FDIC Failed Bank List Scraper

Extract structured failed-bank resolution records from the public FDIC Failed Bank List. This actor turns the official FDIC table into clean dataset rows with bank name, city, state, FDIC certificate, acquiring institution, closing date, fund number, source URL, and optional FDIC detail URL.

What does FDIC Failed Bank List Scraper do?

FDIC Failed Bank List Scraper collects records from the FDIC public bank failures page and exports them as structured JSON, CSV, Excel, XML, or HTML through Apify datasets.

Use it to monitor or analyze U.S. bank failures without manually copying table rows from FDIC.gov.

Who is it for?

• 🏦 Bank analysts tracking resolution history
• ⚖️ Compliance and risk teams checking failed-bank records
• 📰 Journalists researching bank failures and acquiring institutions
• 📊 Fintech data teams enriching regulatory datasets
• 🎓 Researchers studying banking-sector stress over time

Why use this scraper?

The FDIC page is authoritative, but the website table is not ideal for recurring workflows. This actor provides repeatable extraction, filters, API access, and export formats.

What data can you extract?

Field	Description
bankName	Failed institution name
city	Bank city
state	Bank state or territory
stateCode	Two-letter state code when known
cert	FDIC certificate number
fund	FDIC fund number
acquiringInstitution	Institution that acquired deposits/assets
closingDate	ISO closing date
closingDateText	Date as displayed by FDIC
detailUrl	FDIC detail page URL
sourceUrl	FDIC list URL used by the actor
scrapedAt	Extraction timestamp

How much does it cost to extract FDIC failed bank data?

This actor uses pay-per-event pricing: a small start fee plus a per-record fee for each saved failed-bank record. Apify shows the exact price before you run the actor.

How to run it

1. Open the actor on Apify.
2. Set the maximum number of failed-bank records.
3. Optionally add state or date filters.
4. Click Start.
5. Download results from the dataset tab.

Input options

Maximum failed-bank records

Set maxItems to control how many records are saved. The default is 100 so first runs stay inexpensive.

States to include

Use states to filter to state names or abbreviations, such as Georgia, CA, or Texas. Leave it empty for all states.

Closing-date range

Use closedFrom and closedTo in YYYY-MM-DD format to focus on a period, for example post-2008 failures or recent resolution activity.

Include detail URLs

Keep includeDetailUrls enabled if you want the FDIC detail page URL for each failed bank.

Example input

{
  "maxItems": 100,
  "states": ["Georgia", "California"],
  "closedFrom": "2008-01-01",
  "includeDetailUrls": true
}

Example output

{
  "bankName": "Community Bank and Trust - West Georgia",
  "city": "LaGrange",
  "state": "Georgia",
  "stateCode": "GA",
  "cert": "25796",
  "fund": "10551",
  "acquiringInstitution": "Anchor Bank",
  "closingDate": "2026-05-01",
  "closingDateText": "May 1, 2026",
  "detailUrl": "https://www.fdic.gov/bank-failures/failed-bank-list/community-bank-and-trust-west-georgia",
  "sourceUrl": "https://www.fdic.gov/bank-failures/failed-bank-list?items_per_page=All",
  "scrapedAt": "2026-07-05T00:00:00.000Z"
}

Tips for best results

• Start with the default maxItems before running the full historical list.
• Use state filters when building state-level market or compliance reports.
• Use date filters when comparing crisis periods or recent bank-resolution trends.
• Keep detail URLs enabled when analysts need source traceability.

Integrations

Use the dataset export in BI tools, notebooks, compliance dashboards, or internal enrichment pipelines. Apify integrations can send the dataset to Google Sheets, webhooks, cloud storage, or downstream automation.

API usage

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('automation-lab/fdic-failed-bank-list-scraper').call({
  maxItems: 100,
  states: ['Texas'],
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient

client = ApifyClient('YOUR_APIFY_TOKEN')
run = client.actor('automation-lab/fdic-failed-bank-list-scraper').call(run_input={
    'maxItems': 100,
    'states': ['Texas'],
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)

cURL

curl -X POST 'https://api.apify.com/v2/acts/automation-lab~fdic-failed-bank-list-scraper/runs?token=YOUR_APIFY_TOKEN' \
  -H 'Content-Type: application/json' \
  -d '{"maxItems":100,"states":["Texas"]}'

MCP usage

Connect this actor to Claude or other MCP clients through Apify MCP Server:

https://mcp.apify.com/?tools=automation-lab/fdic-failed-bank-list-scraper

Claude Code setup:

$claude mcp add apify-fdic-failed-banks https://mcp.apify.com/?tools=automation-lab/fdic-failed-bank-list-scraper

Claude Desktop JSON config:

{
  "mcpServers": {
    "apify-fdic-failed-banks": {
      "url": "https://mcp.apify.com/?tools=automation-lab/fdic-failed-bank-list-scraper"
    }
  }
}

Example prompts:

• "Extract FDIC failed banks in Georgia since 2008."
• "Get the latest 100 FDIC failed-bank records and summarize acquiring institutions."
• "Create a CSV of California failed banks with certificate numbers."

Monitoring workflow

Schedule the actor weekly or monthly to capture newly added FDIC failures. Because the source is public and small, scheduled runs are lightweight.

Compliance workflow

Risk teams can join the dataset against internal counterparty, branch, or institution datasets using FDIC certificate numbers and institution names.

Journalism workflow

Reporters can filter by state and date range, then use detail URLs for source attribution in stories about bank failures and acquisitions.

Data source

The source is the official FDIC failed bank list at FDIC.gov. The actor does not require a login and does not bypass access controls.

Limitations

The actor extracts fields visible in the FDIC failed bank list table. It does not scrape every detail page field in this version.

Legality

The actor collects publicly available government information from FDIC.gov. You are responsible for using the data lawfully and following applicable policies for your organization.

Troubleshooting

Why did I get fewer records than expected?

Check maxItems, states, closedFrom, and closedTo. Filters are applied after the FDIC table is fetched.

Why is detailUrl missing?

Set includeDetailUrls to true. A detail URL is included when the FDIC table row provides a link.

FAQ

Does this require proxies?

No. The actor uses direct HTTP requests to a public government page.

Can I export to CSV or Excel?

Yes. Use Apify dataset export formats after the run finishes.

Does it include active banks?

No. This actor focuses on failed-bank records. For active institution data, use related BankFind actors.

Related scrapers

• https://apify.com/automation-lab/fdic-bankfind-scraper
• https://apify.com/automation-lab/cfpb-complaints-scraper

Version

Initial version focused on the public FDIC failed bank list table.

Support

If you need more FDIC detail-page fields, open an Apify issue with an example record and the fields you need.