, XML, or API data. You can run it on a schedule, filter by years or dates, and connect the dataset to alerts, dashboards, spreadsheets, or compliance review workflows. ### What data can you extract? | Field | Description | | --- | --- | | `releaseNumber` | CFTC release identifier when available. | | `title` | Enforcement action title. | | `dateIso` | Normalized action date. | | `year` | Publication year. | | `actionType` | Best-effort action category. | | `respondents` | Parsed respondents, defendants, or parties. | | `monetaryAmounts` | Dollar amounts mentioned in the source text. | | `penaltyTotalUsd` | Best-effort numeric sum of detected dollar amounts. | | `releaseUrl` | CFTC press release URL. | | `orderLinks` | Linked orders, PDFs, federal register notices, or downloads. | | `summaryText` | First substantive summary paragraph. | | `detailText` | Truncated press release body text. | | `scrapedAt` | Timestamp when the row was saved. | ### How much does it cost to scrape CFTC enforcement actions? This actor uses pay-per-event pricing. You pay a small start fee per run and a per-record fee for each enforcement action saved. A typical monitoring run for recent years is inexpensive because the CFTC index is static HTML and does not require a browser. See the Apify run pricing panel for the current tiered per-item price. ### Input options - `maxItems` limits how many enforcement actions are saved. - `years` selects specific CFTC year-filtered index pages. - `startUrls` lets you provide custom CFTC enforcement index URLs. - `fromDate` and `toDate` filter records by action date. - `includeDetails` follows press release pages for body text and richer amount extraction. - `includeOrderLinks` captures linked order and PDF URLs as metadata. ### Example input ```json { "maxItems": 100, "years": [2026, 2025, 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017], "fromDate": "2024-01-01", "includeDetails": true, "includeOrderLinks": true } ```` ### Example output ```json { "releaseNumber": "9263-26", "title": "CFTC Orders Two Foreign Firms to Pay $2.5 Million for Illegal Off-Exchange Transactions with U.S. Customers", "dateIso": "2026-06-29", "year": 2026, "actionType": "Administrative Order", "respondents": ["Netrios LP Ltd.", "Red Acre Ltd."], "monetaryAmounts": ["$2.5 Million", "$1.75 million", "$750,000"], "penaltyTotalUsd": 5000000, "releaseUrl": "https://www.cftc.gov/PressRoom/PressReleases/9263-26", "orderLinks": [ { "title": "Administrative Order: Netrios LP Ltd., Red Acre Ltd.", "url": "https://www.cftc.gov/media/14291/ENF_Netrios_RedAcreOrder062626/download", "type": "Administrative Order" } ] } ``` ### How to run it 1. Open the actor on Apify. 2. Choose the years or custom CFTC index URLs you want to monitor. 3. Set `maxItems` to the number of enforcement actions you need. 4. Keep detail enrichment enabled if you need summary text and penalty extraction. 5. Click **Start**. 6. Export the dataset or connect it through the Apify API. ### Tips for better results - Use `years` for broad historical collection. - Use `fromDate` for scheduled monitoring. - Set `includeDetails` to `false` for a faster title/date/link inventory. - Leave `includeOrderLinks` enabled if your workflow needs legal order PDFs. - Use a low `maxItems` for test runs, then increase it for production exports. ### Integrations You can connect this actor to: - ๐Ÿ“ฌ Email or Slack alerts for newly saved enforcement actions. - ๐Ÿ“ˆ BI dashboards tracking penalties by year. - ๐Ÿงพ Case-management systems used by legal and compliance teams. - ๐Ÿ” Due-diligence workflows that screen entities for regulatory exposure. - ๐Ÿ—‚๏ธ Document review pipelines that download linked orders after the actor saves metadata URLs. ### API usage with Node.js ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('automation-lab/cftc-enforcement-actions-scraper').call({ maxItems: 100, years: [2026, 2025, 2024], includeDetails: true }); console.log(run.defaultDatasetId); ``` ### API usage with Python ```python from apify_client import ApifyClient client = ApifyClient('YOUR_APIFY_TOKEN') run = client.actor('automation-lab/cftc-enforcement-actions-scraper').call(run_input={ 'maxItems': 100, 'years': [2026, 2025, 2024], 'includeDetails': True, }) print(run['defaultDatasetId']) ``` ### API usage with cURL ```bash curl -X POST "https://api.apify.com/v2/acts/automation-lab~cftc-enforcement-actions-scraper/runs?token=$APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"maxItems":100,"years":[2026,2025,2024],"includeDetails":true}' ``` ### MCP usage Use this actor from Claude Desktop, Claude Code, or another MCP-compatible client through Apify MCP. MCP tool URL: `https://mcp.apify.com/?tools=automation-lab/cftc-enforcement-actions-scraper` Claude Code setup: ```bash claude mcp add apify-cftc-enforcement https://mcp.apify.com/?tools=automation-lab/cftc-enforcement-actions-scraper ``` Claude Desktop JSON config: ```json { "mcpServers": { "apify-cftc-enforcement": { "url": "https://mcp.apify.com/?tools=automation-lab/cftc-enforcement-actions-scraper" } } } ``` Example prompts: - "Run the CFTC enforcement actions scraper for 2026 and summarize penalty amounts." - "Monitor CFTC enforcement actions since 2024-01-01 and list respondents." - "Extract linked consent orders from recent CFTC enforcement actions." ### Scheduling and monitoring For repeat workflows, create an Apify schedule with a recent `fromDate` and a modest `maxItems`. The dataset can be compared with previous runs by `releaseUrl` or `releaseNumber` to identify new CFTC actions. ### Data quality notes The CFTC source is a public Drupal website. Respondent names and penalty totals are best-effort parsed from titles, order labels, and press release text. Always review the source press release and linked order before making legal or compliance decisions. ### Limitations - The actor does not download or parse PDF contents. - Some older CFTC records may have different formatting. - `penaltyTotalUsd` can double-count if the press release repeats the same amount in multiple contexts. - `actionType` is inferred from text and linked document labels. ### Legality The actor collects public government web pages and public links. You are responsible for using the data lawfully, respecting Apify terms, and ensuring your downstream use complies with your internal policies and applicable regulations. ### FAQ #### Is it legal to scrape CFTC enforcement actions? The source pages are public CFTC government pages. Review your downstream use with your legal or compliance team if you combine the data with other screening systems. ### Troubleshooting #### Why did I get fewer records than expected? Check `maxItems`, `years`, `fromDate`, and `toDate`. The CFTC year filter returns a finite list for each selected year. #### Why is a respondent missing? Some CFTC titles do not name all parties in a consistent way. Enable `includeDetails` and inspect `detailText` or the linked order for complete legal names. #### Why is the penalty total different from the order? `penaltyTotalUsd` is a convenience field parsed from visible dollar amounts. Treat it as a screening aid, not a legal calculation. ### Related scrapers Explore other Automation Lab compliance and finance actors on Apify: - https://apify.com/automation-lab/ofac-sdn-watchlist-scraper - https://apify.com/automation-lab/sec-edgar-scraper - https://apify.com/automation-lab/finra-brokercheck-scraper ### Support If the CFTC website changes or you need another enforcement source, open an issue on the actor page with a sample URL and the fields you expect. ### Changelog Initial version extracts CFTC enforcement index records, press release detail text, order links, monetary amounts, and respondents. # Actor input Schema ## `maxItems` (type: `integer`): Maximum number of CFTC enforcement action records to save. ## `years` (type: `array`): Optional CFTC enforcement years to scrape. Leave empty to scrape recent years automatically. ## `startUrls` (type: `array`): Optional CFTC enforcement index URLs. Use this for custom year-filtered pages or archived pages. ## `fromDate` (type: `string`): Only include actions on or after this date (YYYY-MM-DD). ## `toDate` (type: `string`): Only include actions on or before this date (YYYY-MM-DD). Leave empty for no upper bound. ## `includeDetails` (type: `boolean`): Open each CFTC press release to extract release number, body summary, detailed text, and monetary amounts. ## `includeOrderLinks` (type: `boolean`): Collect linked administrative orders, consent orders, federal register PDFs, and downloads as metadata URLs. ## Actor input object example ```json { "maxItems": 20, "years": [ 2026, 2025, 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017 ], "startUrls": [ { "url": "https://www.cftc.gov/LawRegulation/Enforcement/EnforcementActions/index.htm?year=2025" } ], "fromDate": "2024-01-01", "includeDetails": true, "includeOrderLinks": true } ``` # Actor output Schema ## `overview` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "maxItems": 20, "years": [ 2026, 2025, 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017 ], "startUrls": [ { "url": "https://www.cftc.gov/LawRegulation/Enforcement/EnforcementActions/index.htm?year=2025" } ], "fromDate": "2024-01-01", "includeDetails": true, "includeOrderLinks": true }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/cftc-enforcement-actions-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "maxItems": 20, "years": [ 2026, 2025, 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017, ], "startUrls": [{ "url": "https://www.cftc.gov/LawRegulation/Enforcement/EnforcementActions/index.htm?year=2025" }], "fromDate": "2024-01-01", "includeDetails": True, "includeOrderLinks": True, } # Run the Actor and wait for it to finish run = client.actor("automation-lab/cftc-enforcement-actions-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "maxItems": 20, "years": [ 2026, 2025, 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017 ], "startUrls": [ { "url": "https://www.cftc.gov/LawRegulation/Enforcement/EnforcementActions/index.htm?year=2025" } ], "fromDate": "2024-01-01", "includeDetails": true, "includeOrderLinks": true }' | apify call automation-lab/cftc-enforcement-actions-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/cftc-enforcement-actions-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "CFTC Enforcement Actions Scraper", "description": "Monitor CFTC enforcement actions, penalties, respondents, press releases, and linked orders for compliance research and due diligence.", "version": "0.1", "x-build-id": "DK0Ffq8SjkZvXqpW8" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~cftc-enforcement-actions-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-cftc-enforcement-actions-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automation-lab~cftc-enforcement-actions-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-cftc-enforcement-actions-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automation-lab~cftc-enforcement-actions-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-cftc-enforcement-actions-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "maxItems": { "title": "Maximum enforcement actions", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of CFTC enforcement action records to save.", "default": 20 }, "years": { "title": "Years to scrape", "type": "array", "description": "Optional CFTC enforcement years to scrape. Leave empty to scrape recent years automatically.", "items": { "type": "integer", "minimum": 1995, "maximum": 2030 } }, "startUrls": { "title": "Custom CFTC index URLs", "type": "array", "description": "Optional CFTC enforcement index URLs. Use this for custom year-filtered pages or archived pages.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "fromDate": { "title": "From date", "type": "string", "description": "Only include actions on or after this date (YYYY-MM-DD)." }, "toDate": { "title": "To date", "type": "string", "description": "Only include actions on or before this date (YYYY-MM-DD). Leave empty for no upper bound." }, "includeDetails": { "title": "Follow press release detail pages", "type": "boolean", "description": "Open each CFTC press release to extract release number, body summary, detailed text, and monetary amounts.", "default": true }, "includeOrderLinks": { "title": "Include linked orders and PDFs", "type": "boolean", "description": "Collect linked administrative orders, consent orders, federal register PDFs, and downloads as metadata URLs.", "default": true } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```