Key Takeaways
Regulatory frameworks globally are shifting from template-based reporting to granular, data-centric models for improved interoperability.
Global alignment creates opportunities for advanced analytics and technologies, turning compliance into a strategic advantage.
Firms must design adaptable, scalable architectures to stay agile amid continuous regulatory change.
Regulatory modernization is accelerating. The respective approaches to risk management and regulatory reporting in broader frameworks, such as the latest Basel reforms and International Reporting Framework (IReF), are indicators of a global trend. Domestic initiatives, such as Switzerland’s Einzelkrediterhebung (EKE), Canada’s Data Collection Modernization (DCM) and India’s Element-Based Reporting (EBR), are each advancing in parallel, signaling a shift in how jurisdictions envision reporting architecture and data collection.
Q&A with Dan Shmueli
Dan Shmueli, Vice President of Strategy of Regulatory Solutions Americas at Nasdaq, discusses regulatory reporting in 2025, upcoming Basel reforms and how Nasdaq supports clients with both global and local standards.
This global alignment toward granular data reporting and harmonized data standards presents an opportunity for leaders that far exceeds improved interoperability: To lead a transformational shift of their own—one that will enable breakthrough technologies and unlock advanced analytics that amplify risk intelligence and generate strategic insights.
In building an adaptable reporting foundation that approaches regulatory change as the norm, rather than responding to each update as a momentary exception, leaders will enhance their firm’s competitive positioning in capitalizing on growth opportunities when they emerge.
Granular Data Reporting: Upcoming Data-Centric Regulatory Frameworks
While upcoming frameworks vary in scope and mandate, they reflect a global trend toward a unified approach to modern regulatory reporting, in which the mere submission of accurate data is no longer sufficient.
These frameworks—scheduled to begin implementation from late 2025 through 2030—are shaping this global alignment with expectations for greater data granularity and standardization, along with more transparency and explainability in how data is sourced, validated and interpreted.
| Granularity | Harmonized Taxonomy | Transparency | |
|---|---|---|---|
| Basel reforms | Aggregation of risk metrics and governance across business lines, risk types, and legal entities | (not applicable) | Consistent, accurate and timely aggregation of risk data aggregation across the enterprise |
| IReF | Transaction-level and item-level reporting for statistical, prudential and resolution reporting | Consistent definitions | Single source of truth for improved data lineage and traceability |
| EKE | Attribute-level data for credit, liquidity and stress testing | (not applicable) | (not applicable) |
| DCM | Granular data elements | Consistent definitions | Clear data lineage for reduced ambiguity and improved traceability |
| EBR | Atomic, element-level data | Standardized classifications | Metadata enrichment for improved data lineage, traceability and validation |
Basel III Endgame: Standardizes approaches for measuring credit, market and operational risk instead of internal models, and enhances risk data and governance to meet stricter regulatory capital requirements
International Reporting Framework: Replaces fragmented national reporting with a single, standardized and granular data submission that harmonizes statistical, prudential and resolution reporting across Europe, improving data quality and reducing duplication
Switzerland’s Einzelkrediterhebung: Requires standardized core data elements across regulatory reports, improving data quality, reducing duplication and enabling automation and advanced analytics
Canada’s Data Collection Modernization: Requires standardized, metadata-rich data submissions through a new technology platform, improving data granularity, timeliness and quality while reducing ad-hoc reporting and enabling automation
India’s Element-Based Reporting: Requires standardized, metadata-rich data elements with validation rules, ensuring accurate, reusable and automated regulatory reporting that uses AI and SDMX standards
Common Principles of a Data-Centric Reporting Model
Here are common principles seen in the global regulatory shift to data-centric reporting, and how leaders can leverage this regulatory alignment to transform their firm’s approach.
Principle | Shift | Benefit | Strategic Opportunity |
|---|---|---|---|
Granularity and Standardization | From aggregated, template-based reporting to atomic data elements and harmonized taxonomies | Reduce data duplication and improve data quality | Adoption of advanced analytics: Gain deeper insights for strategic decision-making and identify organizational growth opportunities. |
Transparency and Explainability | From opaque models to enhanced data lineage and governance | Improve data traceability, auditability and interpretability | Amplification of critical risk data: Reduce ambiguity in risk assessments, strengthen regulator trust and accelerate responses to regulatory inquiries. |
Automation and Agility | From manual, template-driven processes to modular, scalable architecture | Create foundation for end-to-end automation | Adoption of advanced technologies: Leverage technologies—such as automation, AI and machine learning—to propel agility needed to absorb change without disruption and respond quicker to evolving regulatory requirements and market conditions. |
Building A Foundation for Adaptability in the Era of the Data-Centric Model
As frameworks align globally toward granular data reporting, building a foundation for adaptability means transitioning from reactive compliance to proactive architecture.
Rather than continual disruptive adjustments amid every regulatory update, institutions are built for ongoing regulatory evolution.
Here’s what an adaptable reporting system looks like:
Requirement | Benefit | Outcome |
|---|---|---|
Unified Data Foundation | Single source of truth for reporting data | Reduced efforts and resources spent on manual and custom adaptations for regulatory updates |
Rule Interpretation | Clear insight into regulatory intent | Reduced ambiguity of regulatory updates and accelerated implementation timelines |
Data Lineage and Transparency | Visibility of data flow from source to submission | Improved teams’ understanding of regulatory update impact, dependencies and downstream effects |
Continuous Assurance | Proactive anomaly detection | Reduced last-minute remediations |
Operational Oversight | Visibility of workflows across teams and jurisdictions | Removed bottlenecks keeps reporting on schedule and avoids regulatory penalties |
Scalable Deployment | Consistent, scalable deployment of regulatory updates | Standardized implementation and minimizes data silos |
Governance and Accountability | Consistent workflows with transparency into ownership structure and report status | Standardized reporting workflows |
Designing for Adaptability
As upcoming regulatory frameworks align globally toward principles of granularity, transparency and agility, leaders face a strategic inflection point: Maintain the status quo or embrace this regulatory alignment to lead a shift of their own.
Leaders should focus on moving beyond reactive compliance by designing an adaptable reporting system that expects continual regulatory change. Leaders can turn regulatory alignment into a strategic advantage and ensure readiness and adaptive resilience for an era where adaptability is the greatest competitive differentiator.
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