GLEIF Publishes Report Examining Benefits of LEI Adoption in US
GLEIF and the U.S.-based Data Foundation published the report on envisioning comprehensive entity identification for the U.S. federal government. The report explores how Legal Entity Identifier (LEI) adoption by U.S. federal agencies could streamline entity identification and produce benefits in and beyond financial markets. The report presents findings based on the comprehensive research on the entity identification systems currently deployed across the U.S. government.
The joint GLEIF and Data Foundation research report explores the current landscape of U.S. federal agencies’ entity identification needs and describes the entity identification system that each uses. It the compares the Global LEI System to the other systems currently in use in the U.S and identifies how U.S. federal agencies would benefit from replacing proprietary or internal identifiers with the LEI. Finally, it proposes factors that describe the feasibility of a particular U.S. entity identification system to convert to a comprehensive entity identification system built on the LEI or, alternatively, the value of mapping existing identifiers against the LEI.
This research demonstrates that the U.S. federal government uses fifty distinct entity identification systems—all of which are separate and incompatible with one another. Entity identification, therefore, continues to represent a significant challenge for the missions of many federal agencies. Any agency tracking non-federal entities to perform a regulatory, statistical, procurement, or assistance function must either create its own entity identification system or adopt one originally created by another agency. Both approaches present difficulties in matching entities and properly assigning legal responsibility. The findings in this report may serve to inform regulators in any jurisdiction where public authorities continue to rely on a multitude of identification regimes.
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Keywords: International, US, Banking, Insurance, Securities, LEI, GLEIS, Data Foundation, GLEIF
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