Why business identity matters for AI
Artificial intelligence is transforming how companies process data, assess risk, and make decisions. Financial institutions use AI to detect fraud, assess credit risk, and verify counterparty identity. Across industries, automated systems increasingly rely on AI to screen suppliers, partners, and clients before entering into contracts or transactions. In all these cases, one shared requirement exists: the AI system needs accurate, verified information about who it is dealing with. This is exactly where the LEI code becomes essential.
What does AI actually need from business data?
AI is only as good as the data it relies on. This principle is especially true for business identity data. Consider a simple example: “Volkswagen AG”, “Volkswagen Aktiengesellschaft”, and “VW Group” all refer to the same company. However, to a machine, these look like three completely separate entities.
Furthermore, this challenge exists across all major markets. In Japan, kanji and romanized company names do not automatically match. In India, “Private Limited” and “Pvt Ltd” carry identical meaning but appear as different data strings. In the United States, meanwhile, the same business may carry different names depending on its state of registration. As a result, fragmented data causes automated systems to struggle — and incorrect entity matching leads directly to incorrect decisions.
To function reliably, AI therefore needs business data that meets four criteria. First, every entity must be uniquely identifiable. Second, data must be verified and up to date. Third, it must be structured and machine-readable. Finally, it must work consistently across Europe, Asia, and the Americas. The LEI code meets all four requirements.
What is the LEI code and why does it work for AI?
The LEI code (Legal Entity Identifier) is a 20-character alphanumeric code that uniquely identifies a legal entity at a global level. GLEIF — the Global Legal Entity Identifier Foundation — governs the standard, which conforms to ISO 17442.
Each LEI code links to verified public data: the company’s official name, registered address, legal form, country of incorporation, registration number, and ownership structure. Moreover, GLEIF makes all this information freely accessible through its global database. When a transaction, contract, or report includes an LEI code, an AI system can immediately identify the exact entity — regardless of name variation, language, or jurisdiction. This makes the LEI code a natural anchor identifier for AI-powered applications.
Does your company not yet have an LEI code? You can register one in just a few minutes — register your LEI code here.
How GLEIF is already using AI to improve LEI data
GLEIF actively uses artificial intelligence to strengthen the Global LEI System. Specifically, in 2025, GLEIF integrated a tool called LENU — Legal Entity Name Understanding — into its data quality framework. LENU automatically detects and normalizes legal entity name forms across different languages and jurisdictions. As a result, LEI data grows more precise every year — and more valuable for anyone building AI applications on top of it.
The results are clearly measurable. GLEIF’s overall data quality score reached 99.99% in both 2024 and 2025. Additionally, the average time to resolve data quality issues dropped from 33 days to just 14 days. For anyone building AI applications that rely on verified business identity, this level of reliability matters enormously.
Practical use cases: the LEI code as a foundation for AI systems
KYC and due diligence automation. Financial services companies must collect and verify information about clients and partners. This process is known as KYC — Know Your Customer. AI-powered KYC tools use the LEI code to pull a company’s official data, ownership structure, and related entities directly from the GLEIF database. Consequently, this cuts manual workload and lowers the risk of misidentification significantly.
Supply chain risk assessment. Large corporations and logistics firms use AI to assess supplier reliability. In practice, the LEI code allows these systems to connect data about one company across multiple databases — even when that supplier operates through different legal entities in different countries. Therefore, risk teams get a complete and accurate picture without manual cross-referencing.
Regulatory reporting and compliance. The LEI code carries regulatory weight across multiple continents. In Europe, MiFID II, EMIR, and DORA all require it. In the United States, the CFTC mandates it for derivatives reporting. In India, the Reserve Bank of India requires an LEI for all companies making cross-border transactions above 50 million rupees. Additionally, the Financial Stability Board recommends broader LEI adoption to improve cross-border payment transparency. As a result, AI compliance tools can verify automatically whether report identifiers are valid and current.
What does this mean for your company?
If your company operates in finance, insurance, supply chain, legal services, or real estate investment, then a valid LEI code is increasingly a practical necessity. In other words, it is no longer just a regulatory requirement — it is a competitive one. AI systems searching for data to conduct business with you will find companies with structured, verified identity far easier to work with. Without an LEI code, your company is simply harder for these systems to trust.
Already have an LEI but it has lapsed? In that case, renew it before issues arise — renew your LEI code here. An expired LEI code is not a reliable source for AI systems or regulators.
Summary
Artificial intelligence does not operate in a vacuum. Instead, it needs structured, verified, and unambiguous data. Currently, the LEI code is the only globally standardized identifier that meets all these requirements for business entity identification. GLEIF’s data quality stands at its highest level, AI tools are developing rapidly, and regulatory requirements keep expanding — across Europe, Asia, and the Americas. Therefore, companies already represented in this system are better positioned for tomorrow — both for AI-powered processes and for regulatory compliance.