The regulatory reporting landscape for global derivatives markets is currently undergoing a period of profound transformation.
As discussed extensively at the recent ISDA Annual General Meeting, the industry is grappling with a combination of evolving regulatory demands, the ongoing challenge of maintaining data quality, and the integration of new technological standards. For financial institutions, adapting to these changes requires moving away from fragmented, reactive compliance projects and towards strategic, model-driven architectures.
A significant development in the pursuit of reporting efficiency is the growing push for global regulatory harmonisation. A recent memorandum of understanding between the Commodity Futures Trading Commission and the Securities and Exchange Commission aims to simplify trade reporting. The industry is hopeful that such alignment means firms will not have to separately review and reconcile harmonisation efforts between these major regulators in the future.
However, structural disagreements and regional divergences remain, most notably in the debate between single-sided and dual-sided reporting. Proponents of single-sided reporting, such as the DTCC, argue that it generates less data, requires reporting only once, and eliminates concerns regarding trade reconciliation. North America currently utilises single-sided reporting, whereas the European Union and the United Kingdom require dual-sided reporting. Dual-sided reporting causes significant friction for institutions, demanding a huge effort to review and reconcile disparate data sets, as highlighted by panellists. Despite industry preference for the simplicity and inherent data quality of single-sided submissions, regulators maintain a strong preference for seeing both sides of a reporting transaction. Furthermore, the responsibility for reconciliation varies globally; in Europe, it is owned by the Trade Repositories, while in the APAC region, it is owned by the regulators.
Ensuring high data quality remains a persistent challenge that necessitates huge investments in data validation from market participants. This challenge is compounded by the fact that different regulators maintain distinct expectations regarding data quality, an issue recently raised in an IOSCO meeting. This lack of uniformity creates significant operational friction for firms operating across multiple jurisdictions.
Despite these jurisdictional hurdles, the overall landscape is showing signs of improvement. The adoption of Critical Data Elements is actively helping to raise the standard of data quality across the industry by establishing a common data layer across various regulations. Establishing these universal data points is a crucial step in reducing the burden on compliance teams.
Securing the Foundation with DRR and CDM
To truly solve the problem of fragmented data models, the industry is increasingly turning to the Common Domain Model and Digital Regulatory Reporting. Panellists noted that the industry is not simply solving a single problem; rather, every new regulation becomes a new problem. The challenge often lies in finding agreement among firms that want to utilise these new standards versus relying on their existing legacy systems. However, moving to a model-driven approach gives firms the opportunity to standardise their data; once this standardisation is achieved, implementing Digital Regulatory Reporting becomes significantly easier.
Adopting this framework provides a quicker time-to-market and creates a fully auditable trail from the initial interpretation of the rules through to the final submission. A critical advantage of this approach is the prevention of "interpretation drift," ensuring that traceability remains central to the compliance workflow. Furthermore, by embedding validation rules directly into the reporting framework prior to submission, firms can avoid the duplication of validation efforts between themselves and Trade Repositories. The industry is also discussing the future possibility of machine-readable rules published directly by regulators, which would further streamline this process. However, it is worth noting that regulators like the CFTC intend to maintain a neutral approach regarding technology, meaning that regulations will not be implemented in a specific technology or issued strictly as code in the near future.
As firms look to refine data quality further, the role of artificial intelligence is coming under the spotlight. The industry is currently exploring the use of AI tools to automatically detect reporting errors and highlight data anomalies. Discussions are also ongoing regarding how digital assets and smart contracts will ultimately impact trade reporting.
However, the consensus is that the implementation of AI must be handled in a highly surgical manner to avoid introducing new risks into the compliance pipeline. Crucially, AI tools still require strict oversight, meaning a human must remain in the middle of the workflow to control and verify the AI output. The actual reporting infrastructure must continue to rely on deterministic models, which can then be fed and supported by AI-driven insights to safely enhance efficiency without compromising accuracy.
Ultimately, achieving future-ready regulatory reporting requires a delicate balance. Financial institutions must actively adopt harmonised data standards and model-driven frameworks to streamline their compliance obligations, whilst remaining pragmatic and cautious in their deployment of emerging technologies like artificial intelligence.