FDTA and SBR: Building a Connected Data Ecosystem for Financial Regulatory Reporting

The Data Foundation and Donnelley Financial Solutions (DFIN) co-hosted a webinar in November 2025 to explore the potential for standard business reporting (SBR) principles as an opportunity to create a connected, standards-driven ecosystem that delivers better data, lower cost, and faster insight, building on regulatory reporting frameworks within the Financial Data Transparency Act (FDTA). 

Based on a new white paper from the Data Foundation and DFIN on the same topic, which I had the pleasure of co-authoring with Mark Dangelo, co-founder of DMink, a company that assists startups and established firms with next-generation data management, data architectures, and technology solutions, the webinar included a conversation with Dangelo, DFIN’s Senior Director of Corporate Governance Services Bridget Hughes, moderated by Data Foundation President and Chief Executive Officer Nick Hart, and opening remarks from DFIN’s President of Global Markets Craig Clay. 

For anyone who could not attend the live webinar, you can watch a recording here or read my five takeaways in the summary below. Two brief definitions that will be important to understand the webinar discussion: 

• The FDTA, which was signed into law in 2022, was designed to eliminate financial regulatory reporting inconsistencies using interoperable, machine-readable data standards. 
• SBR refers to the adoption of a common data structure across multiple regulatory agencies’ reporting requirements, as has been demonstrated by countries such as the Netherlands and Australia. To facilitate and build an SBR-like mechanism, regulatory agencies create a common structure, usually centered on a shared dictionary of data fields, also known as a taxonomy. 

The report and the webinar provide insights into the rationality behind adopting SBR principles that can ultimately transform regulatory reporting from fragmented processes into a connected, standards-driven ecosystem that delivers better data, lower cost, and faster insight.

The Critical 12-Month Window for Taxonomy Harmonization

The panel emphasized that regulators face an imminent deadline to establish interoperable taxonomies before implementation becomes fragmented across agencies. In 2026, federal financial regulators are expected to publish a final rule with data standards required under the FDTA. Then, individual agencies will support that rule with implementation activities that relate to their unique contexts.  

“Regulators need to publish and harmonize interoperable taxonomies aligned with SBR principles,” DFIN’s Craig Clay said. 

Without better coordination, the U.S. risks codifying redundancies and unnecessary cost rather than achieving the efficiency gains promised by the FDTA.

The nine federal financial regulatory agencies covered by the FDTA’s proposed rule must work together to create common data vocabularies and taxonomies that enable the "submit once, use everywhere" model. Early alignment will prevent agencies from building "siloed frameworks that increase complexity and compliance burden,” Clay explained. 

How FDTA Regulatory Compliance Can Catalyze Business Transformation

Dangelo explained how FDTA’s rules around standardizing the data that organizations report to federal agencies would not only save time and money for industry, but would also optimize the data for training AI applications. 

In terms of reducing saving time and money, Dangelo said “the idea here is that we get that reusability, so not only am I getting common data, I don't have all the costs of the data warehouses, I don't have the extraction transformation loads, I don't have the data staff that's actually trying to create the lineage, I don't have the audit oversight, I don't have the legal mandates that are trying to figure it out.” 

“I can now have concrete examples where I can rethink of how that data is used,” he added. “I can standardize it, I can normalize it, and I can reuse it. So it's defined once, I reuse it everywhere.” 

Hughes agreed: “Regulated entities are the ones that really will benefit from the submit once, use everywhere model. Rather than just reporting, they'll be mapping their reporting data—whether it's financial, sustainable, whichever data they have—to common vocabularies and taxonomies. They'll be validating at the source, generating machine-readable submissions that can be reused across many reporting obligations and to many different agencies.” 

Treating data as a reusable product could support emerging AI technologies as well. FDTA’s regulatory requirements for standardized, machine-readable data created the foundation necessary for advanced AI implementations, turning compliance from a burden into a strategic advantage for organizations willing to embrace data-driven architectures.

“What our regulators did … they have set within these regulations the principles of operation that will feed our future AI systems,” Dangelo said. “Regulations in this way can be a catalyst for us, how we transform our business.” 

The Role Evolution for Chief Data Officers and Cross-Functional Collaboration

The panel also discussed how FDTA implementation requires fundamental changes in organizational structure. Dangelo described the Chief Data Officer (CDO) as "the enterprise architect for data," responsible for ensuring "consistency across these cross-functional systems, these cross-functional regulations." Unlike traditional IT roles focused on specific applications, CDOs must manage data that "cuts across the applications" and maintain the true lineage of the data. 

This role evolution extends beyond CDOs to affect risk officers, compliance officers, IT leaders, and legal teams. The complexity of managing data "measured in zeros of 10 to 23, with 23 zeros on a yearly basis" requires what Dangelo called "a layering mindset" where "everybody has to work together because the data is no longer siloed. It is cross-functional."

Learning from International Case Studies While Recognizing U.S. Complexity

The panel examined experiences from the Netherlands, Australia, and the European Union (EU), identifying both successes and cautionary tales. Dangelo highlighted that successful implementations reduced data elements dramatically, "sometimes by 30, 40-fold," resulting in industry spending "somewhere on the order of 20-45 percent less on regulatory compliance" after 4-5 years.

However, both Bridget Hughes and Mark Dangelo expressed concerns about whether the U.S. could adopt SBR principles on the same timeline. Hughes stated bluntly: "I think it is overly optimistic." She noted that in the international examples, "it was pretty controlled" by the national governments in those countries in a way that isn’t typical in the U.S. 

Dangelo agreed. “The EU has shown that without that centralized approach … it's like clicking our heels in the Wizard of Oz and saying, ‘I want to go home.’”

The U.S. must adopt an "engineering mindset” for the regulations, which would involve a phase for developing the regulations, a pilot phase for gathering industry feedback, and then a large-scale production phase. “I hate to say it: We're stuck in that prototyping stage,” Dangelo said. “We have the regulations, but we really haven't rolled this out in the pilots. We haven't gotten industry feedback. Industry hasn't joined the march.” 

It’s Time Focus on the Design Phase of FDTA’s Implementation

To conclude the webinar, Hart asked the panel which of the five implementation stages (awareness, design, pilots, infrastructure, expansion) needs urgent attention. Both Hughes and Dangelo chose design. Hughes emphasized the need to "staff interagency working groups, finish the rulemaking process and the format, identify boundaries," and secure funding. Dangelo stressed that design requires "industry buy-in to industry participation," warning that "without that partnership, you can define this all you want, and it's still going to be viewed as a burden."

With a published final rule expected in 2026, the Data Foundation will be ready to engage with industry and agency partners during the next phase of the FDTA’s rollout. If implemented successfully, the law would offer federal agencies the opportunity to demonstrate how modern data standards deliver efficiency and transparency simultaneously. Despite the obstacles that our panel identified, we are committed to leaning in with our partners and allies, including DFIN and other Data Coalition members, to ensure that the law’s ambitious vision becomes a reality.