Reporting is moving from periodic submission to continuous data discipline. The future operating model will be built around reusable, validated and harmonized transaction data.
Overview
Regulatory reporting has become one of the most sophisticated and costly areas of financial operations. Firms must report similar but not identical data across multiple regimes, using different templates, validation rules, identifiers, reconciliation tolerances and submission channels. The result is duplication, operational risk and recurring remediation effort.
EMIR REFIT made this pressure visible. The revised EMIR reporting technical standards became applicable on 29 April 2024 and introduced a stronger focus on validation rules, reconciliation tolerances and ISO 20022 XML schemas. For many institutions, this was not only a regulatory change. It was a data architecture stress test.
European regulatory discussions are also exploring a comprehensive approach for simplifying financial transaction reporting. One direction under consideration is the possibility of applying a 'report once' principle across MiFIR, EMIR and SFTR, potentially through a unified template and harmonized legal frameworks. Even if implementation is long-term, the strategic direction is clear: reporting models built on duplicated manual transformations are becoming unsustainable.
The reporting problem is a data problem
Regulatory reporting failures rarely originate only in the reporting engine. They usually arise from upstream data quality issues: incomplete trade capture, inconsistent identifiers, missing counterparty data, conflicting product classifications, late lifecycle events, weak reference data or unclear ownership of corrections.
A reporting team can repair some errors manually, but this does not scale. The more regimes converge toward standardized schemas and tighter validation, the more firms need clean, controlled data before reporting, not after rejection by a trade repository or authority.
The target state is an integrated reporting data layer: trade, counterparty, product, collateral, valuation, lifecycle and reference data captured once, validated at source, enriched through controlled processes and reused across reporting obligations.
Why report once matters
The report-once concept is not merely a policy slogan. It reflects a practical need to reduce overlapping reporting obligations while preserving regulatory information scope. If reporting data is captured consistently, authorities can receive what they need without forcing firms to rebuild the same transaction story multiple times under different regimes.
For institutions, the benefits would include fewer reconciliations between regimes, reduced duplicate submissions, clearer ownership of data lineage and lower remediation costs. However, the transition would not be simple. A unified reporting model requires harmonized definitions, strong data governance, common identifiers, systems integration and robust change management.
Firms should therefore not wait for final regulatory simplification. They should prepare by building a reporting architecture that can support harmonization when it arrives.
Operating model implications
A future-ready regulatory reporting function needs three capabilities. First, regulatory interpretation must be connected to data implementation. Legal and compliance teams must translate requirements into data fields, rules and controls, not only policy memos.
Second, data ownership must move upstream. Operations, trading, finance, risk and technology must understand which data points they own and how their processes affect reporting quality. Reporting teams should not be the last line of manual correction.
Third, management oversight must rely on quality indicators. Rejection rates, late submissions, reconciliation breaks, manual adjustments, field-level issues and root causes should be visible to senior stakeholders. Regulatory reporting quality should be managed as an operational risk indicator.
From remediation to industrialization
Many institutions still manage reporting change through tactical projects. A new RTS, validation rule or schema update triggers a project team, manual mapping, user acceptance testing and a post-go-live issue backlog. This approach is expensive and vulnerable to repeat failures.
The alternative is industrialization: reusable data models, standardized mappings, automated controls, regression testing, traceable lineage and integrated issue management. Under that model, regulatory change is still substantial, but it becomes manageable.
Our Approach
- Reporting Diagnostic - Assess current reporting processes, data lineage, controls, rejection causes, manual adjustments and technology dependencies.
- Data Model and Lineage - Define reusable reporting data domains across transactions, counterparty, product, valuation, collateral and lifecycle events.
- Control Framework - Implement validation, reconciliation, exception workflow, approval evidence and root-cause monitoring.
- Operating Model Redesign - Clarify ownership across compliance, operations, finance, risk, IT and business lines.
- Regulatory Change Readiness - Prepare the reporting architecture for future harmonization and report-once models.
