🎯 Who Really Controls Global Business?

Separating Fund Holdings from Operational Control in 21M Ownership Links / An Exclusive Data Research by MediumAxis

💡 Key Finding

The entities appearing as “parents” most frequently in global ownership networks are not industrial conglomerates—they are financial intermediaries: asset managers, custodian banks, and index fund providers. This reflects investment holdings, not operational control. True operating companies with verified revenue tell a different story.

Who Actually Controls Global Business?

When we talk about “the world’s largest companies,” we usually think of names like Apple, Amazon, or major industrial conglomerates. These companies dominate headlines, market capitalization rankings, and public perception of economic power.

But ownership tells a very different story.

Behind every operating company sits a network of shareholders, holding entities, and controlling interests. At global scale, these ownership structures form a dense and highly interconnected system — one that is largely invisible in traditional business analysis.

This research takes a different approach.

Instead of looking at revenue or market value, it analyzes corporate control — tracing how companies are connected through direct and ultimate ownership relationships across millions of entities.

Dataset & Scope

The analysis is based on a large-scale corporate ownership dataset covering:

• • ~20 million companies and subsidiaries

  • direct and ultimate parent relationships

  • cross-border ownership links across multiple jurisdictions

The data is derived from aggregated registry sources, including datasets such as Bureau van Dijk (BvD), and processed to reconstruct global ownership structures at scale.

Rather than focusing on a small sample of public firms, this approach captures the broader corporate graph, including private companies, holding structures, and investment vehicles.

Why This Matters

Ownership is the foundation of control.

Understanding who ultimately owns and connects companies reveals:

• • how economic power is distributed

  • which institutions sit at the center of global business

  • how capital flows across borders

  • and how corporate structures differ across regions

It also exposes a key blind spot:

The entities that control global business are often not the ones that operate it.

A Note on Interpretation

Large-scale ownership data comes with structural challenges:

• some entities represent investment or custody structures, not traditional operating companies

• corporate service providers and nominee entities can appear as intermediaries

• regional differences (especially in jurisdictions like China) introduce variations in reporting and structure

Where relevant, these effects are considered in the interpretation of results. With that context, we can now examine what the data actually reveals.

Layer 1: Financial Intermediaries (Hold Shares, Not Operations)

Top 15 by subsidiary count. Revenue data often unavailable because fund holdings ≠ operational revenue.

⚠️ Note: Revenue figures from Apollo.io represent organizational revenue, not assets under management. For fund managers like BlackRock, AUM ($10T+) far exceeds operational revenue.

Layer 2: Operating Conglomerates — Verified with Revenue

Top 15 operating companies with verified Apollo revenue data. Revenue bands for cleaner visualization.

📊 Operating Scale: Subsidiaries vs. Revenue

Scatter plot of verified operating conglomerates. Note the wide range: some companies achieve massive revenue with relatively few subsidiaries.

🔍 Click image to enlarge • Data: Apollo.io revenue verification (21% match rate)

Top 15 Ownership Flows by Volume

These 15 corridors represent ~48% of all cross-border ownership links, highlighting deep financial integration between major economies.

🔍 Click image to enlarge • Interpretation: US↔UK/CA flows reflect financial integration; HK→CN shows offshore-onshore Chinese structures

Detailed Flow Analysis

Global Ownership Imbalance

Positive balance = net owner (owns more abroad than foreign-owned domestically). Negative = net owned.

🔍 Click image to enlarge • Green = Net Owner | Red = Net Owned

Top 5 Net Owners vs. Net Owned

💡 Interpretation: Switzerland, France, Japan = wealth management & fund domiciles. China, Brazil, Russia = emerging markets with significant foreign capital inflows.

🔍 Methodology Notes

• Source: Bureau van Dijk Orbis (21M majority-owned relationships)
• Scope: Ultimate parent companies only; country-level geography
• Enrichment: Apollo.io revenue verification (21% match rate); Adapt.io industry classification (6.5% match rate)
• Exclusions: Minority stakes, non-majority links, entities with missing critical fields

🇨🇳 Chinese Entities: Verified or Multi-Country (Included in Main Analysis)

Only Chinese entities with verified revenue data OR operations in 2+ countries are included here. Others are flagged as potential artifacts (see methodology appendix).

📌 Note: ~4.5M high-count Chinese entities with 1 country and no revenue verification are flagged as suspicious_cn_aggregator or potential_artifact. Full list available in methodology appendix.

🔗 Access the Full Intelligence

This analysis represents a fraction of the Bureau van Dijk Orbis dataset. For complete ownership tracing, custom enrichment, or enterprise integration:

👉 [INSERT YOUR “Core Global Intelligence Assets” TEMPLATE CARDS HERE]

Primary Data: Bureau van Dijk Orbis

• ✅ 21,489,291 majority-owned ownership relationships
• ✅ Ultimate parent identification via graph traversal
• ✅ Country-level geographic aggregation
• ✅ Entity categorization via keyword + heuristic rules
• ⚠️ Excludes minority stakes, non-majority links, entities with missing critical fields

Enrichment Sources

⚠️ Data Quality Flags

• suspicious_cn_aggregator: High-count Chinese entities with 1 country, no cross-border links (likely SPV aggregation)
• potential_artifact: Registry relationships interpreted as ownership (e.g., corporate service providers)
• large_entity_unverified: High subsidiary count but no clear category match or revenue verification
• Recommendation: For due diligence, combine Orbis ownership tracing with local business registry verification and manual review of flagged entities.

🚀 Ready to Unlock Complete Ownership Intelligence?

This article demonstrates the power of structured ownership data. For enterprise-grade access, custom enrichment, or integration support:

📧 Questions? Contact our data intelligence team for custom extracts, API access, or methodology documentation.