# European Company Financials Database - North Data (`jungle_synthesizer/northdata-european-company-financials-scraper`) Actor

Extract European company records: registry identity, officers with appointment dates, multi-year published financials, merger and acquisition events, and register filings. Covers registers across Germany, Austria, Switzerland, UK, France, Benelux, and the Nordics.

- **URL**: https://apify.com/jungle\_synthesizer/northdata-european-company-financials-scraper.md
- **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community)
- **Categories:** Business
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.80 / 1,000 record scrapeds

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?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## European Company Financials Database — North Data Scraper

Pulls registry identity, officers, published financials, and merger history for European companies from North Data. Point it at a company name, register number, or officer name and it comes back with structured records instead of a PDF you have to read.

***

### European Company Financials Database Features

- Search by company name, national register number (HRB, KBO, Siren, CVR, ...), or officer name
- Returns registry identity — legal form, register court, register number, LEI, founding date, registered address
- Extracts a multi-year `financials` time series (revenue, profit, total assets, equity, employees) with the source publication cited per figure, not a single flattened "latest" number
- Pulls the officer roster with role and appointment date, and resignation date where the register recorded one
- Surfaces merger, acquisition, and control events as dated relations — the beginnings of a corporate-group picture, not just a contact card
- Parses the register's own dated event stream, so you get incorporations, capital changes, and — where present — insolvency and liquidation events
- Filter by country when a query matches entities across several jurisdictions

***

### Who Uses a European Company Financials Database?

- **KYB / AML analysts** — verify a counterparty's registry identity, officers, and group structure before onboarding
- **Credit and risk teams** — pull a company's multi-year revenue and profit trend instead of trusting a single self-reported figure
- **M\&A and PE screeners** — track a target's merger and acquisition history across jurisdictions in one pass
- **Sales and lead-gen teams** — build prospect lists with real registered addresses, legal forms, and officer names, not scraped contact pages
- **Journalists and researchers** — follow a company's register event history — capital changes, officer turnover, dissolutions — as a dated timeline

***

### How the North Data Scraper Works

1. Give it one or more search queries — a company name, a register number, or a person's name.
2. It works through the search results for each query, pulling every matching profile (or just the countries you specify).
3. For every match, it opens the profile page and parses the registry identity, the financial-performance chart, the officer timeline, and the merger/register event streams.
4. Everything comes back as one flat dataset row per company, with the multi-record fields (officers, financials, events) as JSON arrays inside their column.

***

### Input

```json
{
  "queries": ["Siemens AG"],
  "countries": ["Germany"],
  "maxItems": 50
}
```

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `queries` | array (required) | — | Company names, register numbers, or officer names to search |
| `countries` | array | none (all) | Restrict results to these countries — leave empty to keep every country a query matches |
| `maxItems` | integer | 10 | Maximum company records to save across all queries |

#### Resuming a large crawl

Every run emits a `resumeCursor` in its Output. If a large crawl stops before it finishes — because it hit `maxItems`, your spend cap (`maxTotalChargeUsd`), or was aborted — start a new run with **the same input** plus that `resumeCursor` to continue from where it left off. The crawl resumes from the queued work the previous run didn't reach.

- You are **not re-charged** for records the earlier run already delivered.
- Resume within your account's run-retention window — on the free tier, roughly your 10 most recent runs. Once the source run is pruned, its `resumeCursor` is no longer valid.
- `resumeCursor` is opaque — supply it unmodified.

***

### European Company Financials Database Output Fields

```json
{
  "northdata_url": "https://www.northdata.com/Siemens+AG,+M%C3%BCnchen/HRB+6684",
  "company_name": "Siemens AG",
  "legal_form": "AG",
  "country": "DE",
  "register_court": "District Court of Munich",
  "register_type": "HRB",
  "register_number": "6684",
  "lei": "W38RGI023J3WT1HWRP32",
  "status": "active",
  "founding_date": "1996-08-28",
  "address_street": "Werner-von-Siemens-Str. 1",
  "address_postcode": "80333",
  "address_city": "München",
  "share_capital_amount": 2350000000,
  "share_capital_currency": "EUR",
  "officers": "[{\"name\":\"Roland Busch\",\"role\":\"CEO\",\"appointed_on\":\"2021-03-12\"}]",
  "financials": "[{\"fiscal_year\":2025,\"revenue\":78914000000,\"profit\":9620000000,\"currency\":\"EUR\"}]",
  "revenue_latest": 78914000000,
  "fiscal_year_latest": 2025,
  "network_edges": "[{\"related_name\":\"Siemens Treasury GmbH\",\"relation\":\"merger\",\"since\":\"2025-05-12\"}]",
  "register_events": "[{\"event_date\":\"1996-08-28\",\"event_type\":\"Registration\"}]",
  "insolvency_events": "[]"
}
```

| Field | Type | Description |
|-------|------|--------------|
| `northdata_url` | string | Source profile URL for this company |
| `company_name` | string | Registered company name |
| `legal_form` | string | Legal form parsed from the name (GmbH, AG, SE, Ltd, SAS, BV, NV, ...) |
| `country` | string | ISO country code of the registered address |
| `register_court` | string | Register court / registering authority (sparse — jurisdiction-dependent) |
| `register_type` | string | Register type code (HRB, HRA, KBO, Siren, CVR, ...) |
| `register_number` | string | Register number within that register |
| `lei` | string | Legal Entity Identifier (sparse — not every company has one) |
| `vat_id` | string | VAT identification number (sparse) |
| `status` | string | `active` or `dissolved`, inferred from the register event stream |
| `founding_date` | date | Incorporation date |
| `dissolution_date` | date | Dissolution date, if a dissolution/liquidation event was found (sparse) |
| `address_street` / `address_postcode` / `address_city` | string | Registered address |
| `industry_code` / `industry_label` | string | Industry classification, where the register publishes one (sparse) |
| `business_purpose` | string | Corporate purpose as filed |
| `share_capital_amount` / `share_capital_currency` | number / string | Registered share or base capital, from the most recent dated capital event (sparse) |
| `officers` | JSON string | Array of `{ name, role, appointed_on, resigned_on }` |
| `financials` | JSON string | Array of `{ fiscal_year, revenue, total_assets, equity, profit, employees, currency, source }` — one entry per year with a published figure |
| `revenue_latest` / `total_assets_latest` / `equity_latest` / `employees_latest` / `fiscal_year_latest` | number | Convenience fields pulled from the most recent year in `financials` |
| `network_edges` | JSON string | Array of `{ related_name, related_url, relation, since, until }` — merger, acquisition, and control events |
| `register_events` | JSON string | Array of `{ event_date, event_type, text, source_gazette }` — the register's own dated event stream |
| `insolvency_events` | JSON string | Array of `{ event_date, court, file_number, event_type }` — events matched as insolvency, liquidation, or dissolution |

**A note on sparse fields.** North Data's coverage is dense for Germany and Austria and thinner elsewhere — a branch or subsidiary entry often has no financial-performance chart of its own, and some jurisdictions never publish a VAT ID or LEI. An empty array or `null` field there is an honest "not published," not a bug.

***

### FAQ

#### How do I search North Data with this scraper?

European Company Financials Database takes a `queries` array — company names, register numbers like `HRB 6684`, or officer names. It works through each query's results and pulls a full profile for every match, or just the countries you list in `countries`.

#### What financial data does it return?

European Company Financials Database returns a multi-year `financials` array per company — revenue, profit, and (where published) total assets, equity, and employee counts, each tagged with its fiscal year, currency, and source publication. It's a time series, not a single number from last quarter.

#### Does it need a North Data account or API key?

No. It runs against the public profile pages, so there's nothing to authenticate.

#### Can I filter results by country?

Yes. Pass a `countries` array and results outside those countries are skipped — useful when a company name matches entities in several jurisdictions at once, which happens more often than you'd think for a name like "Siemens."

#### Why are some fields empty on certain companies?

Because the register didn't publish them. A branch office rarely carries its own financial statements, and VAT IDs and LEIs aren't universal. See the note under Output Fields above.

***

### Need More Features?

Need a different jurisdiction filter, additional register fields, or a bulk mode built around a seed list from one of our national-register actors? [File an issue](https://console.apify.com/actors/issues) or get in touch.

### Why Use European Company Financials Database?

- **Actual financial statements** — a real multi-year `financials` array, not a lead-gen card that stops at the officer list
- **Federated across jurisdictions** — one profile schema for Germany, Austria, Switzerland, the UK, France, the Benelux countries, and the Nordics, so you're not stitching together a dozen national register scrapers
- **Honest about gaps** — sparse fields stay sparse instead of getting padded with a guess, which matters when the output feeds a risk model

# Actor input Schema

## `sp_intended_usage` (type: `string`):

What will this data feed? E.g. lead lists, KYB checks, price tracking.

## `sp_improvement_suggestions` (type: `string`):

Provide any feedback or suggestions for improvements.

## `sp_contact` (type: `string`):

We'll personally help with your use case. No spam.

## `resumeCursor` (type: `string`):

Leave empty for a fresh crawl. To CONTINUE a previous run where it stopped — without paying again for records you already received — paste the `resumeCursor` value from that run's Output (the run's OUTPUT key). Resume promptly: the previous run's data expires with your account's retention window (free tier: your ~10 most recent runs).

## `queries` (type: `array`):

Company names, register numbers (e.g. "HRB 6684"), or officer names to search on North Data.

## `countries` (type: `array`):

Restrict results to these countries. Leave empty to keep every country a query matches.

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

Maximum number of company records to scrape across all queries

## Actor input object example

```json
{
  "sp_intended_usage": "Describe your intended use...",
  "sp_improvement_suggestions": "Share your suggestions here...",
  "sp_contact": "Share your email here...",
  "queries": [
    "Siemens AG"
  ],
  "maxItems": 10
}
```

# 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 = {
    "sp_intended_usage": "Describe your intended use...",
    "sp_improvement_suggestions": "Share your suggestions here...",
    "sp_contact": "Share your email here...",
    "queries": [
        "Siemens AG"
    ],
    "maxItems": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("jungle_synthesizer/northdata-european-company-financials-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 = {
    "sp_intended_usage": "Describe your intended use...",
    "sp_improvement_suggestions": "Share your suggestions here...",
    "sp_contact": "Share your email here...",
    "queries": ["Siemens AG"],
    "maxItems": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("jungle_synthesizer/northdata-european-company-financials-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 '{
  "sp_intended_usage": "Describe your intended use...",
  "sp_improvement_suggestions": "Share your suggestions here...",
  "sp_contact": "Share your email here...",
  "queries": [
    "Siemens AG"
  ],
  "maxItems": 10
}' |
apify call jungle_synthesizer/northdata-european-company-financials-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,jungle_synthesizer/northdata-european-company-financials-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/YxHmnHFOo9en8f4jh/builds/JIudPpv5MLyKD8n3j/openapi.json