🛡️ CFPB Consumer Complaints Scraper — Financial Compliance Intel

Pull complaints from the Consumer Financial Protection Bureau's public database. Filter by date, product, company, or state. Cleaner output than the raw CSV export, paginated, and rate-friendly. For fintech competitive intel, compliance teams, banking-sector journalism, and lawyers building CFPB-pattern cases.

📦 What you get per complaint

• complaint_id, date_received, date_sent_to_company
• product, sub_product, issue, sub_issue
• consumer_complaint_narrative (text, when consumer consented)
• company, state, zip_code
• company_response, company_public_response
• submitted_via, consumer_consent_provided
• timely_response, consumer_disputed, has_narrative
• tags

🎯 Use cases

1. Fintech competitive intel — track complaint volume on Robinhood, Cash App, Coinbase vs. legacy banks.
2. Compliance teams — monitor your own bank's complaint volume + response patterns by ZIP/state.
3. Banking-sector journalism — investigate spikes in complaint counts before earnings announcements.
4. Class-action lawyers — identify CFPB-pattern issues to build complaint clusters.
5. Bank M&A due diligence — review acquired-target's complaint history pre-close.
6. Academic research — empirical work on consumer-finance regulation effectiveness.

🚀 Quick start (JSON input)

{
  "dateFrom": "2025-01-01",
  "dateTo": "2025-01-15",
  "product": "",
  "company": "",
  "state": "",
  "maxComplaints": 200
}

💻 Code Example — Python SDK

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("nexgendata/cfpb-consumer-complaints-scraper").call(run_input={
    "dateFrom": "2025-01-01",
    "dateTo": "2025-01-31",
    "product": "Mortgage",
    "state": "CA",
    "maxComplaints": 500,
})
for c in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(c["date_received"], c["company"], c["issue"])

🌐 Code Example — cURL

curl -X POST "https://api.apify.com/v2/acts/nexgendata~cfpb-consumer-complaints-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"dateFrom":"2025-01-01","dateTo":"2025-01-15","product":"Credit card","maxComplaints":50}'

🔌 Integrations

• Zapier — Slack alerts when complaint volume on a watched company spikes.
• Make.com — daily aggregation into your fintech compliance dashboard.
• n8n — pipe into a private vector DB for narrative-based pattern matching.

💰 Pricing (pay per event)

• Actor Start: flat per-run fee (depends on memory).
• Complaint: charged once per complaint pushed to the dataset.

Cost example: 1,000 complaints ≈ 1,000 × per-complaint event + 1 start. Cheaper than building/maintaining your own CSV ingestion pipeline.

❓ FAQ

Q: How fresh is the data? CFPB updates the database daily. Records show up within ~24 hours of submission to CFPB.

Q: Why aren't all complaints showing a narrative? Only complaints where the consumer explicitly consented to publication include the consumer_complaint_narrative field. The has_narrative boolean tells you upfront.

Q: Can I search by ZIP code or city? This actor exposes state-level filtering directly. ZIP filtering is straightforward to add post-fetch from the returned zip_code field (CFPB redacts the last 2 digits for privacy).

Q: How do I find the exact company string for filtering? CFPB normalizes to all-caps legal names. Run a wide pull first, then filter by the company value you see (e.g. 'WELLS FARGO & COMPANY' not 'Wells Fargo').

Q: Bug reports? Open an issue on the Apify console — responses within 24 hours.

🔗 Related NexGenData Actors

• SEC Form 8-K Material Events Tracker
• SEC Form 4 Insider Trading Tracker
• FTC Enforcement Actions Scraper

🚀 Apify Affiliate Program

New to Apify? Sign up via our referral link — you get free platform credits on signup, and you help fund the maintenance of this actor fleet.

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