GAO Report Evaluates Progress and Challenges in Establishing Government-Wide FDTA Data Standards
A newly released FDTA data standards GAO report from the U.S. Government Accountability Office (GAO) has issued a comprehensive evaluation of implementation progress under the Financial Data Transparency Act. The report explores early efforts to build uniform data standards across financial regulatory reporting and analyzes the feasibility of expanding these models into a broader, government-wide framework.
The report, titled Regulatory Reporting Reform: Financial Data Transparency Act Requires Initial Steps Toward Government-wide Data Standards (GAO-26-108420), was formally presented to congressional committees on May 14, 2026.
Rulemaking Delays and Structural Core
Enacted in December 2022, the FDTA requires covered U.S. financial regulatory agencies to jointly develop data standards for the information they collect. The framework aims to reduce private-sector compliance burdens while enhancing transparency and interoperability across the financial regulatory system. Currently, federal financial regulators collect data across more than 500 disparate information collections, often requiring the exact same data to be formatted differently for nine separate agencies.
The FDTA implementation framework involves coordination among nine covered U.S. financial regulatory agencies, including the Federal Reserve, Consumer Financial Protection Bureau (CFPB), Commodity Futures Trading Commission (CFTC), Federal Deposit Insurance Corporation (FDIC), Federal Housing Finance Agency (FHFA), National Credit Union Administration (NCUA), Office of the Comptroller of the Currency (OCC), Securities and Exchange Commission (SEC), and the U.S. Department of the Treasury.
The statute originally mandated that participating agencies finalize joint data standards by December 23, 2024. However, the GAO report highlights that a final joint rule had not been published as of May 1, 2026. Regulators remain in the early stages of reviewing the volume of public comments submitted in response to their initial August 2024 joint proposed rulemaking. Once a joint rule is finalized, individual agency-specific rules must be issued within three years after the final joint rule, meaning the full operational timeline is sliding deeper into the late 2020s.
Crucially, industry practitioners emphasize that the FDTA framework primarily focuses on standardizing the structure, formatting, and interoperability of existing regulatory disclosures rather than introducing entirely new categories of compliance reporting.
Per the FDTA, all covered information must meet specific technological benchmarks to the extent practicable:
- Be electronically searchable.
- Be machine readable, meaning it can be processed by a computer without human intervention and without losing semantic meaning.
- Be suitable for artificial intelligence (AI) applications.
The foundational August 2024 proposed rule identified four core requirements intended to act as a principles-based joint standard for transmitting and structuring data:
- Data should be fully searchable and machine readable.
- The standard should clearly define each data element and specify its relationship to other data elements.
- Data should be consistently identified in accordance with its regulatory requirement.
- The data standard should be nonproprietary or available under an open license.
To achieve consistent entity identification across fragmented reporting frameworks, the proposed rule identifies the International Organization for Standardization (ISO) 17442 Legal Entity Identifier (LEI) as the common identifier joint standard.
Internal Governance and Coordination Frameworks
To facilitate joint standard-setting and technical coordination, the nine covered financial agencies manage their decision-making by consensus across three specific collaborative workgroups:
- The FDTA Chief Data Officer’s Group: Composed of Chief Data Officers from the covered agencies, this body provides executive oversight and strategic direction for the overall project.
- The FDTA Brass Tacks Group: Consists of core staff from each covered agency responsible for assembling preliminary staff-level drafts of the rulemaking documents.
- The FDTA Technical Subgroup: A team of technical experts, data architects, modelers, and taxonomists who evaluate the practical advantages and disadvantages of specific data standards.
While the underlying technology to establish these standards exists, practitioners noted that organizational coordination and governance alignment may present greater challenges than the underlying technology itself. Reaching consensus on uniform data definitions is challenging because agencies operate with separate regulatory missions, varying data requirements, and highly unequal technical capabilities. The GAO report highlighted that because these three workgroups operate strictly by consensus and lack a single designated lead agency to drive the project forward, decision-making has significantly slowed, especially when straddling leadership gaps during presidential transitions.
Key Findings: Practical Benefits and Operational Precedents
To evaluate the path forward, the GAO report analyzed verified domestic and international data-tagging baselines:
SEC Enforcement Trends
The GAO referenced the SEC’s semiannual FDTA corporate disclosure reports from June and December 2025 to illustrate the immediate value of machine-readable data. Under the FDTA, the SEC is required to report semiannually on the public and internal use of machine-readable data for corporate disclosures, a requirement scheduled to remain in effect through December 2029.
The SEC noted that machine-readable disclosures enhanced its ability to identify anomalies and support enforcement investigations involving multiple public companies and individuals. Access to structured disclosures allowed enforcement staff to perform more efficient analyses of individual issuers’ accounting practices across wide-ranging cross-sections of the market. The SEC reported that without structured, machine-readable formatting, alleged violations would have been significantly more difficult to detect and pursue in a timely, cost-effective manner.
Global Standard Business Reporting (SBR) Baselines
The report draws heavily on mature international Standard Business Reporting (SBR) systems implemented in countries like Australia and the Netherlands, which utilize a specialized version of XML called XBRL to tag and label data elements. According to examples referenced in the GAO report, these rollouts drove dramatic efficiency improvements:
- The Netherlands: Moving to a uniform SBR taxonomy drove an estimated 98 percent reduction in unique corporate reporting data fields over roughly a decade, dropping from approximately 200,000 unique data elements down to 4,500.
- Australia: Implementing an SBR framework between 2008 and 2014 resulted in a more than 80 percent reduction in unique reporting terms, cutting the compliance dictionary from 35,000 terms down to 7,000.
U.S. Interagency Precedents
The GAO report notes that an expansion toward a true government-wide SBR mechanism would be a substantial undertaking. However, future efforts can be informed by leading practices developed under prior U.S. federal data laws. The report explicitly analyzes three precedents: the Federal Funding Accountability and Transparency Act of 2006 (FFATA), which built USAspending.gov; the Digital Accountability and Transparency Act of 2014 (DATA Act); and the Grant Reporting Efficiency and Agreements Transparency Act of 2019 (GREAT Act).
Implementation Costs and Roadblocks
Transitioning away from fragmented filing methods—which currently range from PDFs and web forms to varying XML- and XBRL-based implementations—will demand significant upfront investments. The GAO outlined several major cost and operational categories for reporting entities:
- LEI Operational Costs: While the joint rule does not force entities to buy an LEI, individual agency rulemakings likely will. Stakeholders noted that entities may have to pay a fee to obtain and renew the LEI annually. Representatives from an association representing state and local government finance offices expressed concerns regarding the ongoing manageability and costs of these requirements.
- System Updates and Testing: Reporting entities will face expenses to adapt internal processes, overhaul core software systems, execute structured data tagging, and perform rigid cross-system testing.
- Disproportionate Burden on Small Entities: Representatives from local and municipal government finance offices warned that additional staffing, training, and ongoing schema mapping protocols will heavily strain smaller municipalities and localized compliance offices operating with restricted budgets and limited resources.
Why This Matters
The GAO report underscores a structural shift toward digitized, machine-readable, and deeply integrated regulatory compliance ecosystems. Ultimately, this shift toward interoperability aims to move the U.S. toward a “submit once” data environment. Instead of forcing private entities to report identical data points in completely different formats to multiple regulators, a unified taxonomy allows data to be shared seamlessly across the entire federal oversight ecosystem. As federal financial regulators push past initial rulemaking stalls, organizations must prepare for a compliance environment where data is expected to be inherently taxonomy-driven, interoperable across multi-jurisdictional lines, and increasingly designed for automated analytics and AI-assisted workflows.
How Ez-XBRL Supports This Transition
Ez-XBRL bridges the gap between fragmented legacy reporting structures and modern, machine-readable compliance mandates through its centralized disclosure management platform. By offering comprehensive support for XML, XBRL, and Inline XBRL (iXBRL) standards, Ez-XBRL automates taxonomy mapping and structured data tagging workflows.
Our software is built to handle these kinds of digital data standards as evidenced by our solutions for European Standard Business Reporting (SBR) frameworks, similar to the international examples mentioned in the GAO report. For instance, Ez-XBRL supports data formatting for SBR programs such as existing mandates in the Netherlands and Finland, and handles reporting requirements for the Dutch KvK (Chamber of Commerce) and Finland’s PRH (Patent and Registration Office) reporting.
By bringing this practical, global experience to the U.S. market, Ez-XBRL provides the automated validation mechanisms and collaborative review tools that corporations, municipal bond issuers, and financial institutions need to ensure data quality. We help simplify workflows and maintain audit readiness as individual regulatory agencies introduce their customized FDTA compliance frameworks.
