Tony Kelly | 7/9/2024The Federal Government’s passage of the Financial Data Transparency Act (FDTA) heralds a transformative shift in financial data collection and reporting for federal financial regulators. The FDTA has a multifaceted goal of enhancing transparency, streamlining compliance processes, and supporting the development of cutting-edge, open regulatory technologies through the adoption of common data standards.
The FDTA identified U.S. financial regulatory agencies (many of whom are existing Analytica clients) that are impacted, to include the Department of the Treasury, Securities and Exchange Commission, Federal Deposit Insurance Corporation, Office of the Comptroller of the Currency, Bureau of the Consumer Financial Protection, Federal Reserve System, National Credit Union Administration, and Federal Housing Finance Agency. The joint rule proposes that these organizations adopt principles to develop specific data standards governing information financial institutions reported to each agency and data collected from member agencies on behalf of the Financial Stability Oversight Council.
At its core, the FDTA seeks to make financial data reported to regulatory bodies electronically searchable and machine-readable, significantly enhancing the value of data as an asset and its usability. Many of these organizations have established data management processes that set consistent semantics and syntax of their data. FTDA will require that standards be applied to make this financial data machine-readable. This initiative will improve public access to financial data, fostering greater transparency, accountability, and value. The FDTA also creates significant opportunities to apply data science and advanced analytics approaches across a broad spectrum of use cases, from improving operations to deterring fraud and criminal activity.
The FDTA will require a harmonized data approach and mandates the adoption of standardized identifiers for financial transactions and entities. Furthermore, the reported data must be in specific machine-readable formats, such as XML, JSON, or XBRL, and available under non-proprietary, open-license formats. High-quality data standards are required to be implemented and documented in machine-readable taxonomies and ontology models. These measures will reduce the complexity and redundancy in regulatory reporting with the goal of making compliance more efficient and less burdensome.
The FTDA will require alignment among agencies. Establishing cross-agency working groups can foster collaboration and drive consensus on data standards. Agencies can leverage established frameworks, like ISO 20022, for financial messaging standards and provide a solid foundation for interoperability. In addition, Analytica recommends would also recommend maintaining data quality and consistency through implementing a robust data management and governance program with data stewardship roles and advanced data engineering practices such as data lineage tracking, automated data validation, and cleansing processes. Agencies will also need to address data privacy considerations in data system designs through techniques like data anonymization and encryption and ensuring compliance with federal and state regulations. Leveraging experiences from cloud migrations can enhance data security by adopting best practices for cloud security, including encryption at rest and in transit, identity, and access management (IAM), and regular security audits. Additionally, employing explainable AI techniques, such as SHAP (SHapley Additive exPlanations), can enhance model interpretability, ensuring that AI models used in financial reporting are transparent and understandable.
The Financial Data Transparency Act represents a significant advancement in financial regulation and will have a material impact on covered financial regulators. As agencies move towards full implementation, their collaboration and commitment will be vital to realizing the full potential of this transformative legislation. Please contact us to explore how these changes may impact your operations.
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