Spreadsheet-heavy assemblyCritical logic and adjustments live in local files with limited repeatability.
Regulatory Reporting Solution
Regulatory Reporting That Connects Source Data to Controlled, Traceable Reporting Outputs
DataConsultant helps enterprises design, implement and improve the data capability behind regulatory reporting: controlled sourcing, report-ready data, documented transformations, calculations, reconciliations, exceptions, approvals, lineage and retained evidence. The goal is a repeatable reporting process that accountable teams can understand, review and operate without treating the final report as a disconnected spreadsheet exercise.
Source-to-report lineage
Controlled calculations
Reconciliations & validation
Review & approval ownership
Decision-ready evidence
From Source Systems to Controlled Reporting Evidence
Where Regulatory Reporting Breaks Down
The reporting deadline exposes problems that usually start much earlier in the data chain: unclear definitions, fragmented sourcing, undocumented calculations, weak reconciliations and person-dependent review steps.
Weak field lineageTeams cannot show where material values originated or how they changed.
Undocumented calculationsRules, mappings and overrides are difficult to test or reproduce.
Late source defectsMissing, stale or inconsistent data is discovered close to submission.
Incomplete reconciliationsControl totals and variances do not cover the material reporting chain.
Fragmented accountabilityReporting, finance, compliance, risk, data and IT hand-offs are unclear.
Difficult change impactNew templates, rules or sources trigger manual discovery and regression risk.
Thin evidence trailApprovals, exceptions, rationale and supporting artefacts are hard to reconstruct.
Move From Deadline-Driven Reporting to a Controlled Reporting Capability
The target state separates data preparation, calculation, control, approval and evidence while connecting them through traceable ownership and change management.
Current state
- Multiple manual extracts and reconciliations
- Definitions differ across teams and systems
- Critical logic embedded in spreadsheets
- Exceptions resolved through email and memory
- Lineage assembled after the fact
- Change testing depends on individual knowledge
Target state
- Owned report fields and controlled source mappings
- Versioned transformation and calculation logic
- Documented validation and reconciliation controls
- Workflow-based exceptions and approvals
- Source-to-report evidence and lineage
- Release, regression and reporting-cycle monitoring
Stabilise the Reporting Data Chain Before the Next Reporting Change Becomes Urgent
Start with the material reports, source systems, calculation logic, recurring exceptions and evidence gaps that create the most operational risk.
Assess Reporting Data GapsWhat the Regulatory Reporting Solution Controls
A complete solution is more than report generation. It connects confirmed reporting requirements to data, processing, controls, decision rights, evidence and repeatable operation.
Controlled reporting from requirement to evidence
DataConsultant can help translate confirmed reporting obligations and internal reporting policies into a technical and operational design that makes material data and logic visible, testable and governable.
- Field-level reporting data requirements
- Source-system and ownership mapping
- Transformation and calculation specifications
- Data-quality and reconciliation controls
- Exception, review and approval workflows
- Technical and business lineage
- Change-control and regression-test design
- Evidence retention and operational runbooks
Reporting Data Model
Define report-ready entities, measures, dimensions, reference periods and critical fields.
Transformation Logic
Document mappings, aggregations, classifications, adjustments and effective dates.
Calculation Controls
Version formulas, parameters, rounding, thresholds and reusable business logic.
Reconciliation
Compare report outputs with approved sources, totals, periods and control points.
Approval & Evidence
Route exceptions, reviews, sign-offs and retained support through controlled workflows.
Change Management
Assess rule, template, source, calculation and platform changes before release.
Regulatory Reporting Architecture: Source, Calculate, Reconcile, Approve, Evidence
The reference architecture keeps the reporting chain explicit. Specific technologies vary, but the control points should remain understandable across business, data, technology, risk and assurance teams.
Calculation engineering: make reporting logic testable
Material logic should be explicit enough for reporting owners and engineers to understand how a value is produced and how a change affects downstream outputs.
- 01Map each calculation to defined source fields and approved business meaning.
- 02Separate reusable transformations from report-specific calculation logic where practical.
- 03Version formulas, mappings, parameters, classifications and effective dates.
- 04Define expected results and regression tests for material rules and edge cases.
- 05Record controlled overrides and adjustments with rationale, owner and approval.
| Control point | Question | Evidence | Owner |
|---|---|---|---|
| Source completeness | Did all required sources arrive for the reporting cut-off? | Load status, counts, exceptions | Data owner |
| Calculation validation | Did versioned logic produce expected values? | Test results, rule version, variance | Reporting / engineering |
| Reconciliation | Do report totals reconcile to approved reference points? | Control totals, explanations, approvals | Control owner |
| Exception closure | Were material breaks resolved or explicitly accepted? | Issue record, rationale, sign-off | Reporting owner |
| Release approval | Is the reporting output authorised for release? | Review record and final approval | Accountable approver |
Reporting Decisions and Actions by Process Stage
Each stage should make the required information, control decision and next action explicit.
| Process stage | Required information | Decision | Action | Evidence |
|---|---|---|---|---|
| Data intake | Expected sources, cut-off, record counts, freshness | Is the reporting dataset complete enough to proceed? | Accept load or raise source exception | Load log and source exception record |
| Transformation | Mappings, classifications, effective-date logic | Is the approved transformation version being applied? | Process data or route configuration issue | Version and execution record |
| Calculation | Formulas, parameters, reference data, adjustments | Are calculated values within expected control ranges? | Continue, investigate variance or correct controlled logic | Calculation results and test evidence |
| Reconciliation | Control totals, authoritative references, prior period | Are differences explained and acceptable? | Close, remediate or escalate exception | Reconciliation and approval record |
| Review & release | Output, exceptions, lineage, sign-offs | Is the report ready for authorised submission or publication? | Approve, hold or return for remediation | Final approval and retained evidence |
Make Every Material Reporting Value Explainable From Source to Approval
Design the data model, transformations, reconciliations and evidence trail around the reporting decisions your reviewers actually need to make.
Define Your Reporting Control ModelReporting Data Requirements and Enterprise Integration
Regulatory reporting normally spans multiple domains and systems. Readiness is less about having perfect data than knowing which fields are material, who owns them, how they are defined, how frequently they arrive and which controls apply.
Finance & ledger data
Balances, postings, entities, accounts, periods and reconciliation references where relevant.
- General ledger and sub-ledgers
- Chart of accounts and legal entities
- Period-close and adjustment data
Risk & control data
Exposures, classifications, control results, limits and risk measures where applicable.
- Risk engines and control repositories
- Materiality and classification data
- Issue and exception records
Operational & business data
Transactions, products, customers, contracts, assets, events and operational measures.
- ERP, CRM and operational applications
- Product, customer and transaction systems
- Asset, workforce or service systems
Reference, metadata & evidence
Definitions and control context needed to interpret and reproduce the report.
- Reference and master data
- Business glossary and lineage
- Policies, approvals and retained artefacts
Enterprise ApplicationsERP, finance, risk, CRM, operational and external sources
Integration & StorageBatch, API, CDC, ETL or ELT, warehouse or lakehouse
Reporting Data LayerModels, snapshots, reference data, quality and metadata
Control & WorkflowCalculations, reconciliations, exceptions, review and approval
Report & EvidenceSubmission format, archive, lineage and decision records
Governance, Security, Privacy and Change Control Across the Reporting Cycle
Controls should follow the data from intake through release. The exact control set depends on reporting materiality, data sensitivity, technology, internal policy and applicable obligations.
Critical-field ownership
Assign accountable owners for material data elements, definitions, quality rules and approved sources.
Least-privilege access
Restrict source, transformation, adjustment, review and release permissions to approved roles.
Segregation of duties
Separate preparation, material adjustment, control review and final approval where required.
Data quality controls
Define completeness, validity, consistency, timeliness and reasonableness checks for reporting risk.
Lineage & metadata
Maintain business and technical traceability from report field to source, rule, owner and transformation.
Privacy & retention
Identify sensitive data, minimise unnecessary use and apply approved retention and handling requirements.
Change & release
Assess impacts from regulatory, source, model, mapping, platform and organisational changes before production.
Evidence & auditability
Retain control execution, exceptions, decisions, approvals, versions and supporting artefacts for review.
Operating Model: Clear Accountability From Data Owner to Final Approver
A reporting solution remains reliable only when decision rights, hand-offs, escalation and change ownership are explicit.
Design Reporting Controls That Survive Platform, Source and Requirement Changes
Connect ownership, security, quality, lineage, testing and approval so reporting changes can be assessed before they become production incidents.
Discuss Your Reporting ControlsFrom Reporting Scope to Operational Transition
Implementation should be sequenced around reporting materiality, data readiness, control risk and reuse. Timeline is confirmed during scoping rather than assumed from a generic project template.
Scope & requirement alignment
Confirm reports, entities, reference dates, accountable owners, authorised interpretations and decision criteria.
Output: traceable reporting scopeCurrent-state data & control assessment
Map sources, spreadsheets, transformations, manual adjustments, reconciliations, controls, issues and evidence.
Output: current-state risk mapTarget reporting design
Define data model, lineage, transformations, calculations, control points, workflow, access and evidence architecture.
Output: target solution blueprintBuild, remediate & integrate
Implement data flows, rule logic, reconciliations, exception routing, metadata and approved platform integrations.
Output: configured reporting capabilityTest, reconcile & approve
Run data tests, expected-result checks, parallel reconciliations, defect resolution and evidence-based acceptance.
Output: tested release evidenceTransition, monitor & improve
Establish runbooks, reporting-cycle monitoring, ownership, service measures, change intake and knowledge transfer.
Output: operational reporting modelReporting Evidence and Operational Monitoring
Monitoring should show whether the reporting cycle is healthy and where intervention is needed. Targets are agreed for the organisation rather than invented on the page.
Source intake evidenceArrival, cut-off, volume, freshness and failed-load records.
Calculation evidenceRule version, input parameters, execution results and test status.
Reconciliation evidenceControl totals, variance explanations, owner decisions and closure.
Exception evidenceIssue severity, root cause, remediation, acceptance and escalation.
Approval evidenceReviewer, approver, timestamp, scope and material exceptions.
Change evidenceImpact analysis, test results, release approval and effective date.
Tangible Regulatory Reporting Deliverables
Deliverables are selected according to whether the engagement is assessment, design, implementation, remediation or operational support.
Reporting Requirement Inventory
Reports, fields, definitions, frequencies, entities, owners and dependencies.
Source & Lineage Map
Field-level sources, transformations, calculations, adjustments and outputs.
Reporting Data Model
Report-ready entities, measures, dimensions, reference data and periods.
Transformation & Calculation Specs
Mappings, formulas, classifications, parameters, versions and edge cases.
Control & Reconciliation Framework
Checks, tolerances, control totals, owners, evidence and escalation.
Exception & Approval Workflow
Routing, decision rights, segregation, closure criteria and sign-off points.
Testing & Change Pack
Test cases, regression coverage, impacts, defects, releases and approvals.
Operating Runbook
Cycle calendar, responsibilities, monitoring, support and improvement backlog.
Business outcomes a controlled reporting capability can support
- More consistent and repeatable reporting preparation
- Clearer source-to-report traceability for material values
- Earlier visibility of data, calculation and reconciliation issues
- More structured exception handling and approval decisions
- Better-controlled change impact analysis and regression testing
- Clearer accountability across reporting, data and technology teams
- More complete evidence for internal review and assurance activities
- Reduced dependence on undocumented individual knowledge
When this solution is a strong fit
- Reporting relies on many source systems, manual transformations or spreadsheets.
- Source-to-report lineage is incomplete or difficult to maintain.
- Repeated reporting defects or reconciliation breaks consume review time.
- A platform migration or data transformation must preserve reporting continuity.
- New reporting requirements require controlled data and change implementation.
- Ownership, approvals and evidence are fragmented across business and technology.
Custom Scope & Pricing for Regulatory Reporting
DataConsultant does not publish a fixed price for this solution. A reliable estimate requires the actual reporting scope, source landscape, control depth and delivery model.
Request a Quote Based on the Reporting Work That Actually Needs to Be Done
Scope can focus on one report, one reporting family, one legal entity, a remediation programme, a platform transition or a wider reporting operating model. Third-party software, cloud consumption or licence costs are separate unless explicitly included in the agreed scope.
Request a Regulatory Reporting QuoteReporting coverageReports, entities, jurisdictions, frequencies and reference periods.
Source complexitySystems, interfaces, volumes, identifiers, historical depth and cut-offs.
Calculation logicTransformations, formulas, mappings, parameters and controlled adjustments.
Control depthQuality rules, reconciliations, evidence, approvals and exception workflow.
Technology changeNew pipelines, data stores, reporting tools, metadata or workflow integration.
Delivery modelAssessment, design, implementation, remediation, training or managed support.
What DataConsultant Needs From Your Team
Missing information can be documented as a limitation. It should not be silently assumed.
Confirmed requirementsCurrent report templates, definitions, interpretations and reporting calendar.
Source evidenceSystem inventories, mappings, data dictionaries, representative data and lineage.
Control contextReconciliations, policies, prior findings, issue logs, approvals and known exceptions.
Accountable stakeholdersReporting, compliance, finance, risk, data, engineering, security and platform owners.
Build a Regulatory Reporting Capability That Can Be Explained, Tested and Operated
Bring your reports, recurring issues, source landscape and change priorities. We can scope the data, control and implementation work required for the next stage.
Discuss Your Reporting ScopeRelated DataConsultant Solutions
Regulatory reporting often depends on broader data quality, observability and governed-data capabilities. These adjacent solutions may be relevant when the reporting problem extends beyond the report itself.
Regulatory Reporting Frequently Asked Questions
Practical questions about reporting data, controls, architecture, implementation, scope and operating responsibility.
What is a regulatory reporting solution?
A regulatory reporting solution is the controlled data, transformation, calculation, reconciliation, review, approval and evidence capability used to prepare repeatable reporting outputs from enterprise source systems. The exact reports, fields, rules, submission formats and control obligations depend on the organisation, jurisdiction and applicable reporting requirements.
What problems does regulatory reporting modernisation address?
Common problems include spreadsheet-heavy consolidation, inconsistent definitions, undocumented adjustments, weak source-to-report lineage, late source data, repeated reconciliation breaks, unclear ownership, manual sign-offs, difficult change impact analysis and limited evidence of how a submitted value was produced.
What data is normally required for regulatory reporting?
Required data depends on the reporting obligation but may include finance, ledger, risk, customer, product, transaction, operational, asset, reference, master and externally supplied data. A reliable design also needs metadata such as field definitions, source ownership, reporting periods, calculation logic, lineage, quality rules, adjustments and control evidence.
Does DataConsultant interpret regulations or provide legal advice?
DataConsultant can translate confirmed reporting requirements into data, architecture, workflow and control requirements. Legal interpretation, regulatory sign-off, statutory audit, formal assurance and other activities requiring authorised specialists remain outside scope unless separately and appropriately commissioned.
Can the solution work with our existing reporting platform?
Yes, where the existing platform can meet the agreed requirements. The solution can integrate with current source systems, data warehouses, lakehouses, ETL or ELT tooling, data-quality platforms, metadata catalogues, workflow tools, reporting applications and evidence repositories. Technology recommendations are based on requirements rather than forcing a replacement.
How are calculations and transformations controlled?
Material calculations and transformations should have defined business logic, source mappings, version control, approval ownership, test cases, effective dates and change records. The implementation can separate reusable transformation logic from report-specific rules so changes can be assessed and tested before release.
How are reconciliations and exceptions handled?
Reconciliations can compare report-ready data with authoritative sources, control totals, prior periods, ledgers, operational records or other approved reference points. Exceptions should be assigned to an owner, investigated, documented, approved where necessary and tracked to closure with retained evidence.
Is AI required for regulatory reporting?
No. Core regulatory reporting can be implemented with deterministic data engineering, calculation, validation, reconciliation and workflow controls. AI or machine learning may be considered for supporting activities such as anomaly triage or document analysis only when the use case is appropriate, explainable and governed.
How does the solution support data lineage and auditability?
The design can connect report fields to source systems, data elements, transformations, calculations, adjustments, controls and approvals. Technical lineage, business lineage and retained evidence help reviewers understand where a value came from, how it changed and which decisions affected the final output.
Can DataConsultant modernise one report before scaling wider?
Yes. A focused report, reporting family, legal entity or process can be used to validate the data model, transformation pattern, controls, reconciliation approach, evidence model and operating workflow before broader rollout. The pilot scope should be chosen around materiality, complexity and reuse potential.
How long does a regulatory reporting engagement take?
Timeline is confirmed during scoping. It depends on the number of reports and entities, source-system complexity, quality of existing documentation, historical data needs, calculation and reconciliation depth, technology changes, control requirements, testing cycles, stakeholder availability and rollout scope.
How is regulatory reporting pricing calculated?
DataConsultant does not publish a fixed price for this solution. Pricing is scope-led and depends on reporting coverage, source systems, data complexity, transformation and calculation logic, control depth, lineage, integrations, testing, documentation, governance, security, implementation involvement and any ongoing operational support. A quote is provided after discovery.
What does DataConsultant need from the client?
Useful inputs include confirmed reporting requirements, current report templates, source-system information, data dictionaries, existing mappings and calculations, control documentation, prior issues or findings, representative data samples, reporting calendars, platform constraints and access to accountable reporting, compliance, finance, risk, data and technology stakeholders.
Can DataConsultant support ongoing reporting operations?
Ongoing support can be scoped for reporting data preparation, scheduled controls, exception management, reconciliations, evidence assembly, operational monitoring, issue tracking, change support and continuous improvement. Regulatory accountability, interpretation and final submission approval remain with the client unless a different lawful responsibility model is explicitly agreed.
Request a Regulatory Reporting Scope Review
Share your contact details and requirement. DataConsultant can review the likely reporting-data scope, stakeholder involvement, dependencies and appropriate next step.