# CFPB HMDA Lenders Scraper — Mortgage Lender Filing Database (`compute-edge/cfpb-hmda-lenders-scraper`) Actor Extract every U.S. mortgage lender that reported under the Home Mortgage Disclosure Act (HMDA) for a given year. Includes legal entity identifier (LEI), institution name, and total LAR record count. - **URL**: https://apify.com/compute-edge/cfpb-hmda-lenders-scraper.md - **Developed by:** [Compute Edge](https://apify.com/compute-edge) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## CFPB HMDA Lenders Scraper — U.S. Mortgage Lender Filing Database Pull the **complete list of U.S. mortgage lenders** that reported under the **Home Mortgage Disclosure Act (HMDA)** for a given year — over 5,000 banks, credit unions, and non-bank originators per filing year, ranked by loan-application record (LAR) count, with each institution's Legal Entity Identifier (LEI) and direct download links to their full LAR file. HMDA is the single most authoritative public dataset of U.S. mortgage lending. Every covered institution must report each loan application to the CFPB; the filer roster + LAR counts let you see who actually originated mortgages last year, who's gaining or losing share, and who has more than X loans worth of detail to mine downstream. ### What you get | Field | Description | |-------|-------------| | `year` | HMDA filing calendar year | | `lei` | 20-character Legal Entity Identifier (GLEIF) | | `name` | Reported institution legal name | | `loanCount` | Number of LAR records reported by this filer for the year | | `rank` | National rank (1 = largest filer by LAR count) | | `marketSharePct` | Filer's share of total LAR records that year | | `institutionUrl` | Deep link into the CFPB Data Browser for the institution | | `downloadAllRecordsUrl` | One-click CSV download of every LAR record this filer submitted | ### How to scrape HMDA mortgage lenders 1. Click **Try for free** to start a run with the default year (2023). 2. Optionally narrow by `nameFilter` (e.g. `"CHASE"`), `minLoanCount` (e.g. `1000`), or `maxResults`. 3. Run — the dataset comes back as JSON / CSV / Excel / Markdown. A typical 2023 pull returns ~5,100 lenders in under 30 seconds. ### Pricing $0.003 per lender row. A full year (~5,100 filers) costs roughly $15.30 in result fees plus minimal compute. Compute is billed separately by Apify. ### Example input ```json { "year": 2023, "nameFilter": "CREDIT UNION", "minLoanCount": 500, "maxResults": 0 } ```` ### Example output ```json { "year": 2023, "lei": "5493003GQDUH26DNNH17", "name": "NAVY FEDERAL CREDIT UNION", "loanCount": 173415, "rank": 6, "marketSharePct": 1.42, "institutionUrl": "https://ffiec.cfpb.gov/data-browser/data/2023?category=states&leis=5493003GQDUH26DNNH17", "downloadAllRecordsUrl": "https://ffiec.cfpb.gov/v2/data-browser-api/view/csv?years=2023&leis=5493003GQDUH26DNNH17" } ``` ### Use cases - **Mortgage industry sales/marketing** — Build TAM lists of lenders by size and segment. - **Vendor / fintech BD** — Prospect the long tail of small banks and credit unions actually originating mortgages. - **Bank M\&A research** — Identify share gainers/losers year over year. - **Academic / regulatory research** — Pair filer roster with LAR data for fair-lending and CRA studies. ### Other actors you might like - `fdic-banks-scraper` — FDIC-insured institution roster - `fdic-enforcement-actions-scraper` — FDIC enforcement actions - `sec-edgar-scraper` — SEC EDGAR filings - `treasury-fiscal-scraper` — Treasury fiscal data ### FAQ **Q: Where does the data come from?** A: The CFPB Data Browser public API (`ffiec.cfpb.gov/v2/data-browser-api/view/filers`). No login or key required. **Q: How do I get individual loan records, not just the lender list?** A: Each row includes a `downloadAllRecordsUrl` — that CSV contains every LAR record that filer submitted (rate, loan amount, applicant demographics, action taken, census tract, etc.). **Q: Why are some institution names ALL CAPS?** A: That's how lenders self-report to HMDA. Upper-case is normal. ### Legal Data comes from the public Consumer Financial Protection Bureau HMDA Data Browser. This actor is not affiliated with or endorsed by CFPB or FFIEC. Use of the data is subject to the public-domain terms of the CFPB. Loan-application records contain demographic data; if you re-publish raw LAR data you remain responsible for fair-lending and privacy compliance. # Actor input Schema ## `year` (type: `integer`): Calendar year of HMDA filings to retrieve. Defaults to a known-published year so empty input always returns data. ## `nameFilter` (type: `string`): Filter by lender name (case-insensitive partial match). Examples: 'CHASE', 'CREDIT UNION', 'WELLS FARGO'. ## `minLoanCount` (type: `integer`): Only include lenders with at least this many HMDA-LAR records for the year. 0 = include all filers. ## `maxResults` (type: `integer`): Maximum number of lenders to return. Set to 0 for unlimited. ## Actor input object example ```json { "year": 2023, "nameFilter": "", "minLoanCount": 0, "maxResults": 0 } ``` # Actor output Schema ## `dataset` (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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("compute-edge/cfpb-hmda-lenders-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 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); }); // 📚 Want to learn more 📖? Go to → 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 = {} # Run the Actor and wait for it to finish run = client.actor("compute-edge/cfpb-hmda-lenders-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call compute-edge/cfpb-hmda-lenders-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=compute-edge/cfpb-hmda-lenders-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "CFPB HMDA Lenders Scraper — Mortgage Lender Filing Database", "description": "Extract every U.S. mortgage lender that reported under the Home Mortgage Disclosure Act (HMDA) for a given year. Includes legal entity identifier (LEI), institution name, and total LAR record count.", "version": "0.1", "x-build-id": "SDgPUg8s8rfRiEX4j" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/compute-edge~cfpb-hmda-lenders-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-compute-edge-cfpb-hmda-lenders-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/compute-edge~cfpb-hmda-lenders-scraper/runs": { "post": { "operationId": "runs-sync-compute-edge-cfpb-hmda-lenders-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/compute-edge~cfpb-hmda-lenders-scraper/run-sync": { "post": { "operationId": "run-sync-compute-edge-cfpb-hmda-lenders-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "year": { "title": "HMDA Filing Year", "minimum": 2018, "maximum": 2030, "type": "integer", "description": "Calendar year of HMDA filings to retrieve. Defaults to a known-published year so empty input always returns data.", "default": 2023 }, "nameFilter": { "title": "Lender Name Filter", "type": "string", "description": "Filter by lender name (case-insensitive partial match). Examples: 'CHASE', 'CREDIT UNION', 'WELLS FARGO'.", "default": "" }, "minLoanCount": { "title": "Minimum Loan Count", "minimum": 0, "maximum": 1000000, "type": "integer", "description": "Only include lenders with at least this many HMDA-LAR records for the year. 0 = include all filers.", "default": 0 }, "maxResults": { "title": "Max Results", "minimum": 0, "maximum": 50000, "type": "integer", "description": "Maximum number of lenders to return. Set to 0 for unlimited.", "default": 0 } } }, "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 } } } } } } } } } } ```