FDTA fine-tuning? XBRL US calls for a data quality upgrade
In a recent response to the proposed Financial Data Transparency Act (FDTA) rule, XBRL US has called for enhancements to improve standardisation and reduce regulatory costs.
Campbell Pryde, President and CEO of XBRL US, argues that regulators should adopt a single semantic data model, specifically XBRL, instead of the current properties-based approach outlined in the proposal. This will help agencies move away from siloed, non-interoperable datasets, leading to better data quality, reduced costs, and increased flexibility for both regulators and reporting entities.
Pryde highlights the benefits of a unified approach, noting that XBRL enables machine-readable and machine-understandable data, enhancing data quality through validation rules, and allowing datasets to be easily shared and analysed. Standardisation also drives economies of scale, reducing costs for regulators, businesses, and data users alike, while supporting artificial intelligence and machine learning applications.
XBRL US further recommends the adoption of existing taxonomies where possible, including those developed by the Financial Accounting Standards Board (FASB), and stresses the importance of removing potential “off-ramps” that could weaken the rule’s implementation. Standardisation is key to ensuring transparency, efficiency, and collaboration across agencies, ensuring that the FDTA achieves its full potential.
XBRL US has been working hard on this, with many members contributing their expertise to shape their final response. They are now encouraging members to submit their own comments to the nine agencies involved by the 21st October deadline (right around the corner!). Regulators do read these letters, and a higher volume of submissions can have a greater impact on the final rule. The FDTA is a critical piece of regulation, so we would encourage our readers to have their say.
For the full response, see the blog here.
