The Financial Data Transparency Act (FDTA, P.L. 117-263 §5801 [136 Stat. 3421]), enacted in 2022, requires agencies that oversee the activities of financial institutions to adopt data standards to govern the collection of information from such financial institutions. The FDTA defines data standard as "a standard that specifies rules or formats by which data is described and recorded" (12 U.S.C. §5334(a)(3)).
Proponents of such data standards argue that they can improve the electronic collection of data, particularly from multiple data providers that use different information technologies. For example, in a 2024 letter urging financial regulatory agencies to adopt the data standards required by the FDTA, several Members of Congress stated that implementation
will alleviate regulatory reporting burdens and will improve the accessibility, uniformity, and usefulness of federal financial data for the public…. It will also improve the collection and dissemination of federal financial data. This will spur innovation and facilitate the responsible use of technology to fully utilize the publicly available data [covered] agencies publish.
This In Focus informs Congress on the progress of the FDTA's implementation to date. It identifies the covered federal financial agencies implementing the data standards and summarizes the standards they have proposed, including an identifier for financial entities. The In Focus also discusses a certain data standard for some financial data reporting that is already underway. The distinction between data formats and definitions, which is also discussed, is important to consider. Many data collections must be tailored to specific policy mandates, possibly limiting the extent to which data standards can be jointly implemented.
The FDTA builds upon requirements in the Dodd-Frank Wall Street Reform and Consumer Protection Act (P.L. 111-203) for data collection, analysis, and standardization. Specifically, the FDTA amends Title I of the act, the Financial Stability Act of 2010 (12 U.S.C. §§5311-5374) and directs most agency heads comprising the Financial Stability Oversight Council (FSOC) to jointly issue a final rule that establishes joint data standards for two types of data collections: (1) collections by each agency from their regulated entities and (2) collections on behalf of FSOC (12 U.S.C. §5334(b)).
FSOC was established to monitor and identify risks to national financial stability. FSOC members include the Department of the Treasury, Federal Reserve System, Securities and Exchange Commission (SEC), Federal Deposit Insurance Corporation, Office of the Comptroller of the Currency, Consumer Financial Protection Bureau (CFPB), National Credit Union Administration, Federal Housing Finance Agency, and Commodity Futures Trading Commission (CFTC). Although the FDTA refers to these agencies as covered agencies, it does not specify the CFTC as a covered agency for its purposes. However, FDTA permits the Treasury Department to designate any other primary financial regulatory agency a covered agency (12 U.S.C. §5334(a)(1)(I)), which it did of CFTC.
The covered agencies must adopt joint data standards, resulting in each agency using and applying the same rules and formats to the applicable data it collects from the entities it regulates. The promulgation of joint data standards, therefore, is to seek interoperability, enabling financial regulatory data to be jointly used by FSOC's member agencies (12 U.S.C. §5334(c)(2)(B)). These joint data standards are to take effect not more than two years after promulgation of the final rule. On August 22, 2024, the covered agencies published in the Federal Register a notice of proposed rulemaking (NPRM) of the joint data standards. As of August 2025, a final rule has not been published.
At a minimum, the FDTA requires the joint data standards to include a nonproprietary legal entity identifier (LEI), which uniquely identifies legal entities that participate in financial transactions. In the wake of the financial crisis, regulators and financial firms were unable to quickly identify market participants that were exposed to above-normal financial risks. An LEI is intended to alleviate some of the challenges with that identification. The covered agencies propose that all legal financial entities with reporting requirements use the LEI developed by the Global Legal Entity Identifier Foundation.
Prior to enactment of the FDTA, some of the covered agencies were using a specific data standard known as XBRL for certain data reported by their regulated entities. When electronically reporting data to an agency that uses XBRL, an entity assigns a predefined label, or identifier tag, to each reported data element. Tags enable machine-readability, meaning that computers can process and understand the data without a person needing to intervene. (The FDTA's definition of machine-readable is given at 44 U.S.C. §3502(18)). Adopting a data standard, such as XBRL, can reduce an agency's data processing costs and increase the usability of reported data, as the SEC noted in a December 2024 report to Congress.
In 2005, the Federal Financial Institutions Examination Council (an interagency group of federal financial regulators) required banks to submit quarterly Reports of Condition and Income (known as call reports) using the XBRL standard. In 2009, the SEC adopted a rule requiring corporations to file and submit required forms electronically using XBRL via its Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system. In 2022, the Municipal Securities Rulemaking Board, which oversees the municipal bond markets and its participants, launched an innovation sandbox that allowed financial reporting in XBRL. Although the covered agencies do not explicitly propose the sole and specific use of XBRL, the NPRM says XBRL could satisfy certain properties of the data standards specified in the FDTA.
The covered agencies presently interpret the FDTA's requirements for data standards to cover only regulated entities' reporting requirements. The FDTA states that the data standards should—to the extent practicable—use schemas with accompanying taxonomy or ontology models. Schemas are used to delineate relationships either between data elements or between datasets, resulting in a structure, organization, and format that can be used when electronically sending and receiving data for reporting purposes. A taxonomy (or ontology under certain circumstances) is generally used as a categorization system that creates and controls the relationships among data based on its semantic meaning. For example, financial assets can be classified in numerous ways, such as by product type (e.g., mortgage loan, commercial loan, bond, derivative), type of issuer, or type of risks (e.g., prepayment, default, liquidity).
The FDTA states that the adoption of standardized schemas and taxonomies should be, "to the extent practicable," giving regulators discretion to determine the practicability of features mentioned in statute. In the NPRM, the covered agencies note that not all FSOC agencies currently use schemas or taxonomies for reporting and that such standards may be inappropriate in some cases. Thus, the financial regulators are not proposing to adopt standardized taxonomies and schemas.
Reporting compliance is frequently linked to certain statutory requirements. For example, regulated entities engage in different types of financial activities that may be covered by specific policy mandates and require specific data reporting requirements. Because even similar financial entities, such as lending institutions, differ in size and lending strategies, reporting requirements are tailored to these differences. Furthermore, some reporting must follow calculation guidelines specified by different accounting definitions or by regulators that enforce different policy mandates. Additionally, while some data may have conceptual similarities (e.g., call reports for banks compared to those for credit unions), actual differences in the data may be important to preserve under separate policy and reporting regimes.
Independent of the FDTA's implementation, regulators may establish comparability among certain terms (i.e., variables) that have been defined (using different legislative authorities) to satisfy multiple statutory purposes when possible. For example, banking regulators and the CFPB harmonized the definitions of small business and small farm for reporting compliance with Section 1071 of Dodd-Frank under the Community Reinvestment Act (P.L. 95-128). The alignment of standardized data semantics to satisfy multiple regulatory purposes prior to being electronically reported can reduce reporting burdens and facilitate data interoperability.
Although the FDTA does not confer to the covered agencies any new authority to collect new data, regulated entities have raised cost concerns associated with adopting data standards. In 2023, the SEC noted that small filers typically paid between $1,500 and $5,000 annually for third-party compliance services, which may include software costs, while larger filers typically pay between $5,000 and $30,000 annually. Although the adoption of data standards (as noted by the SEC in December 2024) reduces the aggregation, processing, and reporting costs for regulators, regulated entities still incur costs. Some entities (e.g., credit unions) question the need to adopt data standards if their data will still be used predominantly by their primary regulators rather than other regulators. Furthermore, some regulated entities are also concerned about incurring future costs to respond to new requirements, such as having to adopt new variable definitions, if the financial regulators plan to adopt specific taxonomies or schemas under the FDTA in the future.
The SEC notes that compliance costs can sometimes be measured in terms of burden because the underlying data collections (i.e., forms) are subject to the Paperwork Reduction Act (PRA). The PRA requires federal agencies to minimize the time and resources it takes for the public to provide data to the government. By definition, burden includes the acquisition and use of technology needed to provide data to an agency (44 U.S.C. §3502(2)(B)). Thus, under the PRA, the federal financial regulators must remain mindful of the compliance costs even when adopting data standards for information collections.