US Banks & Credit Unions Scraper — Financials, Branches & B2B Leads

The only scraper that combines every U.S. bank and credit union in one dataset — ~4,000+ FDIC-insured banks and ~4,500+ NCUA-insured credit unions — with their financials, branches, and contact details, straight from official regulators.

For each institution you get: name, charter type & regulator, full address, phone (credit unions) or website (banks), total assets, deposits/shares, loans, net income, net worth, ROA, members & employees, branch count, year established, minority-depository status, an asset tier, and a 0–100 lead score — with filtering by state, asset size, type and charter, plus a monitoring mode for newly chartered institutions.

No login, no API key, no browser — just official open data from the FDIC and NCUA.

Why this scraper?

• Banks and credit unions, together. Every other tool covers only one regulator. This one merges FDIC banks and NCUA credit unions into a single, consistent schema — the complete U.S. depository-institution market in one run.
• Financial intelligence built in. Total assets, deposits/shares, loans, net income, net worth/equity, ROA, member counts and branch networks — qualify, segment and benchmark institutions by size and health.
• Contactable. Credit unions include a direct phone; banks include a website — plus a full mailing address for every institution.
• Lead score & asset tiers. A 0–100 score and asset tier weigh institution size, branch network and contactability so you can prioritize the highest-value targets.
• Monitoring mode. Run on a schedule and capture only institutions new since last time — newly chartered banks/credit unions or ones that newly match your filters.

Use cases

• Fintech & core-banking sales — vendors of core systems, digital banking, lending platforms, card processing, AML/BSA, and compliance prospect banks & credit unions by state, asset size and charter.
• Vendor & supplier targeting — anyone selling to financial institutions (marketing, ATMs, security, consulting, staffing) builds a clean, segmented prospect list with contact details.
• M&A & investment research — find acquisition targets and benchmark assets, net worth and ROA across institutions and states.
• Market & competitive analysis — size the market by region, charter and asset band; track the branch footprint.
• Risk & due diligence — verify charters, regulators, capital and minority-depository status.
• Monitoring new institutions — run on a schedule with monitoring mode to capture newly chartered banks and credit unions as fresh leads.

How to use

1. Sign up for Apify — the free plan is enough to try this actor.
2. Choose institution types (banks, credit unions, or both) and narrow with states, asset size, charter and branches.
3. Click Start and export the results.
4. Export as JSON, CSV, Excel, or XML — or pull results programmatically via the Apify API.

Input

{
  "institutionTypes": ["bank", "creditUnion"],
  "states": ["TX"],
  "assetMin": 100000000,
  "minBranches": 1,
  "sortBy": "assets",
  "maxResults": 100,
  "monitorMode": false
}

Key options:

• institutionTypes — bank (FDIC), creditUnion (NCUA), or both.
• states — two-letter state codes.
• nameQuery — institution name contains.
• assetMin / assetMax — total-asset range (in dollars).
• minMembers — credit-union member floor; minBranches — branch floor.
• charterTypes — charter-class codes (banks: N/NM/SM/SA/SB; credit unions: 1/2/3).
• activeOnly / withContactOnly — exclude closed banks; keep only institutions with a phone or website.
• sortBy — assets, leadScore, members, branches, or name.
• monitorMode / monitorKey — emit only institutions new since the last run.

Output

Each item is one institution. Example (credit union, trimmed):

{
  "recordType": "institution",
  "institutionType": "creditUnion",
  "name": "Amplify Credit Union",
  "regulator": "NCUA",
  "ncuaCharterNumber": "68001",
  "charterClassLabel": "State charter (federally insured)",
  "street": "4400 Amplify Way",
  "city": "Austin",
  "state": "TX",
  "zip": "78731",
  "addressFull": "4400 Amplify Way, Austin, TX 78731",
  "phone": "(512) 836-5901",
  "website": null,
  "totalAssets": 1300000000,
  "totalDeposits": 1050000000,
  "totalLoans": 1100000000,
  "netIncome": 9500000,
  "netWorth": 130000000,
  "netWorthRatio": 10.0,
  "returnOnAssets": 0.73,
  "members": 60000,
  "employees": 320,
  "branches": 6,
  "assetTier": "large ($1B–10B)",
  "yearEstablished": 1967,
  "isMinorityDepository": null,
  "leadScore": 84,
  "dataAsOf": "2025-12-31",
  "scrapedAt": "2026-06-20T00:00:00.000Z"
}

Banks add fdicCertNumber, website, equityCapital, returnOnEquity, and establishedDate; credit unions add members, potentialMembers, netWorthRatio, region and lowIncomeDesignated.

Automate & schedule

• Apify API — start runs, fetch datasets, and manage schedules over REST.
• Schedules — run quarterly (when NCUA publishes new Call Report data) or monthly with monitoring mode to capture newly chartered institutions.
• Webhooks — trigger downstream actions (CRM import, Slack alert, email sequence) the moment a run finishes.

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'MY_APIFY_TOKEN' });
const run = await client.actor('scrapesage/us-banks-credit-unions-scraper').call({
    institutionTypes: ['bank', 'creditUnion'],
    states: ['TX'],
    assetMin: 100000000,
    maxResults: 500,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Integrate with any app

• Make — multi-step automation scenarios.
• Zapier — push new institution leads straight into your CRM.
• Slack — get notified when a monitored watch finds new institutions.
• Google Drive / Sheets — auto-export every run to a spreadsheet.
• Airbyte — pipe results into your data warehouse.
• GitHub — trigger runs from commits or releases.

Use with AI assistants (MCP)

The output is clean, LLM-ready JSON. Call this actor from Claude, ChatGPT, or any agent framework through the Apify MCP server — ask your assistant to "list Texas credit unions over $500M in assets with their phone numbers" and let it run this scraper for you.

Agent-ready: autonomous payments (x402 & Skyfire)

This actor is agent-ready — AI agents can discover it, run it, and pay for it autonomously, with no Apify account and no human in the loop. It uses pay-per-event pricing and limited permissions, so it qualifies for Apify's agentic-payment standards:

• x402 — an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the Apify MCP server — no account, no API key.
• Skyfire — agent-to-service payments for fully autonomous AI-agent workflows.

Building an AI agent, MCP tool, or autonomous data pipeline? This scraper is ready to plug in and pay as it goes.

More scrapers from scrapesage

Build a complete U.S. B2B & financial-data lead stack:

• Financial Advisor Scraper — FINRA + SEC advisors & firms.
• BrokerCheck Scraper — advisors, brokers & firms with disclosures.
• SBA Loan Leads Scraper — SBA 7(a) & 504 financed small businesses.
• TaxBuzz Scraper — tax preparers, CPAs & accountant leads.
• Insurance Agent Scraper — local insurance agent leads.
• US Business Formation Scraper — newly-registered LLCs & companies.
• USAspending Scraper — federal awards, contractors & recipient leads.
• GSA eLibrary Scraper — federal contractors & B2B leads.

Tips

• Target by size. Set assetMin (e.g. $1B+) to focus on the institutions with the biggest technology and vendor budgets, or a assetMax to find community banks & small credit unions.
• Credit-union-only outreach. Set institutionTypes: ["creditUnion"] and withContactOnly: true — credit unions carry a direct phone number.
• Whole-market view. Leave both types selected and states empty for the complete U.S. depository-institution dataset (~9,000 institutions).
• Recurring monitoring. NCUA publishes new Call Report data quarterly; combine Schedules with monitorMode to capture newly chartered institutions.

FAQ

Where does the data come from? Banks come from the official FDIC BankFind Suite API; credit unions come from the official NCUA quarterly Call Report datasets. Both are public U.S. regulator sources — no login or API key required.

How current is it? FDIC data is updated continuously; NCUA Call Report data is published quarterly (about two months after each quarter end). Every credit-union record includes dataAsOf. The actor automatically uses the most recent NCUA quarter (or set ncuaQuarter).

Do I get a phone number? Yes for credit unions (from the institution's main office). Banks include a website and full address rather than a phone in the regulator data.

What financials are included? Total assets, deposits/shares, loans, net income, net worth/equity, ROA (and ROE for banks), plus member and employee counts and branch totals.

Can I export to Google Sheets, CSV, or Excel? Yes — one click in the dataset view, or automatically on every run via the Google Drive integration.

Need help?

Open an issue on the actor's Issues tab, or visit the Apify help center. Feature requests are welcome — this actor is actively maintained.