FDIC Bank Data Scraper: Assets, ROA, Deposits & Failures

Every FDIC-insured US bank with assets, deposits, equity, net income, ROA/ROE, regulator, holding company and offices, plus the full list of bank failures. $0.90 per 1,000 banks.

This FDIC BankFind scraper returns every FDIC-insured US bank and savings institution as one row each, with the latest call-report assets, deposits, equity, net income, ROA and ROE, plus the full list of bank failures since 1934. Filter by state, city, bank class or asset size and export to CSV, Excel or JSON, with no API key needed.

The FDIC's BankFind data covers every insured bank and savings institution in the United States, with balance-sheet figures from the latest quarterly call report. It is the authoritative source for sizing, ranking and tracking US banks, and it includes every bank failure since 1934.

Quick start

1. Press Start. The form is already filled with this example input, so the first run returns real rows in under a minute:

{
  "states": [
    "CA"
  ],
  "maxResults": 100
}

2. Swap in your own values, or call the Actor through the Apify API, Make, Zapier, n8n or the Python/JS clients with the same JSON.
3. Download the results as JSON, CSV or Excel from the Output tab, or schedule the run to repeat.

Full guide: How to Download FDIC Bank Data: Assets, ROA, ROE and Bank Failures by State (Real Run: Texas Banks Over $5 Billion)

What the FDIC Bank Data Scraper does

The Actor reads the FDIC's official BankFind Suite API (api.fdic.gov/banks), which is public and needs no key. It has two datasets:

• Institutions (dataset: "institutions"): one row per FDIC-insured bank or savings institution, with its FDIC certificate number, name, address, county and metro area, website, charter class, chartering agency and primary federal regulator, specialization, minority depository institution status, holding company, Federal Reserve RSSD ID and LEI, founding and insurance dates, number of offices, and the latest call-report financials: total assets, total and domestic deposits, equity capital, net income year to date and for the quarter, and return on assets and on equity (year to date and quarterly). Coordinates and a BankFind link are included.
• Failures (dataset: "failures"): one row per failed bank, with its certificate number, city and state, failure date and year, resolution and transaction type, charter class, insurance fund, the acquiring institution and its location, total assets and deposits at failure, and the FDIC's estimated loss with the date of that estimate.

You filter by name, state, city, certificate number, bank class, asset range and active status (and failure year for the failures dataset), and choose the sort order. Rows are fetched 500 at a time. Every row is a bank, a company, so there is no personal data in the output.

Who it is for

• Fintech and B2B sales teams selling to banks: build a target list by state, size band and charter, with the holding company and website on each row.
• Bank analysts and investors: compare profitability (ROA, ROE) and size across a state or peer group from the latest quarter.
• Compliance and KYC teams: confirm a bank's legal status, regulator, FDIC certificate, RSSD ID and LEI.

Real example 1: every Texas bank with $5 billion or more in assets

Say you sell software to large banks in Texas and want the full list of active banks headquartered there with at least $5 billion in total assets, largest first, with their profitability and holding company.

Step 1: Enter the input

Open the FDIC Bank Data Scraper in Apify Console, switch the input form to JSON and paste this. It is the exact input used for the run:

{
    "dataset": "institutions",
    "states": [
        "TX"
    ],
    "minTotalAssetsUsdThousands": 5000000,
    "activeOnly": true,
    "sortBy": "assets_desc",
    "maxResults": 25
}

What each setting does:

• dataset: institutions, the bank list. The other value is failures.
• states: TX, two-letter state codes of the main office. Add more to cover a region, for example ["TX", "OK", "LA"].
• minTotalAssetsUsdThousands: 5000000. FDIC amounts are in thousands of US dollars, so 5,000,000 means $5 billion. maxTotalAssetsUsdThousands sets an upper bound the same way; together they make a size band.
• activeOnly: true (the default) skips banks that have closed or merged.
• sortBy: assets_desc, largest first. The other options are deposits_desc, established_desc (newest charter first) and name.
• maxResults: 25, a cap on rows saved and so on cost.

Other filters on the form:

• bankNames: a name or part of one, such as community or savings. Each name runs as its own search.
• cities: city of the main office.
• certNumbers: exact FDIC certificate (CERT) numbers, for example 628 for JPMorgan Chase Bank.
• bankClasses: N national commercial banks (OCC-supervised), NM state non-member commercial banks, SM state Fed-member commercial banks, SB savings banks, SA savings associations, OI insured US branches of foreign banks and NC non-insured institutions. Empty means all.
• failedSinceYear: used by the failures dataset only.

Step 2: Run it

Press Start. The run finished with status SUCCEEDED in about 4 seconds and saved 20 rows: only 20 active Texas banks meet the $5 billion threshold, so the 25-row cap was not reached. It was charged 20 bank events plus the start event, $0.0181 on the Free/Bronze tier.

Step 3: Read the output

All 20 banks, with assets converted from thousands to billions for readability (the dataset keeps the FDIC's raw numbers):

name	city	bankClass	primaryRegulator	total assets	ROA %	ROE %	offices
Charles Schwab Bank, SSB	Westlake	SM	FED	$250.8B	1.33	18.03	1
Frost Bank	San Antonio	SM	FED	$54.0B	1.31	15.3	224
Prosperity Bank	El Campo	NM	FDIC	$43.9B	1.37	7.42	406
Texas Capital Bank	Dallas	SM	FED	$33.6B	1.03	9.55	10
Charles Schwab Premier Bank, SSB	Westlake	SM	FED	$26.6B	1.52	20.07	1
Sunflower Bank, National Association	Dallas	N	OCC	$15.7B	0.34	2.63	103
First Financial Bank	Abilene	SM	FED	$15.2B	1.77	15.35	84
NexBank	Dallas	NM	FDIC	$14.2B	1.05	12.13	2
PlainsCapital Bank	University Park	SM	FED	$12.7B	1.11	9.99	57
Charles Schwab Trust Bank	Westlake	SM	FED	$10.5B	2.05	27.48	1
Amarillo National Bank	Amarillo	N	OCC	$10.4B	1.76	16.07	35
International Bank of Commerce	Laredo	NM	FDIC	$10.2B	2.82	13.85	80
Woodforest National Bank	The Woodlands	N	OCC	$9.0B	2.05	24.22	741
Southside Bank	Tyler	NM	FDIC	$8.8B	1.35	10.98	58
TBK BANK, SSB	Dallas	SI	FDIC	$7.4B	0.63	4.16	62
Third Coast Bank	Humble	SM	FED	$6.7B	1.37	11.42	22
The American National Bank of Texas	Terrell	N	OCC	$5.5B	0.63	11.51	28
Broadway National Bank	San Antonio	N	OCC	$5.4B	1.74	20.65	31
City Bank	Lubbock	NM	FDIC	$5.4B	1.52	14.4	36
Vantage Bank Texas	San Antonio	SM	FED	$5.1B	1.64	18.91	23

One full row as JSON:

{
    "fdicCert": 5510,
    "name": "Frost  Bank",
    "active": true,
    "address": "111 W Houston St",
    "city": "San Antonio",
    "state": "TX",
    "stateName": "Texas",
    "zip": "78205",
    "county": "Bexar",
    "metroArea": "San Antonio-New Braunfels, TX",
    "website": "https://www.frostbank.com",
    "bankClass": "SM",
    "bankClassDescription": "Commercial bank, state charter, Fed member",
    "charterAgent": "STATE",
    "primaryRegulator": "FED",
    "specialization": "Commercial Lending Specialization",
    "minorityDepositoryInstitution": null,
    "holdingCompany": "CULLEN FROST BANKERS INC",
    "holdingCompanyCity": "SAN ANTONIO",
    "holdingCompanyState": "TX",
    "fedRssdId": "682563",
    "lei": "G5AHTAP80NWA3Q8RDC78",
    "established": "1899-02-20",
    "fdicInsuredSince": "1934-01-01",
    "closedOrMergedOn": null,
    "offices": 224,
    "domesticOffices": 222,
    "totalAssetsUsdThousands": 53950075,
    "totalDepositsUsdThousands": 43669523,
    "domesticDepositsUsdThousands": 43669523,
    "equityCapitalUsdThousands": 4659316,
    "netIncomeYtdUsdThousands": 349946,
    "netIncomeQuarterUsdThousands": 175946,
    "returnOnAssetsPct": 1.31,
    "returnOnEquityPct": 15.3,
    "returnOnAssetsQuarterPct": 1.32,
    "returnOnEquityQuarterPct": 15.33,
    "financialsAsOf": "2026-06-30",
    "latitude": 29.4268790164156,
    "longitude": -98.4956639998107,
    "bankFindUrl": "https://banks.data.fdic.gov/bankfind-suite/bankfind/details/5510"
}

What the 20 rows show:

• $551 billion in 20 banks, but very unevenly spread. Charles Schwab Bank, SSB in Westlake reports $250.8 billion, almost half the total, and Schwab has two more banks in the list (Charles Schwab Premier Bank and Charles Schwab Trust Bank), each with a single office. They hold large balances with almost no branches.
• Branch footprints differ by two orders of magnitude. Woodforest National Bank has 741 offices on $9.0 billion of assets, while Texas Capital Bank runs $33.6 billion through 10 offices. Prosperity Bank (406 offices) and Frost Bank (224) are the big branch networks.
• Profitability varies. Return on assets runs from 0.34% at Sunflower Bank to 2.82% at International Bank of Commerce in Laredo. Charles Schwab Trust Bank has the highest return on equity, 27.48%.
• Three federal regulators. 9 banks are state-chartered Fed members (SM, regulator FED), 5 are state non-members (NM, FDIC), 5 are national banks (N, OCC) and TBK Bank is a state savings institution (SI, FDIC). That matters if you sell compliance software, because exam cycles and reporting differ by regulator.
• All financials are as of 2026-06-30 (financialsAsOf): year-to-date net income covers six months, the quarter fields April to June.

Real example 2: every US bank failure since 2020

The same Actor reads the FDIC's failure list. This is the input used for the second run:

{
    "dataset": "failures",
    "failedSinceYear": 2020,
    "maxResults": 25
}

failedSinceYear keeps failures in or after that year. On the failures dataset, states, cities, certNumbers and the asset range also work; activeOnly, bankClasses and sortBy do not apply, and rows always come newest failure first.

The run finished in about 3 seconds with 17 rows (17 failures since 2020, under the cap), charged 17 bank events plus the start event: $0.0154 on Free/Bronze. All 17:

name	city, state	failureDate	transactionType	acquiringInstitution	total assets	estimated loss
SMALL BUSINESS BANK	Lenexa, KS	2026-07-17	PA	THE FARMERS STATE BANK OF OAKLEY, KANSAS	$72.9M	$5.7M
KENTLAND FS&LA	Kentland, IN	2026-07-10	PA	KENTLAND BANK	$3.8M	$1.2M
COMMUNITY BANK AND TRUST - WEST GEORGIA	Lagrange, GA	2026-05-01	PI	ANCHOR BANK	$305.7M	$97.3M
METROPOLITAN CAPITAL B&T	Chicago, IL	2026-01-30	PA	FIRST INDEPENDENCE BANK	$261.2M	$19.6M
SANTA ANNA NATIONAL BANK	Santa Anna, TX	2025-06-27	PI	COLEMAN COUNTY STATE BANK	$76.9M	$9.8M
PULASKI SAVINGS BANK	Chicago, IL	2025-01-17	PA	MILLENNIUM BANK	$49.5M	$31.9M
FIRST NB OF LINDSAY	Lindsay, OK	2024-10-18	PI	FIRST BANK & TRUST CO.	$107.8M	$45.1M
REPUBLIC BANK	Philadelphia, PA	2024-04-26	PA	FULTON BANK, NATIONAL ASSOCIATION	$5.9B	$709.6M
CITIZENS BANK	Sac City, IA	2023-11-03	PA	IOWA TRUST & SAVINGS BANK	$60.4M	$12.5M
HEARTLAND TRI-STATE BANK	Elkhart, KS	2023-07-28	PA	DREAM FIRST BANK,NATIONAL ASSOCIATION	$139.4M	$42.7M
FIRST REPUBLIC BANK	San Francisco, CA	2023-05-01	PA	JPMORGAN CHASE BANK, N.A.	$212.6B	$15.5B
SIGNATURE BANK	New York, NY	2023-03-12	PA	FLAGSTAR BANK, N.A.	$110.4B	$0
SILICON VALLEY BANK	Santa Clara, CA	2023-03-10	PA	FIRST-CITIZENS BANK & TRUST COMPANY	$209.0B	$18.7B
ALMENA STATE BANK	Almena, KS	2020-10-23	PA	EQUITY BANK	$65.7M	$15.9M
FIRST CITY BANK OF FLORIDA	Fort Walton Beach, FL	2020-10-16	PA	UNITED FIDELITY BANK, FSB	$136.6M	$7.2M
THE FIRST STATE BANK	Barboursville, WV	2020-04-03	PA	MVB BANK, INC	$151.8M	$43.7M
ERICSON STATE BANK	Ericson, NE	2020-02-14	PA	FARMERS AND MERCHANTS BANK	$100.9M	$23.3M

What it shows:

• No failures in 2021 or 2022, five in 2023 and four so far in 2026, the most recent being Small Business Bank in Lenexa, Kansas on 17 July 2026.
• 2023 was about size, not count. First Republic Bank ($212.6 billion in assets, acquired by JPMorgan Chase Bank), Silicon Valley Bank ($209.0 billion, First-Citizens Bank & Trust) and Signature Bank ($110.4 billion, Flagstar Bank) account for most of the assets in the list. The estimated losses for First Republic and Silicon Valley Bank are $15.5 billion and $18.7 billion. Signature Bank's estimated loss field is 0 in the FDIC data at this date, so check BankFind before quoting it.
• Resolution. 14 of the 17 were PA (purchase and assumption: another bank took over deposits and some assets) and 3 were PI (purchase and assumption of insured deposits only). The estimatedLossAsOf date (2026-07-31 here) tells you how current the loss estimate is.

Units, codes and the call report date

• All money fields are in thousands of US dollars, as the FDIC publishes them. Multiply by 1,000 for dollars. The field names end in UsdThousands so this is never ambiguous.
• Ratios are percentages. returnOnAssetsPct 1.31 means 1.31%.
• financialsAsOf is the call report date. Banks file call reports for each quarter and the FDIC publishes them a few weeks after quarter end, so the newest data is usually one quarter behind.
• The FDIC certificate number (fdicCert) is the stable ID of a bank in FDIC data. Use it to join runs over time or to look a bank up again with certNumbers. For failed banks, the same CERT links the failure to the bank's old institution record.

Output fields

Fields of the institutions dataset, with values from the Frost Bank row above:

Field	What it means	Example from this run
fdicCert	FDIC certificate number.	5510
name / active	Bank name and whether it is active.	Frost Bank / true
address / city / state / stateName / zip / county / metroArea	Main office address and area.	111 W Houston St / San Antonio / TX / Texas / 78205 / Bexar / San Antonio-New Braunfels, TX
website	Website as recorded by the FDIC.	https://www.frostbank.com
bankClass / bankClassDescription	FDIC charter class and its meaning.	SM / Commercial bank, state charter, Fed member
charterAgent / primaryRegulator	Who chartered it and its primary federal regulator.	STATE / FED
specialization	FDIC asset-concentration group.	Commercial Lending Specialization
minorityDepositoryInstitution	Minority depository institution status, when designated.	null
holdingCompany / holdingCompanyCity / holdingCompanyState	Top holding company.	CULLEN FROST BANKERS INC / SAN ANTONIO / TX
fedRssdId / lei	Federal Reserve RSSD ID and Legal Entity Identifier.	682563 / G5AHTAP80NWA3Q8RDC78
established / fdicInsuredSince / closedOrMergedOn	Charter date, insurance date and end date if inactive.	1899-02-20 / 1934-01-01 / null
offices / domesticOffices	Number of offices, total and in the US.	224 / 222
totalAssetsUsdThousands / totalDepositsUsdThousands / domesticDepositsUsdThousands / equityCapitalUsdThousands	Balance sheet, thousands of USD.	53950075 / 43669523 / 43669523 / 4659316
netIncomeYtdUsdThousands / netIncomeQuarterUsdThousands	Net income year to date and for the quarter.	349946 / 175946
returnOnAssetsPct / returnOnEquityPct / returnOnAssetsQuarterPct / returnOnEquityQuarterPct	ROA and ROE, year to date and quarterly.	1.31 / 15.3 / 1.32 / 15.33
financialsAsOf	Call report date of the financials.	2026-06-30
latitude / longitude	Main office coordinates.	29.4269 / -98.4957
bankFindUrl	The bank's page on FDIC BankFind.	https://banks.data.fdic.gov/bankfind-suite/bankfind/details/5510

Fields of the failures dataset, with values from the Small Business Bank row:

Field	What it means	Example from this run
fdicCert / name / city / state	The failed bank.	25744 / SMALL BUSINESS BANK / LENEXA / KS
failureDate / failureYear	When it failed.	2026-07-17 / 2026
resolutionType / transactionType	How it was resolved (for example PA or PI).	FAILURE / PA
charterClass / insuranceFund	Charter class at failure and the insurance fund.	SM / DIF
acquiringInstitution / acquirerCity / acquirerState	Who took over the bank.	THE FARMERS STATE BANK OF OAKLEY, KANSAS / OAKLEY / KS
totalAssetsUsdThousands / totalDepositsUsdThousands	Size at failure, thousands of USD.	72947 / 68773
estimatedLossUsdThousands / estimatedLossAsOf	FDIC estimated loss to the fund and the date of the estimate.	5671 / 2026-07-31
bankFindUrl	BankFind failures search for this CERT.	https://banks.data.fdic.gov/bankfind-suite/failures?searchTerm=25744

Both datasets also have scrapedAt, the time the row was read.

Export FDIC bank data to CSV, Excel or Google Sheets

Every run saves its rows to a dataset, and a dataset can be downloaded in any common format without code.

From Apify Console. Open the run, go to the Output tab and click Export. Pick CSV, Excel (XLSX), JSON, XML, HTML or RSS, and tick only the columns you want. Nested values such as lists and objects are flattened into columns like name/0 or object/field in CSV and Excel.

From a URL. The same export is a plain HTTPS link. Replace <DATASET_ID> with the dataset ID shown on the run's Storage tab:

# CSV with just the columns you need
curl -H "Authorization: Bearer $APIFY_TOKEN" \
  "https://api.apify.com/v2/datasets/<DATASET_ID>/items?format=csv&clean=1&fields=fdicCert,name,city,state,bankClass,primaryRegulator,holdingCompany,website,totalAssetsUsdThousands,totalDepositsUsdThousands,returnOnAssetsPct,returnOnEquityPct,offices,financialsAsOf" -o texas-banks.csv

# Excel
curl -H "Authorization: Bearer $APIFY_TOKEN" \
  "https://api.apify.com/v2/datasets/<DATASET_ID>/items?format=xlsx&clean=1" -o texas-banks.xlsx

Into Google Sheets. Three options, from simplest to most automatic:

1. One-off: download the CSV and use File > Import > Upload in Google Sheets. Choose "Replace current sheet" to refresh an existing tab.
2. Automatic, no code: use Make, Zapier or n8n as described in the next section, ending in a Google Sheets "Add row" step.
3. Formula: =IMPORTDATA("https://api.apify.com/v2/actor-tasks/<USERNAME>~<TASK_NAME>/runs/last/dataset/items?status=SUCCEEDED&format=csv&token=<YOUR_TOKEN>") always pulls the latest successful run of a saved task. The token sits in the formula, so anyone who can open the sheet can see it. Only use this in a private sheet.

In a spreadsheet, divide the UsdThousands columns by 1,000,000 to show billions.

Use it from Make, Zapier or n8n

All three automation tools have an official Apify app, so you can run this Actor and pass its rows on without writing code.

1. Trigger. Use a schedule in the automation tool, or Apify's "Watch Actor runs" / "Watch task runs" trigger if you already schedule the task in Apify.
2. Run. Add the Apify "Run Actor" (or "Run task") action, choose mrslm_data/fdic-bank-data and paste the JSON input from Step 1. Turn on "wait for finish" so the next step gets the data.
3. Get the rows. Add "Get dataset items" and map the run's default dataset ID from the previous step.
4. Send them on. Add a Google Sheets "Add row" step for a bank list, a HubSpot or Salesforce "Create or update company" step keyed on fdicCert or website, or a Slack message when the failures run returns a row with a failureDate you have not seen.

Each module only moves data; the Actor's pricing is the same as when you run it in Console.

Schedule a quarterly refresh

Call-report financials change once a quarter, so a quarterly run is enough for bank lists: for example in the middle of the second month after quarter end, when the FDIC has published the new data. For failures, a weekly run with failedSinceYear set to the current year shows any new failure within days.

1. In the Actor's input form, set up the input from Step 1 and click Save as new task. Give it a clear name such as tx-banks-quarterly.
2. Go to Schedules > Create new, set the cron expression to 0 7 15 2,5,8,11 * and pick your timezone, so it runs at 7 AM on the 15th of February, May, August and November.
3. Add the task to the schedule and save. Each run gets its own fresh dataset.
4. Optional: on the task's Integrations tab, add a webhook, Slack or email notification for "Run succeeded", or connect Make, Zapier or n8n, so the new rows go where you need them.

To fetch the newest results without looking up a run ID, use the task's last-run link: https://api.apify.com/v2/actor-tasks/<USERNAME>~tx-banks-quarterly/runs/last/dataset/items?status=SUCCEEDED&format=json.

Call it from the API (Python, JavaScript or curl)

Start the Actor from your own code with the official Apify clients. Put your API token (Console > Settings > API & Integrations) in an environment variable called APIFY_TOKEN rather than in the code.

Python (pip install "apify-client>=3"):

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run_input = {
    "dataset": "institutions",
    "states": [
        "TX"
    ],
    "minTotalAssetsUsdThousands": 5000000,
    "activeOnly": true,
    "sortBy": "assets_desc",
    "maxResults": 25
}

run = client.actor("mrslm_data/fdic-bank-data").call(run_input=run_input)

# apify-client 3.x returns a Run object, so use run.default_dataset_id
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item["name"], item["totalAssetsUsdThousands"], item["returnOnAssetsPct"])

In apify-client 3.x, call() returns a typed object. Older examples that use run["defaultDatasetId"] were written for 1.x and 2.x and fail in 3.x with TypeError: 'Run' object is not subscriptable.

JavaScript / Node.js (npm install apify-client):

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const input = {
    "dataset": "institutions",
    "states": [
        "TX"
    ],
    "minTotalAssetsUsdThousands": 5000000,
    "activeOnly": true,
    "sortBy": "assets_desc",
    "maxResults": 25
};

const run = await client.actor('mrslm_data/fdic-bank-data').call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, items[0].name);

curl, one request that runs the Actor and returns the rows as CSV (it waits up to 5 minutes, so keep the input small):

curl -X POST "https://api.apify.com/v2/acts/mrslm_data~fdic-bank-data/run-sync-get-dataset-items?format=csv" \
  -H "Authorization: Bearer $APIFY_TOKEN" -H "Content-Type: application/json" \
  -d '{"dataset": "institutions", "states": ["TX"], "minTotalAssetsUsdThousands": 5000000, "activeOnly": true, "sortBy": "assets_desc", "maxResults": 25}' -o texas-banks.csv

Use it from AI agents and chat assistants (MCP)

Apify runs a hosted Model Context Protocol (MCP) server, so assistants such as Claude Desktop, Cursor, VS Code or any other MCP client can call this Actor as a tool. Add this server URL to your MCP client and sign in with your Apify account (or send your API token as a Bearer header):

https://mcp.apify.com/?tools=mrslm_data/fdic-bank-data

The assistant then sees the Actor's input fields, can start a run with the input it builds from your request, and reads the dataset rows back. A prompt like this works well:

List the 20 largest active banks in Ohio by total assets from the FDIC, with their holding company, ROA and ROE, and the call report date.

Runs started through MCP are billed exactly like any other run, per row saved, so it is worth asking the assistant to set maxResults.

What it costs

The Actor uses pay-per-event pricing: one bank event per row saved, for both the institutions and the failures dataset, and nothing for compute.

Price per event

Event (per 1,000)	Free / Bronze	Silver	Gold / Platinum / Diamond
Bank record saved (institution or failure row) (bank)	$0.90	$0.81	$0.72
Actor start (once per run at the default memory, not per 1,000)	$0.00005	$0.00005	$0.00005

You are charged only for the events in this table: nothing for compute, and nothing for searches that return no rows beyond the start fee.

Scenario	Free / Bronze	Silver	Gold
Example 1 in this guide (20 Texas banks)	$0.0181	$0.0163	$0.0145
Example 2 in this guide (17 failures)	$0.0154	$0.0138	$0.0123
Every active bank in one large state, ~400 rows, quarterly	$0.36	$0.32	$0.29
Every active FDIC-insured institution in the US, ~4,500 rows	$4.05	$3.65	$3.24

The last two rows are estimates based on typical counts; the FDIC's own totals change every quarter. To cap spending, set Maximum cost per run in the run options (or maxTotalChargeUsd in the API), or use maxResults.

Tips

• Think in thousands. minTotalAssetsUsdThousands: 1000000 is $1 billion, not $1 million.
• Name searches are not sorted by size. When you use bankNames, the FDIC returns results by search relevance and sortBy is not applied. Sort in your sheet, or filter by state and assets instead.
• Use certNumbers for a watch list of customers or counterparties, and run it each quarter.
• Holding companies group banks. Charles Schwab owns three of the Texas banks above. Group by holdingCompany to count organisations rather than charters.

Limits

• Financials are those the FDIC publishes from call reports, usually one quarter behind.
• The Actor covers FDIC-insured institutions. Credit unions (NCUA), non-bank lenders and holding companies themselves are not rows.
• Failure loss estimates are the FDIC's and are revised over time; check estimatedLossAsOf.
• Branch-level data (each office's address and deposits) is not included, only the office counts.
• There is no date window input for institutions; each run is a snapshot of the current list.

FAQ

How do I list only large banks, or include closed ones? Set minTotalAssetsUsdThousands (for example 1000000 for banks with $1 billion or more in assets). Closed and merged banks are skipped by default; set activeOnly to false to include them.

Where does the data come from? From the official FDIC BankFind Suite API (api.fdic.gov), public and free without a key. Every row links to the bank's page on BankFind.

Why are the numbers so large? They are in thousands of US dollars, as the FDIC publishes them. 53950075 is $53.95 billion.

How fresh is it? Each run reads the API live. Financials follow the FDIC's quarterly call report releases; institution details and failures are updated by the FDIC as they happen.

Can I get only new bank failures? Set dataset to failures and failedSinceYear to the current year, and schedule it weekly. Compare fdicCert with your previous run to spot new rows.

Does it include credit unions? No. Credit unions are insured by the NCUA, not the FDIC.

Does it work with Make, Zapier or n8n? Yes. All three have an Apify app. Use "Run Actor" (or run a saved task), then "Get dataset items" to pass the rows on to Google Sheets, Airtable, a CRM or Slack.

Can AI agents use it? Yes, through Apify's MCP server at https://mcp.apify.com/?tools=mrslm_data/fdic-bank-data, as shown above.

Is it legal?

This Actor only reads official open-data APIs that the publisher offers to everyone without a login or key. It obeys robots.txt, stays under the published rate limits, and never tries to get past logins, paywalls, captchas or bot checks. Every row is a bank (a company). No data about individuals is read or output. You are responsible for how you use the data: follow the source's licence and terms and the privacy and marketing laws that apply to you (GDPR, CAN-SPAM, PECR, etc.). This tool is independent and not affiliated with or endorsed by the data publisher.