The unwilling entity problem

Part 9 in a series on the fundamentals of legal entity identity data. Before we can ask what good legal-entity identification has to do in the face of bad-actor use, we have to ask why legal entities are so useful to them in the first place. And that means asking: why are legal entities so attractive to those who want to move money, evade sanctions, launder proceeds, or sit out of reach of the law? Answer that, and what good identification has to do almost falls out.

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The entity-initiated problem

Part 8 in a series on the fundamentals of legal entity identity data. The entity-initiated model is not a flaw of the LEI; it is the coverage model that made the LEI workable in the contexts it was designed for. But the same model imposes a per-entity cost of discovery, explanation, and registration – a cost that behaves very differently once you step outside the regulatory perimeter. In voluntary, market-driven contexts, where the number of entities needing identification runs into the hundreds of millions, that per-entity friction is the binding constraint. No amount of operational improvement, and no reduction in fees, can close a gap that multiplies with every legal entity created.

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The LEI: Right idea, structural limits

Part 6 in a series on the fundamentals of legal entity identity data. The LEI was designed to identify legal entities. It is the best identifier the world has. So why does less than 1% of the world's legal entities have one? The LEI deserves serious examination – not only because of what it gets right, which is a great deal, but because understanding where its structural constraints lie is essential to understanding what universal legal entity identification actually requires.

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The local company number problem

Part 5 in a series on the fundamentals of legal entity identity data. After fifteen years of working with company register data from over 140 jurisdictions, processing data on more than 200 million legal entities, we can say with some authority: the local company registration number, despite coming from the right source, is fundamentally limited as a basis for systematic, cross-jurisdictional identification.

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Proof of life

Part 3 in a series on the fundamentals of legal entity identity data. In the previous post, we saw how a legal entity comes into being: through an act of registration that doesn't merely record the entity but creates it. We saw that the register is the authoritative source – the thing that makes a legal entity real. But if the register is the source of truth, how do you prove that truth to someone else? For centuries, the answer was simple: a certificate of incorporation. That answer is now dangerously inadequate.

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An entity is born

Part 2 in a series on the fundamentals of legal entity identity data. In the previous post, we explored what a legal entity is: a construct so foundational to modern commerce that we rarely stop to examine what it actually is. We looked at the key features that make legal entities so powerful – distinct legal personality, universal recognition, chainability, and limited liability. Now we turn to a different question: how does a legal entity actually come into being?

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What actually is a legal entity?

Part 1 in a series on the fundamentals of legal entity identity data. Think about the last time you signed a contract. If it was done in a work context, perhaps it was a supplier agreement, a SaaS subscription like Salesforce, or with a new customer. You probably focused on the terms, the obligations, the price. But behind all of those details sits a more fundamental question: who, exactly, is entering into this agreement?

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Mapping innovation in energy startups: A data fusion journey with OpenCorporates and Semantic Scholar

Today’s energy sector is evolving fast. With thousands of new companies emerging each year, keeping track of innovative startups is both a challenge and an opportunity. So how can investors, policymakers, and researchers quickly identify the most promising ventures, especially those with deep scientific expertise? In this post, I’ll walk through the methodology, share some key findings, and explain how this approach opens new doors for data-driven innovation analysis.

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