Organizations as diverse as the European Central Bank and the University of St. Gallen trust the LEI to make smarter, less costly, and more reliable business decisions, thanks to our commitment to high quality data, explains Zornitsa Manolova, Head of Data Quality Management and Data Science, Global LEI Foundation
Author: Zornitsa Manolova
The rapid growth of the global digital economy has made it easier for organizations across every corner of the world to conduct business, connecting millions of companies through financial transactions each day. But even though the technology allows this to happen at unprecedented speed and scale, how can we really be sure that the person or organization we are interacting with, is who they say they are?
For the global digital economy to thrive, every type of organization, from start-ups to multinational corporations, needs both trust and transparency. This requirement is particularly poignant in the context of today’s societal increase in remote working and an even greater reliance on virtual communication.
Yet to deliver trust and transparency, every business in the global supply chain must be identifiable internationally, underpinned by high quality, accurate data. This can be achieved very simply with the Legal Entity Identifier (LEI).
Prioritizing data quality
The LEI acts as an ‘international passport’ for legal entities around the world, empowering organizations to make smarter decisions about who to do business with. Following the continued growth of the Global LEI System and increasing LEI issuance volumes, our latest video outlines our commitment to ensuring high quality data for all users.
Data quality management within the Global LEI System is a significant strategic priority and, in the last eighteen months, we have invested heavily in the pursuit of best practice. We work closely with the Local Operating Units (LOUs) to enforce rigorous data quality checks, provide complete transparency by publishing all results online, and have recorded way over 99% in terms of measurable data quality.
Our stringent approach to data quality has strengthened the overall value of the LEI by reassuring users that all data within the Global LEI System is accurate and transparent. Watch the video to hear endorsements from the European Central Bank (ECB) and Prof. Damian Borth at the University of St. Gallen.
Our work is ongoing and our focus on data quality will remain a priority in line with the Global LEI Foundation’s commitment to excellence.
Registrars conduct a thorough control on the material quality of data, checking that the LEI reference data matches the official truth published by the business registers. In order to ensure the logical and technical quality of data and its consistency, we rely on the API supplied by GLEIF, which allows us to achieve integral data quality in a very efficient manner. – María Emilia Adán, President Colegio de Registradores Madrid
When we speak about the LEI, I immediately have GLEIF in my mind. The umbrella company that is in the middle of all the different local organization units in the different countries, coordinating all those LEIs together and creating one list with unique identifiers, getting the quality that we need, and making the entire system successful for the future. – Prof. Damian Borth, Artificial Intelligence & Machine Learning, University of St. Gallen
The LEI is indeed unique worldwide. It enjoys public level sector support due to the G20 endorsed charter and has entered legislation in various jurisdictions. There will be no other entity identification with those specifications. The LEI indeed deserves our support, and we are committed to developing the LEI further, together with GLEIF and our global partners. – Werner Bier, Deputy Director-General Statistics, European Central Bank (ECB)
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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.