# SEC Financial Statements (Standardized) (`peak-app-rd/sec-financial-statements`) Actor

Ticker or CIK in, standardized annual income statement, balance sheet and cash flow out, from SEC EDGAR XBRL. Every line carries its source tag, accession and a confidence flag.

- **URL**: https://apify.com/peak-app-rd/sec-financial-statements.md
- **Developed by:** [Peak App Research and Development](https://apify.com/peak-app-rd) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 company fiscal years

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## SEC Financial Statements (Standardized)

Turn a ticker or CIK into standardized annual financial statements (income statement, balance
sheet and cash flow statement) built from the XBRL data companies file with the SEC in their
10-K reports. Every number traces back to the exact filing and XBRL tag it came from.

### What you get

One dataset item per company per fiscal year, up to 10 years back:

- **Income statement (15 lines):** revenue, cost of revenue, gross profit, operating expenses,
  total costs and expenses, operating income, interest expense, pretax income, income tax, net
  income attributable to the parent, net income including noncontrolling interests, the
  noncontrolling-interest share, basic and diluted EPS, diluted share count.
- **Balance sheet (9 lines):** cash and equivalents, current assets, total assets, current
  liabilities, total liabilities, long-term debt, temporary (mezzanine) equity, total equity,
  total liabilities and equity.
- **Cash flow (7 lines):** operating, investing and financing cash flow, capital expenditure,
  FX effect, net change in cash, and free cash flow.

Every line includes:

- `value` and `unit`
- `confidence`: `reported` (primary tag), `fallback` (alternate tag), `derived` (computed from
  other reported lines), or `missing`
- `tag`, `accession` and `filed`, so you can open the source filing on EDGAR

### How the numbers are built

- Restated figures replace originally reported ones. Each period is labelled with the fiscal
  year of the company's own 10-K.
- Companies change XBRL tags over time (for example, the 2024 taxonomy moved interest expense
  to a new tag). Each line checks a priority list of tags, and the output shows which one
  was used.
- Consistency checks are reported as warnings and never silently corrected. They cover: the
  balance sheet balances, liabilities + mezzanine + equity = assets, and the cash-flow
  sections sum to the net change in cash.
- The standardization logic is regression-tested against real filings from Apple, JPMorgan
  Chase, Caterpillar, Realty Income and Reddit. The values were checked by hand against the
  filed statements.

### Input

```json
{ "identifiers": ["AAPL", "JPM", "320193"], "years": 5 }
```

- `identifiers`: tickers or SEC CIK numbers, up to 500 per run. Duplicates are ignored.
- `years`: the most recent N annual periods per company (1–10, default 5).

### Output example

```json
{
  "ticker": "AAPL",
  "fiscal_year": 2025,
  "period_end": "2025-09-27",
  "income": {
    "revenue": {"value": 416161000000, "unit": "USD", "confidence": "fallback",
                "tag": "RevenueFromContractWithCustomerExcludingAssessedTax",
                "accession": "0000320193-25-000079", "filed": "2025-10-31"}
  },
  "warnings": []
}
```

### Pricing

Pay per event:

- **$0.00005 per run**: Apify's standard run-start event, which waives the first 5 seconds of
  compute
- **$0.01 per company fiscal year returned**

Five years of statements for one company costs about $0.05. Lookups that fail (unknown ticker, IFRS
filer) are returned as error items and are never charged. You can cap spend with the run's
maximum charge setting. The Actor stops cleanly when the cap is reached.

### Limits

- US-GAAP filers only. Foreign private issuers filing IFRS statements (Form 20-F) return an
  `unsupported_taxonomy` error.
- Annual (10-K) periods only; no quarterly data yet.
- Lines a company doesn't tag with a standard us-gaap element (for example, some industrials
  report interest expense only under their own custom tags) come back as `missing` rather than
  guessed.
- Data comes from SEC EDGAR's public XBRL API. Requests are rate-limited under SEC's fair-access
  policy, so very large batches take a few minutes.

# Actor input Schema

## `identifiers` (type: `array`):

US-GAAP filers only. Examples: AAPL, MSFT, 320193.

## `years` (type: `integer`):

Most recent N annual (10-K) periods. One result is billed per company-year returned.

## Actor input object example

```json
{
  "identifiers": [
    "AAPL"
  ],
  "years": 5
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "identifiers": [
        "AAPL"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("peak-app-rd/sec-financial-statements").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "identifiers": ["AAPL"] }

# Run the Actor and wait for it to finish
run = client.actor("peak-app-rd/sec-financial-statements").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "identifiers": [
    "AAPL"
  ]
}' |
apify call peak-app-rd/sec-financial-statements --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,peak-app-rd/sec-financial-statements"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/qWZcxzQA5kwEzUNHR/builds/bksaN3CM0UAtHCk4X/openapi.json