Don’t Do Business in the Dark: Data Quality Management Lights the Way for Clear Business Information
The availability of open, accurate, and relevant entity identification data has never been more important. In this blog we explore why, and review GLEIF’s flagship initiatives in this critical area.
Author: Zornitsa Manolova
Trust is the main pillar of any economy. It matters more than ever in a digital and globalized economy – as the number of legal entities transacting and interacting is increasing and will continue to do so. This new environment makes identity verification by businesses and authorities more important but also more challenging to do accurately. Transparency of all actors is a prerequisite for any sustainable investment, qualified reporting, or analysis. Yet to deliver trust and transparency, every business must be identifiable internationally, underpinned by high-quality, accurate data.
Looking at the relevant topics for 2023, key issues like data governance, improving data quality and transparency, harmonization and interoperability, and data validation immediately come to mind. However, the focus will also be on regulations related to data as one of the main issues. To name just a few: the Financial Data Transparency Act (FDTA), EU Open Finance, PSD2, EU AI Act, or Corporate Sustainability Reporting Directive (CSRD).
Understanding the impact of the key data quality drivers on the most pressing challenges for society and the economy is of great importance. The usability of data will depend on its interoperability and standardization. When it comes to these two fundamental principles, the relevance of leveraging a global standard for identifying and verifying entities considering the global nature of cross-border trade and suppliers, becomes apparent. A lack of common standards for data and interoperability contributes to a lack of next-generation digital infrastructure and inhibits innovation.
Enabling digital transformation in a way that is interoperable, independent, and autonomous
When it comes to driving economic growth, innovation, and competitiveness, both for corporates and SMEs, data quality, interoperability, and global standards play a crucial role. Data will provide greater transparency in the global marketplace, reduce criminal intent, and lead to more sustainable business decisions, but only if it can be used by all interested parties with less or no effort and it is reliable.
The recent developments in the open finance movement provide a useful jumping off point when exploring this idea. The Expert Group on European Financial Data Space recently stated in their report: “The LEI could play an important role in open finance by promoting standardized data identification and aggregation, improving data quality and transparency, and reducing costs related to verification checks. Data sharing could be made possible if data is collected in a standardized and harmonized way with structured identifiers, such as the LEI. Moreover, the LEI could facilitate the identification of financial service providers and other legal entity parties in a seamless way through its publicly accessible Global LEI Repository. In terms of data access, the LEI could also play an important role in the functioning of application programming interfaces (API).”
The Financial Stability Board published a report in 2022, encouraging global standards-setting bodies and international organizations with authority in the financial, banking, and payments space to drive forward LEI references in their work. A primary near-term goal of the FSB’s report, published as part of the G20 Roadmap for Enhancing Cross-Border Payments, is to stimulate LEI to use initially in cross-border payment transactions. By helping to make these transactions faster, cheaper, more transparent, and more inclusive, while maintaining their safety and security, the LEI has been deemed by the FSB to support the goals of the G20 roadmap.
Elsewhere, a report by the International Chamber of Commerce (ICC) UK calls for the adoption of existing technologies such as Legal Entity Identifiers (LEIs), digital ledgers, invoice number tracking, APIs between revenue departments and banks as well as regulators enabling banks to share fraud data, all of which will help shut fraudsters out of the system.
The Global LEI System (GLEIS) has a unique opportunity to solve the problem of trust for legal entities on a global scale. It can enable digital transformation in a way that is interoperable, independent, and autonomous. As a universal ISO identification standard and a code that connects entities to key reference information, including ownership structure, the LEI tackles data reconciliation problems across borders and promotes an interoperable identity standard.
Data makes us faster, and more prudent and leads to more sustainable decisions
Take Environment, Social, and Governance (ESG) reporting, for instance. For investors, their ability to use LEI data to verify the identity of invested companies and their corporate organizational structures can underpin their responsible investments and inform decision-making. A transparent, current, and accurate view of the names, locations, and legal forms of subsidiaries, parents, and holdings of a company is imperative to fully understand the nature and systemic risks of an investment. Without this high quality, accurate legal entity data, ESG reports lose their value as a means of evaluating performance indicators and promoting sustainable investment.
The LEI is the only global solution providing organizations with reliable data to unambiguously identify companies and corporate structures worldwide.
Global business communities stand not only to benefit from increased LEI adoption but also from their utilization of the open LEI dataset, which is freely available to anyone, anywhere in the world, via the Global LEI Index. The utility of this resource is contingent on a variety of factors, including: the amount of data contained in each LEI record; the quality of that data, including how accurate and up-to-date it is; how deeply and diversely the dataset can be examined; and how accessible it is to the range of organizations that use it, including, for example, regulatory supervisors, independent data service providers, and individual entities conducting supply chain due diligence.
Happily, the quality of data held within the Global LEI Index is already high, thanks to a stringent data quality management system. This benefits data governance and compliance at an individual entity level and provides a foundation for trusted open data initiatives looking to leverage accurate, trusted legal entity identification in their platforms.
GLEIF is committed to perpetually improving the availability of open, accurate, and relevant entity identification data for everyone and is engaged in a plethora of initiatives designed to further that commitment. To illustrate, let’s shine a light on some of these flagship projects.
Transparency and accountability underpin effective environmental stewardship and global sustainability efforts. To demonstrate how LEI data can play a critical role in helping businesses assess the climate change-related risks of their investments, GLEIF joined the Linux Foundation’s OS-Climate initiative in 2022 to help drive trust and transparency in open-source climate data and analytics solutions.
OS-Climate is a member-driven, non-profit organization hosted by the Linux Foundation, which is committed to the development of an open data and open-source analytics platform focused on managing climate risk and accelerating investment in low-carbon and resilient solutions. The partnership enables real-time LEI data to be made publicly available in the cloud via the Amazon Sustainability Data Initiative (ASDI) data catalog. By making this data readily available alongside other key climate-related data sets, such as carbon emissions and climate projections, investors are empowered to make more environmentally friendly financial and investment decisions.
Enabling automated assignment of ELF codes
In line with its commitment to advancing its entity identification data, GLEIF regularly analyzes the provision of the authoritative sources and assigned entity legal form (ELF) codes based on the ISO 20275 standard.
For the latter, GLEIF and its partner Sociovestix Labs developed a machine learning tool in 2022, Legal Entity Name Understanding (LENU), to automatically assign ELF codes based on the legal name and jurisdiction. LENU is now freely available on GitHub.
LENU uses the LEI data to build jurisdiction-specific models and allows the user to get a suggestion for a legal form for any given legal name. GLEIF has established a data quality loop in which the legal form that is suggested by the tool is compared to the ELF code in the current LEI data. In case of clear discrepancies between the model’s results and the current LEI data, GLEIF created data challenges which are sent to the LEI issuers for exact verification and update of the data records, where needed. The updated data is then used to build the next version of the models with a then improved data source which ultimately boosts the model’s performance. This tool is an example of how machine learning algorithms could be applied for assessing and improving the quality of the data.
Enhancing data quality with new data formats and reporting
In 2022, a major milestone for the Global LEI System was achieved with the implementation of the three ROC policies on Fund Relationships and Guidelines for the registration of Investment Funds, Legal Entity Events (formerly referred to as “Corporate Actions”), and Data History, and LEI Eligibility for General Government Entities. These new data formats have expanded the scope of the data contained in the LEI records, creating more transparency in the global marketplace and broadening the utility of the Global LEI System for users everywhere.
To support the efforts of the LEI issuers and ensure stable operations of the system, GLEIF published a revised version of its Rule Setting 3.2, including 118 data quality checks in total. The new Rule Setting came into effect in April 2022, which led to a noticeable drop in the Average Total Data Quality Score from 99.98 to 99.77 (See Figure 1).
This behavior is expected when a new set of data quality checks is introduced. For instance, the drop in August 2021 to 99.71 (see Figure 2) was mainly caused by the introduction of a new Rule Setting. Although in 2022, GLEIF introduced 34 new checks and updated another 40 in order to comply with the new requirements of the three ROC policies, LEI issuers remediated the remaining data quality failures quickly. This was achieved thanks to the LEI issuers’ experience that they gained over the last years and by leveraging the Data Governance Pre-Check facility.
The proactive Pre-Check API was introduced by GLEIF to help LEI issuers in identifying data quality issues before they even enter the system. In the end, the Average Data Quality Score stabilized at 99.97 in the last quarter of the year.
During 2022, the achieved Maturity Levels exhibited similar curves as the Average Data Quality Score, and the number of LEI issuers achieving higher Maturity Levels (Expected and Excellent Quality Levels) declined by 10 organizations when the new policies came into effect (see Figure 3).
However, the developments of the past three years show a continuous improvement of the Maturity Level performance (see Figure 4). This improvement was triggered in 2021 after the introduction of the requirement for new and updated LEI records to be sent to GLEIF’s Data Governance Pre-Check facility. This facility applies the current Rule Setting and provides not only a preview of the data quality results but also the reason for a potential failure. Without a doubt, the introduction of proactive data management via the Data Governance Pre-Check facility was the game changer in terms of maturity.
Increasing transparency into changes in data quality levels
Last year GLEIF made its interactive Data Quality Dashboard open to the public; before then, it was only available for GLEIF, LEI issuers, and ROC members. This innovative tool enables global data consumers to:
Monitor data quality related KPIs on a daily basis
Analyze various statistics for user-defined time periods
Understand the principles behind GLEIF’s Data Quality Checks
Compare the performance of LEI issuers
Investigate the data quality of a single LEI
Research any data challenges that were raised against LEI data
Advancing these and other data quality and data governance initiatives will continue to be a key priority for GLEIF in 2023, and we look forward to sharing news of GLEIF’s continued momentum in the months that lie ahead.
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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.