# Banking Email Scraper (`contacts-api/banking-email-scraper`) Actor Banking email scraper to extract verified banking emails from bank websites, directories, and financial listings 📧🏦 Perfect for B2B outreach, partnerships, and financial services lead generation. Fast, accurate, and reliable. - **URL**: https://apify.com/contacts-api/banking-email-scraper.md - **Developed by:** [Lead Heaven](https://apify.com/contacts-api) (community) - **Categories:** Lead generation, Automation, Other - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $9.99/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period. You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#rental-actors ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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. - **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use). - **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`. - **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`. - **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`. - **Any other language** — 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 ### ⭐ Banking Email Scraper — Build Targeted Banking Email Lists Fast 🤖 Banking Email Scraper is a specialized lead-generation tool that discovers banks and financial institutions in your target locations and extracts public contact data like emails, phone numbers, and social profiles. Powered by location-aware search, it scans Google Maps results for “Banking” (or any niche you enter), crawls company websites, and compiles a clean banking email list you can plug directly into outreach, sales, and partnerships. The best part? Enter your search term (e.g., “Banking”), choose one or more locations (e.g., “Miami, Florida”), set how many companies you want, and let the banking email finder deliver verified Banking emails and phone numbers at scale. — ### 📩 What can the Banking Email Scraper extract? Below is a quick breakdown of the data types this Banking email scraper can deliver ⬇️ | Data Type 📊 | Description | | ----------------------- | ------------------------------------------------------------- | | Business Name | Official company name from the listing | | Website | Primary website URL | | Emails | Public Banking emails discovered on the site | | Phone | Main phone found from listing or site | | Social Media | Detected LinkedIn, Twitter/X, Facebook, Instagram, etc. | | Full Address | Complete street address | | City, State, ZIP | Parsed location components | | Country Code | ISO country code (e.g., US) | | Average Rating | Google rating where available | | Total Reviews | Review count | | Latitude, Longitude | Geo coordinates | | Place ID | Google Maps place identifier | | Pages Scraped | Number of pages scanned on the website | | Emails Found (#) | Total count of emails detected | | Scrape Status | Status for each record (completed, partial, etc.) | Tip: Perfect for building niche-targeted Banking leads with clean structure for CRM or automation. — ### 🧩 Input Parameters #### Example Input JSON ```json { "googleMapsSearchTerm": "Banking", "googleMapsLocation": ["Miami, Florida", "Tampa, Florida"], "maxBusinesses": 25, "scrapeMaxBusinessesPerLocation": true, "proxyConfiguration": { "useApifyProxy": true } } ``` #### Input Parameters Table | Parameter | Description | | --------------------------------- | ------------------------------------------------------------------------------------------------------------------------------- | | googleMapsSearchTerm | Business type or niche to search (e.g., “Banking”, “credit unions”, “investment banks”). | | googleMapsLocation | One or more target locations (e.g., “Miami, Florida”, “New York, NY”). | | maxBusinesses | Maximum number of businesses with emails to collect (1–1000). Scraper stops at this target. | | scrapeMaxBusinessesPerLocation | If enabled, applies maxBusinesses per location; if disabled, combines all locations into a single total limit. | | proxyConfiguration | Configure proxies for reliability at scale; recommended for larger Banking leads campaigns. | — ### 📤 Output Format #### Example Output JSON ```json [ { "name": "First National Bank of Miami", "website": "https://www.fnbmiami.com/", "phone": "+1 305-555-0136", "full_address": "123 Brickell Ave, Miami, FL 33131, United States", "city": "Miami", "state": "FL", "zip": "33131", "country_code": "US", "scraped_emails": ["info@fnbmiami.com", "careers@fnbmiami.com"], "scraped_phones": ["+1 305-555-0136", "+1 305-555-0199"], "scraped_social_media": [ "https://www.linkedin.com/company/fnbmiami/", "https://twitter.com/fnbmiami" ], "emails_found": 2, "pages_scraped": 6, "avg_rating": 4.3, "total_reviews": 128, "lat": 25.7671, "long": -80.1903, "place_id": "ChIJ1aB3EXZy2YgR3fnbbq-EXAMPLE", "scrape_status": "completed" } ] ``` #### Output Fields Table | Field | Description | | ---------------------- | --------------------------------------------------------------------------- | | name | Business name | | website | Official website URL | | phone | Primary phone number | | full\_address | Complete address string | | city | City | | state | State or region | | zip | ZIP or postal code | | country\_code | Country code (e.g., US, CA, GB) | | scraped\_emails | Array of Banking emails discovered | | scraped\_phones | Array of phone numbers discovered | | scraped\_social\_media | Array of social profile links (LinkedIn, X/Twitter, Facebook, etc.) | | emails\_found | Total number of emails found | | pages\_scraped | Number of website pages scanned during discovery | | avg\_rating | Average Google rating | | total\_reviews | Total number of Google reviews | | lat | Latitude | | long | Longitude | | place\_id | Google Maps Place ID | | scrape\_status | Record status (e.g., completed, partial, no\_website, no\_emails) | — ### ⚙️ Key Features of the Banking Email Scraper ✨ - 🎯 Location + Niche Targeting\ Enter a niche like Banking, “credit union,” or “private bank,” and combine with any city or region to find precise Banking leads. - 🔎 Smart Banking finder and email discovery\ Automatically crawls likely contact pages, team pages, and footers to collect public Banking emails and phones. - 🌍 Multi-location scaling\ Add multiple locations and choose whether your limit applies per location or across all, ideal for regional Banking b2b leads. - 🧠 Banking email finder with social detection\ Captures LinkedIn and other social links for richer profiles and better outreach context. - 🛡️ Reliable, proxy-ready scraping\ Built-in proxy configuration improves stability for larger runs with thousands of Banking emails. - 📦 Clean, structured exports\ Get a ready-to-use banking email list in JSON or CSV for CRM import and marketing automation. - 🧩 Purpose-built Banking lead scraper\ Designed to streamline prospecting for banks, credit unions, and financial institutions—perfect for building Banking b2b leads pipelines. If you need a dependable Banking b2b email scraper that balances accuracy, speed, and scalability, this is your go-to Banking Email Scraper. — ### 🛠️ How to use the Banking Email Scraper (Step-by-Step) 📘 1. Log in to Apify\ Create a free account or sign in to your dashboard. 2. Select the Actor\ Search for “Banking Email Scraper” in the Apify Store. 3. Enter Search Term\ Example: “Banking” or “credit unions” (the Banking finder will use this to locate relevant businesses). 4. Add Locations\ Add one or many locations like “Miami, Florida”, “New York, NY”, or country-level regions. 5. Set Maximum Businesses\ Define how many companies with emails you want (e.g., 25). This limits the size of your banking email list. 6. Choose Per-Location Limit\ Enable “Scrape Max Businesses Per Location” if you want up to your limit per city. 7. Configure Proxies (optional but recommended)\ Keep Apify Proxy enabled for reliability on bigger Banking leads runs. 8. Run the Actor 🚀\ The Banking lead finder collects listings, visits websites, and extracts public contacts. 9. Download Results\ Export JSON/CSV and import your Banking emails into your CRM or outreach tools. — ### 🎯 Use Cases: What can you do with the Banking Email Scraper? - 💼 B2B Partnerships & Sales\ Build Banking b2b leads for software, compliance, audits, data vendors, or consulting services. - 📣 Marketing & Outreach\ Send targeted campaigns to decision-makers using a high-quality banking email list. - 🤝 Vendor & Integration Programs\ Identify regional banks or credit unions for product distribution and partnerships. - 🧭 Regional Expansion\ Quickly surface Banking leads in new cities or states for localized campaigns. - 🔎 Competitive & Market Research\ Map the landscape of banks in a region, including reviews and ratings, with your banking email list scraper. - 🧩 CRM Enrichment\ Add public emails, phones, and social links to existing records to boost engagement. A flexible Banking lead scraper for teams in sales, marketing, partnerships, and research. — ### 💎 Why choose us? Choosing our Banking Email Scraper gives you: - ⚡ Faster, reliable discovery with proxy-ready crawling - 🔍 Accurate Banking email finder logic focused on contact pages and footers - 🌐 Multi-location coverage for scalable Banking b2b leads - 📥 Clean exports for easy CRM and automation workflows - 🛡️ Public, compliant data collection practices - 🧠 Smart Banking finder that pulls social links for richer targeting - 🧰 The most practical banking email list scraper for repeatable, high-quality results If you’re building consistent Banking emails pipelines and need a stable Banking b2b email scraper, this tool is built for you. — ### 📊 How many results can you scrape with Banking Email Scraper? The scraper scales from small tests to large regional coverage: - Small campaigns: 10–100 businesses - Medium campaigns: 200–1,000 businesses - Large datasets: 2,000–10,000+ businesses across many locations Total results depend on: - Your googleMapsSearchTerm specificity (broader terms yield more Banking leads) - Number of locations (more locations = larger banking email list) - maxBusinesses limit you set - Whether you apply limits per location or across all - Availability of public emails on business websites Tip: For very large Banking b2b leads projects, break locations into batches and run with proxies enabled for best throughput. — ### ⚖️ Is it legal to scrape banking contact data? Scraping publicly available business information (e.g., company websites and listings) is generally legal when you: - Do not bypass authentication or paywalls - Do not collect private or sensitive personal data - Respect each website’s terms and applicable laws - Use the data ethically for legitimate B2B outreach This actor collects only public Banking emails and phone numbers that organizations publish. Always ensure your outreach complies with applicable regulations (e.g., GDPR, CAN-SPAM, and local data privacy laws). — ### ❓ FAQ — Banking Email Scraper 1. How does the Banking email finder locate emails?\ It crawls company websites discovered via Google Maps listings and scans likely pages (Contact, About, Team, Careers, Footer) to extract public Banking emails. 2. Can I target multiple cities at once?\ Yes. Add several locations in googleMapsLocation and choose whether maxBusinesses applies per location or as a combined total. 3. Do I need API keys?\ No extra keys are required. Just set your search term and locations and run the Banking lead finder. 4. Can it export a banking email list for my CRM?\ Yes. Download JSON or CSV from the dataset and import into your CRM or outreach tool. 5. Does it find social profiles?\ Yes. The Banking Email Scraper attempts to capture LinkedIn and other social links for richer contact context. 6. Is this a Banking b2b email scraper?\ Yes. It’s optimized for public, business-facing contact collection and Banking b2b leads. 7. Does it deduplicate emails?\ Outputs are normalized per business record. You can easily dedupe across runs using the website domain or place\_id. 8. What if a site has no public emails?\ You’ll still get core listing data (name, phone, address, rating). The scrape\_status will reflect partial results. — For any help or custom solution, contact via this mail: leadheavencontact@gmail.com # Actor input Schema ## `googleMapsSearchTerm` (type: `string`): Enter the business type or niche for email scraper (e.g., 'bank', 'credit union'). ## `googleMapsLocation` (type: `array`): Target geographic location for the email scraper (e.g., 'Miami, Florida'). ## `maxBusinesses` (type: `integer`): Target number of emails to find (1-1000). The scraper will stop when this target is reached. ## `scrapeMaxBusinessesPerLocation` (type: `boolean`): If enabled, the scraper will collect up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit. ## `proxyConfiguration` (type: `object`): Proxy settings for scraping. Recommended for large-scale scraping. ## Actor input object example ```json { "googleMapsSearchTerm": "Bank", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): Records produced by Banking Email Scraper, stored in the run's default dataset. # 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 = { "googleMapsSearchTerm": "Bank", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("contacts-api/banking-email-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 = { "googleMapsSearchTerm": "Bank", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("contacts-api/banking-email-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "googleMapsSearchTerm": "Bank", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }' | apify call contacts-api/banking-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,contacts-api/banking-email-scraper" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/v55Clt0HGaiS2h1XO/builds/V8edNGrR49EUSsJoU/openapi.json