Transforming Data into Opportunities: Metric of the Month – Level 2 Understanding
High-quality data is more than a benchmark – it is a strategic necessity for global trust, compliance and interoperability. In this blog, Zornitsa Manolova, Head of Data Quality Management and Data Science at GLEIF, highlights the importance of Level 2 Data understanding in ensuring data users know “who owns whom" across entire corporate groups, strengthening financial stability, compliance, and responsible investment practices.
Author: Zornitsa Manolova
Date: 2025-11-07
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In an increasingly interconnected global economy, the ability for organizations to trust and use data effectively is the foundation for innovation, growth, and competitiveness.
A high-quality data ecosystem is a driver of change and innovation that enables organizations to identify and seize new opportunities. At the same time, low data quality can lead to inefficiencies and expose the organization to regulatory and reputational risks.
GLEIF is committed to optimizing the quality, reliability, and usability of LEI data. Since 2017, it has published dedicated monthly reports to transparently demonstrate the overall level of data quality achieved in the Global LEI System.
To aid broader industry understanding and awareness of GLEIF’s data quality initiatives, this new blog series explores key metrics included within the reports.
This month’s blog examines Level 2 understanding, which answers the question of “who owns whom?”
Level 1 data answers the question "who is who?", but in today’s interconnected financial world, transparency goes beyond knowing a company’s name or registration number – it’s about understanding who truly stands behind it. To make this possible, Level 2 data has been introduced to answer the question of "who owns whom?”.
Within the Global LEI System (GLEIS), Level 2 data captures relationships by not only identifying direct and ultimate accounting consolidating parents, but also international branches and investment funds.
The direct accounting consolidating parent is the lowest-level company that consolidates an entity in its financial statements. In contrast, the ultimate accounting consolidating parent is the top-level company with no parent.
GLEIF tracks and publishes this relationship data through monthly reports, providing transparency into the completeness of parent relationship reporting. The Parent Relationships metric counts the number of LEI records with at least one valid parent entity (PUBLISHED or LAPSED), including direct and ultimate parents and branches, and excluding reporting exceptions. As of October 2025, 135,451 LEIs met the Parent Relationships metric. The Complete Parent Information shows the number of LEI records with a complete and verified set of parent details, accounting for 2,892,126 LEIs — 93.13% of the total LEI population — for the same month.
Together, these metrics provide a clear picture of how comprehensively parent and ownership relationships are being disclosed and maintained across the GLEIS, reinforcing GLEIF’s mission to enhance trust, accountability, and transparency in the global financial ecosystem. This visibility helps regulators, businesses, and analysts assess risks across entire corporate groups rather than individual entities, strengthening financial stability, compliance, and responsible investment practices.
When a legal entity reports itself as an investment fund, it is defined as a collective investment scheme that is beneficially owned by multiple investors and managed on their behalf by an asset manager or, in some cases, by the fund itself. In October 2025, there are 150,774 entities listed as investment funds within the GLEIS, and these are further categorized into three main types of Fund Relationships:
Fund Management Entity: the legal entity responsible for the fund’s constitution, operations, and risk management.
Umbrella Structure: a parent entity that contains several sub-funds, each with distinct investment objectives, investors, and segregated assets and liabilities.
Master–Feeder Structure: a setup where one or more feeder funds invest exclusively, or almost entirely, into a single master fund.
Enhancing Level 2 reporting
To strengthen the foundation of data transparency on which the GLEIS is built, GLEIF is committed to continuously enhancing the quality and integrity of relationship data through Level 2 reporting.
Key recent initiatives to bolster Level 2 reporting include the addition of rigorous Data Quality Checks and the introduction of the Policy Conformity Flag (PCF). In parallel, GLEIF is exploring the use of artificial intelligence (AI) to further improve the automation and accuracy of relationship data extraction:
Strengthening Data Quality Checks
As part of the Rule-Setting Updates in 2025, effective from November 13th, GLEIF introduced new Data Quality Checks to enhance further the accuracy and consistency of relationship data, which will be reflected in upcoming reports and the DQ dashboard. These checks are designed to ensure that reported links between entities are both logical and compliant with established relationship reporting rules and data quality standards. Specific checks include: verifying that the headquarters address of a branch matches the legal address of its head office, and vice versa; confirming matching registration statuses for relationships during transfers; validating that entities do not consolidate others when their legal form prevents such relationships; and ensuring that an entity does not report a parent relationship when the parent’s legal form means it is not expected to consolidate other entities.
In addition, a few existing checks continue to support the integrity of reported direct-parent chains by preventing circular relationships and ensuring that all direct parents and their children converge on the same ultimate parent or the same reporting exception. This verifies that non-branch entities report complete and distinct parent information, with exceptions carefully managed to avoid conflicts with relationship records, and confirms that child relationships use the correct registration status when a record is inactive.
Introducing the Policy Conformity Flag (PCF)
Launched in April 2024, the PCF is a simple tool that determines whether each LEI record meets Regulatory Oversight Committee (ROC) policies. One criterion for determining conforming status is Level 2 reporting. If Level 2 reporting is complete, it means the legal entity has reported data on its direct and ultimate parents or provided one of the acceptable reasons for not reporting this data.
Entities with a conforming status demonstrate a strong commitment to transparency and accountability. Their verified ownership information enables more effective transaction monitoring and a clearer view of corporate structures. Since its launch, the PCF has contributed to measurable improvements in Level 2 data quality – with conformity levels rising from 87.97% in April 2024 to 89.62% in October 2025.
Using AI to retrieve relationships
GLEIF has also piloted the use of AI to automate the extraction of parent-subsidiary relationships from unstructured annual reports. This approach leverages large language models (LLMs) to read companies’ yearly reports directly, generate structured subsidiary lists, and refine them through a multi-stage validation process. The pilot demonstrates that AI-driven extraction is both feasible and comparable to manual methods, identifying a similar number of entities and often capturing subsidiaries that manual reviews overlook. Although AI accuracy continues to improve, early results indicate that combining automated and manual approaches could provide the most comprehensive coverage in the near future. And while still in its early stages, this work highlights the potential of AI to complement existing data validation and analysis processes.
Transforming data into opportunities
Together, these initiatives are playing an integral role in ensuring that LEI records remain accurate, trusted, and interoperable across jurisdictions. As data users, regulators, and institutions increasingly rely on these high-quality datasets, they gain the ability to build more intelligent systems, improve compliance automation, and gain deeper insight into global ownership structures – ultimately driving greater trust, accountability, and innovation throughout the digital ecosystem.
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Zornitsa Manolova leads the Data Quality Management and Data Science team at the Global Legal Entity Identifier Foundation (GLEIF). Since April 2018, she is responsible for enhancing and improving the established data quality and data governance framework by introducing innovative data analytics approaches. Previously, Zornitsa managed forensic data analytics projects on international financial investigations at PwC Forensics. She holds a German Diploma in Computer Sciences with a focus on Machine Learning from the Philipps University in Marburg.
