SBA Loan Leads Scraper — 7(a) & 504 Borrowers, Lenders & Industries

Turn the U.S. Small Business Administration's official loan data into ready-to-use B2B leads and lender intelligence. This actor extracts every approved SBA 7(a) and 504 loan — the borrower business name & full address, the industry (NAICS), the loan amount & approval date, the lender or CDC, jobs supported, franchise, business age, and loan status — and scores each one as a lead.

A business that just received an SBA loan is a high-intent buyer: it's financed, growing, and actively spending on equipment, software, insurance, marketing, real estate, and services. This is the cleanest way to find them.

No login, no API key, no browser — fast streaming extraction straight from official SBA open data (data.sba.gov), so it never breaks on anti-bot walls.

Why this SBA scraper?

Most "SBA" lists are stale snapshots or thin exports. This actor reads the live SBA FOIA datasets and ships the richest, most filterable record in the category:

Data	Typical lists	This actor
Borrower name + full street address	partial	✅
NAICS code and industry sector label	code only	✅
Gross approval, SBA-guaranteed amount & %	❌	✅
Approval date + first disbursement date	❌	✅
Lender bank (with FDIC #) / 504 CDC + third-party lender	❌	✅
Interest rate, type & term	❌	✅
Jobs supported	❌	✅
Business age (startup / new / existing)	❌	✅
Franchise name + flag	❌	✅
Loan status (normalized across programs)	raw codes	✅
Loan-size tier + lead score (0–100)	❌	✅
Filter by state, city, ZIP, county, NAICS, amount, date, lender…	❌	✅
Monitoring mode — only new loans since last run	❌	✅

Use cases

• Lead generation — find recently-financed small businesses by state, city, industry, and loan size. They're proven, growing buyers for equipment, POS/software, insurance, payroll, merchant services, commercial real estate, and B2B services. Sort by leadScore and work the freshest, biggest, most active first.
• Lender & competitive intelligence — track which banks and CDCs are originating loans, in which industries and states, at what volumes (lenderNameQuery, program, naicsCodes). Perfect for fintech, correspondent lenders, and capital markets teams.
• Franchise development — filter to franchisesOnly to see which franchise brands are expanding and where.
• Market research & economic analysis — analyze SBA lending by industry (NAICS), geography, business age, and time. Quantify small-business formation and capital flows.
• CRM enrichment & territory planning — pull borrower lists by ZIP/county to build call lists and size territories.
• Monitoring new borrowers — run on a schedule with monitoring mode to capture only loans added since your last run.

How to use

1. Sign up for Apify — the free plan is enough to try this actor.
2. Open the SBA Loan Leads Scraper, choose a program, a fiscal-year range, and any filters (state, industry, amount…), then click Start.
3. Watch results stream into the dataset table.
4. Export as JSON, CSV, Excel, or XML — or pull results programmatically via the Apify API.

Input

{
    "program": "7a",
    "fiscalYearFrom": 2024,
    "states": ["CA", "TX"],
    "naicsCodes": ["722"],
    "loanAmountMin": 100000,
    "businessAge": "startup",
    "loanStatuses": ["current", "paidInFull", "committed"],
    "maxResults": 1000,
    "sortNewestFirst": true,
    "monitorMode": false
}

• program — 7a (flagship general business loan, recommended), 504 (real-estate/equipment via CDCs), or both.
• fiscalYearFrom / fiscalYearTo — the SBA fiscal-year window (data goes back to FY1991). Lower fiscalYearFrom pulls more history and downloads more source files; the default (2022) keeps runs fast and focused on fresh borrowers.
• states / cities / zipCodes / counties — location filters on the borrower (USPS state codes, exact city names, full-or-prefix ZIPs, project counties).
• naicsCodes / industryKeywords — industry filters: NAICS code prefixes (e.g. 722 = restaurants, 23 = construction) or keywords against the industry description (e.g. dental, trucking).
• businessNameQuery / lenderNameQuery — substring filters on the borrower or the lending bank/CDC.
• loanAmountMin / loanAmountMax — gross approval range (USD).
• approvalDateFrom / approvalDateTo — exact date window (YYYY-MM-DD), finer than fiscal year.
• businessAge — startup, new (≤2 yrs), existing (>2 yrs), or changeOfOwnership.
• businessTypes — corporation/LLC, individual, partnership.
• loanStatuses — normalized statuses (current, paidInFull, committed, chargedOff, cancelled, …). For active businesses, pick current / paidInFull / committed.
• franchisesOnly — only franchise borrowers.
• minJobsSupported — minimum jobs reported (a size proxy).
• maxResults (default 1000) — cap on returned records.
• sortNewestFirst (default true) — return the most recently approved loans first.
• monitorMode / monitorKey — emit only loans new since the last run; use a distinct key per saved watch.

Output

One record per SBA loan (recordType: "loan"):

{
    "recordType": "loan",
    "program": "7(a)",
    "subprogram": "Guaranty",
    "loanId": "80415",
    "borrowerName": "Ricker Pharmacy",
    "borrowerStreet": "1801 BIG HORN AVE",
    "borrowerCity": "Worland",
    "borrowerState": "WY",
    "borrowerZip": "82401",
    "borrowerAddressFull": "1801 BIG HORN AVE, Worland, WY 82401",
    "grossApproval": 890000,
    "sbaGuaranteedApproval": 667500,
    "sbaGuaranteedPct": 75,
    "loanSizeTier": "large ($500K–2M)",
    "approvalDate": "2026-03-26",
    "approvalFiscalYear": 2026,
    "firstDisbursementDate": null,
    "processingMethod": "Preferred Lenders Program",
    "initialInterestRate": 8.75,
    "interestRateType": "Variable",
    "termInMonths": 120,
    "termInYears": 10,
    "naicsCode": "456110",
    "naicsDescription": "Pharmacies and Drug Retailers",
    "naicsSectorCode": "45",
    "naicsSector": "Retail Trade",
    "franchiseName": "Good Neighbor Pharmacy",
    "isFranchise": true,
    "projectCounty": "Washakie",
    "projectState": "WY",
    "businessType": "CORPORATION",
    "businessAge": "Change of Ownership",
    "businessAgeCategory": "changeOfOwnership",
    "loanStatus": "committed",
    "loanStatusLabel": "Committed",
    "jobsSupported": 6,
    "lenderName": "First Financial Bank",
    "lenderType": "Lender / Bank",
    "lenderFdicNumber": "28905",
    "lenderCity": "El Dorado",
    "lenderState": "AR",
    "leadScore": 77,
    "asOfDate": "2026-03-31",
    "scrapedAt": "2026-06-20T02:26:51.063Z"
}

504 records add cdc (Certified Development Company) details plus thirdPartyLenderName / thirdPartyLenderState / thirdPartyDollars in place of the bank fields.

Automate & schedule

Run this actor on autopilot and pull results into your own stack:

• Apify API — start runs, fetch datasets, and manage schedules over REST.
• apify-client for JavaScript and apify-client for Python — official SDKs.
• Schedules — run it weekly/monthly with monitoring mode to capture only newly-added borrowers as fresh leads.
• 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/sba-loan-leads-scraper').call({
    program: '7a',
    fiscalYearFrom: 2024,
    states: ['CA'],
    naicsCodes: ['722'],
    maxResults: 1000,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Got ${items.length} SBA loan leads`);

Integrate with any app

Connect the dataset to 5,000+ apps — no code required:

• Make — multi-step automation scenarios.
• Zapier — push new borrower leads straight into your CRM.
• Slack — get notified when a monitored watch finds new loans.
• 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 "find SBA-financed restaurants in California approved this year and list their lenders" 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 & government-data lead stack:

• US Business Formation Scraper — newly-registered LLCs & companies (fresh formation leads).
• SAM.gov Scraper — federal contract opportunities & contacts.
• USAspending Scraper — federal awards, contractors & recipient leads.
• FMCSA Trucking Scraper — motor carriers, authority & owner leads.
• US Federal Grants Scraper — Grants.gov, NIH & NSF funding.
• FEC Campaign Finance Scraper — donors, PACs & lobbying.
• TaxBuzz Scraper — tax preparers, CPAs & accountant leads.
• Financial Advisor Scraper — FINRA + SEC advisors & firms.

Tips

• Bigger history = bigger downloads. Each fiscal-year bucket is a separate source file. Keep fiscalYearFrom recent (e.g. last 2–3 years) for the freshest leads and the fastest runs; widen it only when you need history.
• Target an industry fast. Use naicsCodes prefixes (722 restaurants, 23 construction, 621 health care, 54 professional services) or industryKeywords for free-text matches.
• Find active businesses. Set loanStatuses to current, paidInFull, and committed to skip cancelled/charged-off loans, and sort by leadScore.
• Track a lender. Put a bank or CDC name in lenderNameQuery to watch a competitor's originations.
• Recurring monitoring. Combine Schedules with monitorMode and a distinct monitorKey per saved watch (e.g. per state/industry).

FAQ

Where does the data come from? The official SBA 7(a) & 504 FOIA datasets published on data.sba.gov. It's public-record government data; this actor downloads, parses, filters, normalizes, and scores it.

How fresh is it? SBA refreshes these datasets periodically (roughly quarterly). Every record includes asOfDate so you always know the data vintage. Run with monitorMode on a schedule to capture newly-added loans automatically.

Is there contact phone/email? SBA loan records contain the borrower business name and full mailing address, industry, and loan details — not phone or email. That's the strongest possible intent signal (a financed, growing business) and is easy to enrich with a phone/email tool or your CRM.

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.

How much does a run cost? You pay per loan record returned (no start fee). A run that scans the full dataset and returns a few hundred filtered leads costs only a few cents of platform compute plus the per-record price.

Is this legal? This actor collects publicly available U.S. government open data. You are responsible for using the data in compliance with applicable laws and SBA's terms.

A field is null — why? Some loans genuinely don't report a value (e.g. first-disbursement date for a just-committed loan, or franchise for a non-franchise). Fields are null only when the source doesn't provide them.

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.