# FDIC BankFind Financials & Failed-Bank Tracker – Banking API (`deadwood_data_solutions/fdic-bank-financials-tracker`) Actor Structured FDIC BankFind feed of U.S. bank institutions, quarterly financials, branch data and failed-bank events. For fintech, bank analysts, vendors and competitive-intelligence teams. - **URL**: https://apify.com/deadwood\_data\_solutions/fdic-bank-financials-tracker.md - **Developed by:** [K O](https://apify.com/deadwood_data_solutions) (community) - **Categories:** Developer tools, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## FDIC BankFind Financials & Failed-Bank Tracker – Banking Data API An **FDIC BankFind API** wrapper and banking-data feed that pulls U.S. bank institution profiles, quarterly financials (assets, deposits, net income, ROA/ROE) and historical failed-bank events, normalizing each into a clean record. Use it to build a **bank intelligence tool**, a fintech onboarding/enrichment feed, a vendor market-sizing dataset, or bank-failure monitoring. ### Who uses it Fintechs enriching bank/partner data, bank and credit-union analysts, vendors selling into financial institutions, investors, and financial-journalism teams. ### Why this is worth charging for FDIC publishes rich institution and financial data via BankFind, but responses are nested (each row wrapped in a data object) and field codes are opaque. This actor normalizes institutions and failures into readable records with numeric financials, ready for enrichment, screening or monitoring. ### Output Each dataset item is one normalized record: ```json { "recordType": "institution", "cert": 3510, "name": "Example National Bank", "city": "Reno", "state": "NV", "totalAssets": 1250000, "totalDeposits": 980000, "netIncome": 15000, "returnOnAssets": 1.2, "returnOnEquity": 11.4, "established": "1985-06-01", "active": 1, "bankClass": "N", "branchCount": 12, "source": "FDIC BankFind" } ```` ### Input | Field | Description | |---|---| | `mode` | Query active/inactive institutions or the historical failed-bank list. | | `state` | Filter by state, e.g. NV. | | `searchName` | Full-text search on institution name. | | `activeOnly` | Institutions mode: only currently-active banks. | | `pageSize` | Rows per page. | | `maxPagesToScan` | Pages per run. | | `onlyNewSinceLastRun` | Recommended for schedules — skips records already returned by a previous run using persisted state, so you're only charged for genuinely new items. | | `maxItems` | Stop after this many normalized records. | ### Pricing (Pay-Per-Event) - **`query`** — $0.02, charged once per run for the API query/poll. - **`institution-record`** — $0.01 per normalized record pushed. This is the primary event. - `apify-actor-start` (Apify-managed) — covers baseline compute per run. A statewide institution pull returns dozens to hundreds of banks for a couple dollars. The failed-bank dataset is small and cheap to snapshot in full. ### Source & reliability Data comes from the official `banks.data.fdic.gov` BankFind API. Nested `data` wrappers are flattened and numeric fields coerced. No proxies required. Run `npm test` for the offline self-test covering the normalizer, including edge cases and missing-field handling. ### FAQ **Is there an API for FDIC bank data?** Yes — this actor wraps FDIC BankFind and returns clean institution and failed-bank records via the Apify API, webhook or export. **Can I get failed banks?** Yes. Set mode to 'failures' to pull the historical failed-bank list with acquirer and failure date. *** *SEO keywords: FDIC API, BankFind API, bank financial data, failed bank list, bank data scraper, financial institution enrichment* # Actor input Schema ## `mode` (type: `string`): Query active/inactive institutions or the historical failed-bank list. ## `state` (type: `string`): Filter by state, e.g. NV. ## `searchName` (type: `string`): Full-text search on institution name. ## `activeOnly` (type: `boolean`): Institutions mode: only currently-active banks. ## `pageSize` (type: `integer`): Rows per page. ## `maxPagesToScan` (type: `integer`): Pages per run. ## `maxItems` (type: `integer`): Stop after this many normalized records have been pushed. Leave blank for no limit (bounded by pagination settings). ## `onlyNewSinceLastRun` (type: `boolean`): Recommended for scheduled runs. Uses persisted state to skip records already returned earlier, so a recurring schedule only charges for genuinely new items. ## Actor input object example ```json { "mode": "institutions", "activeOnly": true, "pageSize": 100, "maxPagesToScan": 3, "onlyNewSinceLastRun": true } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("deadwood_data_solutions/fdic-bank-financials-tracker").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("deadwood_data_solutions/fdic-bank-financials-tracker").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call deadwood_data_solutions/fdic-bank-financials-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=deadwood_data_solutions/fdic-bank-financials-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "FDIC BankFind Financials & Failed-Bank Tracker – Banking API", "description": "Structured FDIC BankFind feed of U.S. bank institutions, quarterly financials, branch data and failed-bank events. For fintech, bank analysts, vendors and competitive-intelligence teams.", "version": "1.0", "x-build-id": "6zBAKdGkJuwNyyjf5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/deadwood_data_solutions~fdic-bank-financials-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-deadwood_data_solutions-fdic-bank-financials-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/deadwood_data_solutions~fdic-bank-financials-tracker/runs": { "post": { "operationId": "runs-sync-deadwood_data_solutions-fdic-bank-financials-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/deadwood_data_solutions~fdic-bank-financials-tracker/run-sync": { "post": { "operationId": "run-sync-deadwood_data_solutions-fdic-bank-financials-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "mode": { "title": "Dataset", "enum": [ "institutions", "failures" ], "type": "string", "description": "Query active/inactive institutions or the historical failed-bank list.", "default": "institutions" }, "state": { "title": "State (2-letter)", "type": "string", "description": "Filter by state, e.g. NV." }, "searchName": { "title": "Name search", "type": "string", "description": "Full-text search on institution name." }, "activeOnly": { "title": "Active institutions only", "type": "boolean", "description": "Institutions mode: only currently-active banks.", "default": true }, "pageSize": { "title": "Rows per page", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Rows per page.", "default": 100 }, "maxPagesToScan": { "title": "Max pages to scan", "minimum": 1, "maximum": 100, "type": "integer", "description": "Pages per run.", "default": 3 }, "maxItems": { "title": "Maximum records to return", "minimum": 1, "type": "integer", "description": "Stop after this many normalized records have been pushed. Leave blank for no limit (bounded by pagination settings)." }, "onlyNewSinceLastRun": { "title": "Only return records not seen in a previous run", "type": "boolean", "description": "Recommended for scheduled runs. Uses persisted state to skip records already returned earlier, so a recurring schedule only charges for genuinely new items.", "default": true } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```