# SEC Executive Compensation Scraper: CEO Pay (`parselab/sec-executive-compensation-scraper`) Actor

Scrape CEO and executive pay from SEC DEF 14A annual meeting filings by ticker or across the market. Get CEO total pay, pay actually received, the average of other executives, CEO pay ratio, median employee pay and shareholder return against peers for each fiscal year. Export to CSV or Excel.

- **URL**: https://apify.com/parselab/sec-executive-compensation-scraper.md
- **Developed by:** [ParseLab](https://apify.com/parselab) (community)
- **Categories:** Business, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $22.50 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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 Executive Compensation Scraper: CEO Pay

This SEC executive compensation scraper reads the annual proxy statements of US public companies and turns the pay versus performance table into clean rows. For every fiscal year you get what the CEO was paid according to the summary compensation table, what the CEO was actually paid after stock awards are revalued, the average of the other named executives, the total shareholder return of the company and of its peer group, and the performance measure that the company says drives pay. A second view gives one row per company with the CEO pay ratio, the median employee pay and the history of the last five years.

Pay data is public, but it sits inside a proxy statement of hundreds of pages. Here the tagged numbers are read directly from the filing, so there is no table to copy by hand. A row carries the CEO name when the filing gives it, total pay and pay actually paid, the gap between them and the ratio, the average pay of the other executives and how many times the CEO earns more, the change of CEO pay against the year before, shareholder return of 100 dollars invested for the company and for peers and the difference, net income, the measure chosen by the company with its value, the list of performance measures that set pay, the CEO pay ratio, the median employee pay and the link to the proxy statement.

Journalists, compensation consultants, investors, governance and ESG analysts, unions and researchers use it to compare pay across companies and years and to check whether pay follows results.

### What can you do with this executive compensation scraper?

- See the CEO pay of a company for the last five fiscal years
- Compare the pay of CEOs across a list of companies
- Check how far pay actually paid is from the pay reported in the summary table
- Find companies where the CEO earns more than 500 times the median employee
- See whether CEO pay moved with shareholder return and against the peer group
- Read which performance measures the board uses to set pay
- Compare the pay of the CEO with the average of the other named executives
- Scan all proxy statements filed in the proxy season for high pay
- Follow the change of CEO pay from one year to the next
- Export compensation data to CSV or Excel, or send it to a dashboard

### What data can you extract from proxy statements?

| Mode | One row is | Highlights |
|---|---|---|
| Fiscal years | One company and fiscal year | Company, ticker, exchange, fiscal year and end date, CEO names and count, CEO total pay and pay actually paid, difference and ratio, all CEOs when there was a change, average total pay and actually paid pay of the other executives, CEO to others ratio, shareholder return of 100 dollars for the company and for peers, difference and return, net income, company selected measure and value, performance measures, change of CEO pay against the year before, CEO pay ratio and median employee pay for the latest year, text of the pay ratio sentence, named executives and peer group, proxy filing date and link |
| Companies | One company | Latest year, CEO names, total pay, actually paid pay and change, average of the other executives and the ratio, CEO pay ratio, median employee pay, shareholder return versus peers, cumulative CEO pay over the years covered, pay growth over the period, number of years where pay actually paid was above reported pay, selected measure, performance measures, and the full history by year |

### How to scrape executive compensation

1. Choose **Fiscal years** or **Companies**.
2. Enter tickers or CIK numbers, or leave them empty to scan the proxy statements of a date range.
3. Optionally set how many proxy statements to read per company, the fiscal years, a minimum CEO pay or a minimum pay ratio.
4. Set **Max Items** and click **Start**.
5. Export the dataset as CSV, Excel or from the Apify console.

### Input example

```json
{
  "mode": "companies",
  "tickers": ["AAPL", "MSFT", "NVDA", "JPM"],
  "maxItems": 50
}
```

### Fiscal year output example

```json
{
  "companyName": "MICROSOFT CORP",
  "ticker": "MSFT",
  "fiscalYear": 2025,
  "fiscalYearEnd": "2025-06-30",
  "ceoTotalCompUsd": 96496790,
  "ceoCompActuallyPaidUsd": 131138799,
  "ceoActuallyPaidMinusTotalUsd": 34642009,
  "ceoActuallyPaidToTotalRatio": 1.36,
  "otherExecutivesAvgTotalCompUsd": 24456053,
  "ceoToOtherExecutivesRatio": 3.95,
  "totalShareholderReturnIndexed": 255,
  "peerGroupReturnIndexed": 276,
  "returnVersusPeersPoints": -21,
  "netIncomeUsd": 101832000000,
  "companySelectedMeasure": "Microsoft Incentive Plan Revenue",
  "ceoTotalCompChangePct": 22,
  "ceoPayRatio": 480,
  "medianEmployeePayUsd": 200972,
  "proxyFiledOn": "2025-10-21"
}
```

### Company view example

```json
{
  "ticker": "NVDA",
  "ceoNames": ["Jen-Hsun Huang"],
  "latestFiscalYear": 2026,
  "ceoTotalCompUsd": 36343830,
  "ceoCompActuallyPaidUsd": 162180936,
  "ceoPayRatio": 129,
  "medianEmployeePayUsd": 282050,
  "fiscalYearsCovered": 5
}
```

### How much does it cost to scrape executive compensation?

You pay per result: $30 per 1,000 rows plus a tiny start fee. The free plan returns up to 10 rows per run. A company view is one row per company, so a list of 500 companies costs around fifteen dollars.

### Tips for better results

- The pay versus performance table has been required in proxy statements since 2022, so the data covers fiscal years from 2021.
- Total pay is the figure of the summary compensation table. Pay actually paid revalues stock and option awards to the end of the year, so it can be far above or below the reported pay.
- Shareholder return is shown as the value of 100 dollars invested at the start of the period. A value of 255 means a gain of 155 percent.
- When a company changed its CEO in a year, the row lists each CEO under the CEO list and uses the one with the highest pay for the main columns.
- A dash in the filing, such as a CEO who received no pay in a year, is returned as an empty value.
- The CEO pay ratio is read from the text of the proxy statement. Some companies word the sentence in a way the Actor cannot read, and then the ratio stays empty.
- Proxy statements are filed mostly from March to June. A scan outside that period returns few companies.
- Each proxy statement is a large document, so scans of many companies take time.

### Who uses executive compensation data?

- **Journalists** write about CEO pay and pay gaps.
- **Compensation consultants and boards** benchmark pay.
- **Investors and ESG analysts** check pay against results.
- **Unions and advocacy groups** track pay ratios.
- **Researchers** study the link between pay and performance.

### Automate and connect

Schedule the Actor after the proxy season and send the results to Google Sheets, Slack, Zapier, Make or n8n, or trigger a webhook when a run ends.

### FAQ

**Do I need an SEC account?**
No. The Actor works without any login.

**Where does the data come from?**
From the pay versus performance table that every US public company must publish in its annual proxy statement, read from the tagged data of the filing.

**Does it include salary, bonus and stock awards separately?**
Not in this version. It returns the total pay, the pay actually paid, the executive averages, shareholder return and the pay ratio.

**Why is the CEO name missing for some companies?**
Many companies do not tag the name of the CEO. The row still carries the numbers.

**Why is a company missing?**
New listings and companies that moved to a new holding company have no proxy statement under their ticker yet.

**Is this financial advice?**
No. Executive pay data is public information. Use it as one input among many.

### Legal note

This Actor collects information that is publicly visible on the website. Check the source site's terms and your local rules before using the data. Nothing here is financial advice.

### Support

Missing a field or found a bug? Open an issue from the Actor page.

# Actor input Schema

## `maxItems` (type: `integer`):

Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000.

## `mode` (type: `string`):

Fiscal years returns one row per company and fiscal year with the pay of the CEO, the pay actually received, the other executives and the shareholder return. Companies returns one row per company with the latest numbers, the CEO pay ratio, totals over the years and the history.

## `tickers` (type: `array`):

Tickers of the companies, for example MSFT, AAPL, JPM. Leave empty together with CIK numbers to read all proxy statements filed in the date range.

## `ciks` (type: `array`):

SEC company numbers, for companies without a ticker.

## `companyNames` (type: `array`):

Part of a company name. Used in the market scan (no tickers) to keep only proxy statements of companies whose name contains the text.

## `proxiesPerCompany` (type: `integer`):

How many of the latest annual proxy statements to read for each company. One statement covers up to five fiscal years, older statements add the earlier years again with their original numbers.

## `fiscalYearFrom` (type: `integer`):

Keep only fiscal years from this year on, for example 2023.

## `fiscalYearTo` (type: `integer`):

Keep only fiscal years up to this year.

## `minCeoPayUsd` (type: `integer`):

Keep only rows where the CEO total pay of the summary compensation table is at least this much, for example 20000000.

## `minPayRatio` (type: `number`):

Keep only companies where the CEO earns at least this many times the median employee, for example 300.

## `dateFrom` (type: `string`):

Market scan only. First filing date of proxy statements, YYYY-MM-DD. The default is 45 days ago. Most proxy statements are filed from March to June.

## `dateTo` (type: `string`):

Market scan only. Last filing date, YYYY-MM-DD. The default is today.

## `maxFilingsToScan` (type: `integer`):

Safety limit for how many proxy statements are read in a market scan. Each one is a large document.

## `includeText` (type: `boolean`):

Adds the sentence about the CEO pay ratio and the text about the named executives and the peer group.

## `contactEmail` (type: `string`):

Added to the request header as SEC fair access guidelines recommend. Leave empty if you prefer.

## Actor input object example

```json
{
  "maxItems": 10,
  "mode": "years",
  "tickers": [
    "MSFT"
  ],
  "proxiesPerCompany": 1,
  "maxFilingsToScan": 300,
  "includeText": true
}
```

# Actor output Schema

## `overview` (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 = {
    "maxItems": 10,
    "tickers": [
        "MSFT"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("parselab/sec-executive-compensation-scraper").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 = {
    "maxItems": 10,
    "tickers": ["MSFT"],
}

# Run the Actor and wait for it to finish
run = client.actor("parselab/sec-executive-compensation-scraper").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 '{
  "maxItems": 10,
  "tickers": [
    "MSFT"
  ]
}' |
apify call parselab/sec-executive-compensation-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,parselab/sec-executive-compensation-scraper"
        }
    }
}
```

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/nBmY6q2G0uUBkSdGI/builds/dP0REixf4BsDq3FO3/openapi.json