Dataconsultant helps banks and financial institutions establish practical governance for data used in regulatory reporting, risk aggregation, finance, compliance, and supervisory evidence. The service connects obligations to accountable owners, critical data elements, lineage, quality controls, issue workflows, and oversight so teams can improve traceability, decision discipline, and sustained control operation.
Regulatory data governance is the structured system of accountability, policies, definitions, controls, traceability, evidence, and oversight used to ensure data supporting regulatory obligations is fit for purpose. It covers more than a governance committee or data catalogue. A working model links obligations and reports to accountable executives, data owners, stewards, critical data elements, source-to-report lineage, quality and reconciliation controls, issue remediation, change management, attestations, and management information. Dataconsultant can assess the current environment, design the target model, support remediation, and help operate selected governance activities.
A general data governance programme may not provide the depth of traceability, control evidence, or accountable reporting needed for prudential, risk, finance, conduct, or supervisory obligations.
Weak ownership, incomplete lineage, insufficient evidence, or overdue remediation.
Different definitions, source systems, transformations, adjustments, and reconciliation outcomes.
Spreadsheet controls, end-user computing, undocumented adjustments, and key-person risk.
Cloud migration, data-platform replacement, core banking change, merger, or reporting redesign.
New reports, jurisdictions, legal entities, risk measures, disclosures, or evidence requirements.
This service is suitable when the organisation needs a documented regulatory data operating model, clear accountability, critical data governance, lineage and control remediation, evidence-ready oversight, or coordinated improvement across risk, finance, compliance, data, and technology.
A narrow report-development request, independent legal opinion, statutory audit, model validation, penetration test, or formal compliance certification requires separate specialist services. Dataconsultant can help define interfaces and data requirements but does not replace authorised assurance or legal functions.
The governance model should reflect the obligation, data journey, risk materiality, operating structure, and evidence expected in each reporting or decision context.
Govern data used for capital adequacy, liquidity, leverage, exposures, concentrations, and supervisory returns through clear definitions, lineage, controls, ownership, reconciliation, and evidence.
Improve governance of credit, market, liquidity, operational, climate, and enterprise risk data used in limits, aggregation, stress testing, management reporting, and escalation.
Connect finance data definitions, chart-of-account mappings, consolidation logic, adjustments, reconciliations, controls, and sign-offs to responsible owners and governed evidence.
Define accountability and quality controls for customer, transaction, screening, monitoring, case, and reporting data while respecting privacy, retention, access, and legal-review requirements.
Map new or amended obligations to reports, definitions, critical data, systems, controls, owners, policies, and implementation actions with versioned decisions and traceable approvals.
Embed regulatory data requirements into migration, lakehouse, warehouse, integration, catalogue, quality, and reporting designs before legacy controls and evidence are retired.
The final scope is selected according to the obligations, reports, legal entities, data domains, existing controls, technology environment, and remediation priorities.
Review policies, committees, roles, inventories, reporting processes, critical data, lineage, quality controls, reconciliations, issue logs, audit findings, technology, evidence, training, and operating metrics. Outputs identify strengths, gaps, material risks, dependencies, and decisions requiring authorised regulatory review.
Create or improve a structured inventory connecting applicable obligations, returns, disclosures, risk measures, management reports, legal entities, owners, data domains, systems, controls, and evidence. The inventory supports impact analysis, prioritisation, change management, and demonstrable accountability.
Identify material data attributes based on regulatory impact, risk, usage, aggregation, reporting sensitivity, and control dependence. Define business meaning, calculation rules, valid values, authoritative sources, ownership, quality thresholds, and permitted transformations.
Define executive accountability, report ownership, domain ownership, stewardship, control ownership, issue escalation, approval rights, committee mandates, RACI, attestation responsibilities, and interfaces with compliance, risk, finance, audit, privacy, security, and technology.
Establish lineage standards and trace critical data from source through integration, transformation, aggregation, adjustment, reporting, and disclosure. Document manual steps, end-user computing, model or rule dependencies, reconciliation points, and change-control requirements.
Design preventive, detective, and corrective controls aligned to material data risks. Define rules, thresholds, monitoring frequency, exception handling, reconciliation, tolerance approval, root-cause analysis, control evidence, ownership, and reporting.
Create consistent severity, ownership, ageing, root-cause, action, dependency, closure, validation, and risk-acceptance practices. Link findings to affected obligations, reports, data, controls, systems, and committees while maintaining an auditable evidence trail.
Support mobilisation, policy rollout, tool configuration requirements, data-owner and steward enablement, governance routines, committee packs, KPI reporting, evidence maintenance, control monitoring, regulatory-change impact, and continuous improvement.
Deliverables are tailored to the engagement and should be reviewed by accountable banking, risk, compliance, legal, audit, and technology stakeholders where relevant.
| Deliverable | What it covers | Typical format | Client input required |
|---|---|---|---|
| Governance assessment | Maturity, gaps, risks, evidence, and prioritised findings | Assessment report and findings register | Policies, interviews, inventories, audit findings, samples |
| Regulatory data inventory | Obligations, reports, owners, domains, systems, controls, evidence | Governed register or tool requirements | Regulatory inventory, report catalogue, legal entities |
| Critical data register | Definitions, materiality, sources, owners, thresholds, controls | Data dictionary or catalogue specification | Report fields, calculations, risk and finance definitions |
| Operating model and RACI | Accountability, decision rights, forums, escalation, attestations | Operating-model pack and role profiles | Organisation structure, committees, policy mandates |
| Lineage and control standards | Traceability, quality, reconciliation, change, evidence requirements | Standards, templates, and control catalogue | Architecture, data flows, rules, control evidence |
| Remediation roadmap | Priorities, owners, dependencies, sequencing, acceptance criteria | Roadmap, work packages, and decision log | Risk appetite, programmes, budgets, resource constraints |
| KPI and oversight framework | Coverage, quality, issues, controls, evidence, adoption, ageing | Dashboard specification and committee pack | Baselines, reporting cadence, management needs |
| Training and transition | Role-based guidance, routines, handover, managed support | Training materials and operating procedures | Audience groups, learning needs, support model |
The sequence is adapted to urgency, regulatory context, evidence availability, transformation dependencies, and whether the work is assessment, design, remediation, or managed support.
Confirm obligations, reports, entities, jurisdictions, stakeholders, decision rights, evidence sources, constraints, and review requirements.
Primary output: agreed scope, governance, information request, and workplan.Review policies, roles, reports, critical data, lineage, quality, controls, issues, technology, committees, and findings.
Primary output: evidence-based current-state assessment and risk-ranked gaps.Connect reports and supervisory needs to definitions, critical data, sources, transformations, controls, owners, and evidence.
Primary output: regulatory data inventory and traceability map.Define accountability, forums, policies, standards, lineage, control expectations, issue processes, attestations, metrics, and tooling needs.
Primary output: target operating model and control framework.Sequence improvements by regulatory materiality, risk, dependency, feasibility, existing programmes, and evidence required for closure.
Primary output: remediation roadmap, work packages, owners, and acceptance criteria.Review deliverables with accountable teams, support implementation, train roles, establish oversight routines, and document limitations.
Primary output: approved governance pack, transition plan, and measurement approach.Technology supports governance, but tools do not replace accountable ownership, clear definitions, effective controls, operating discipline, or evidence of sustained performance.
Metadata catalogues, business glossaries, lineage tools, data-quality platforms, master and reference-data systems, warehouses and lakehouses, integration platforms, regulatory reporting systems, GRC platforms, workflow and ticketing tools, document repositories, identity and access systems, and management-reporting tools.
Framework and regulatory applicability varies by jurisdiction, legal entity, business model, and obligation. Formal interpretations and compliance conclusions must be validated by authorised legal, compliance, risk, audit, or regulatory specialists.
Dataconsultant can support a focused need or a broader regulatory data-governance programme while preserving clear client accountability.
Independent review of selected obligations, reports, domains, controls, findings, or governance capabilities.
Design or refresh accountability, inventory, critical data, lineage, quality, controls, issues, committees, metrics, and evidence.
Support workstream planning, governance implementation, documentation, tool requirements, control rollout, testing coordination, and closure evidence.
Ongoing coordination, monitoring, committee reporting, issue tracking, evidence maintenance, owner enablement, and continuous improvement.
A reliable estimate requires initial discovery. Fixed claims about cost or duration would be misleading without understanding the regulatory, organisational, and technical environment.
Measures should be linked to a documented baseline, risk appetite, regulatory materiality, and the organisation’s ability to attribute improvements.
| Measure | What it indicates | Important interpretation |
|---|---|---|
| Critical data ownership coverage | Percentage of in-scope critical data with approved owners and stewards | Coverage does not by itself prove effective ownership |
| Lineage coverage and validation | Extent of documented and reviewed source-to-report traceability | Depth should match materiality and control need |
| Data quality control performance | Rule execution, exceptions, breaches, ageing, and recurrence | Thresholds require business and regulatory context |
| Reconciliation breaks | Volume, value, age, root cause, and closure of differences | Materiality is more useful than raw counts alone |
| Issue remediation | Open issues, overdue actions, recurrence, and validated closure | Closure quality matters more than speed alone |
| Evidence completeness | Availability and quality of approvals, control records, attestations, and decisions | Evidence should demonstrate operation, not only design |
| Governance participation | Decision timeliness, attendance, escalations, and unresolved dependencies | Meeting activity is not a substitute for outcomes |
It is the accountability, policy, definition, lineage, control, issue, evidence, and oversight system used to ensure data supporting regulatory obligations is governed and fit for its intended purpose. It connects obligations and reports to owners, critical data, systems, transformations, controls, and demonstrable management action.
Scope can include assessment, regulatory data inventory, critical data elements, ownership and stewardship, lineage, data quality and reconciliation controls, reporting governance, issue management, evidence standards, governance forums, remediation planning, implementation support, training, and managed governance activities.
The work can support data-governance implementation for applicable prudential, risk, finance, conduct, privacy, resilience, and reporting obligations, including BCBS 239-related governance needs. Exact applicability and formal interpretation must be confirmed by authorised legal, compliance, risk, audit, or regulatory specialists.
No. Dataconsultant supports data governance, controls, implementation, documentation, and operations. The service does not replace legal advice, regulator approval, statutory audit, independent assurance, or formal compliance certification unless separately provided by appropriately authorised parties.
Critical data is identified by tracing regulatory reports, risk measures, disclosures, decisions, and control obligations to the attributes whose failure could materially affect completeness, accuracy, timeliness, reconciliation, explainability, or compliance. Materiality criteria and approvals are documented.
Lineage can cover source systems, interfaces, transformations, calculations, aggregations, models or rules, manual adjustments, reconciliations, reporting layers, and disclosures. The appropriate depth depends on data criticality, regulatory risk, control requirements, platform capability, and evidence needs.
Typical outputs include an assessment, obligation-to-data map, inventory, critical data register, governance model, RACI, lineage and quality standards, control catalogue, issue workflow, evidence register, committee terms, remediation roadmap, KPI framework, and training or operating materials.
There is no reliable fixed duration before discovery. Timing depends on the number of obligations, reports, entities, jurisdictions, systems, critical data elements, existing lineage and control quality, stakeholder access, evidence availability, remediation depth, and governance review cycles.
Pricing is influenced by scope, regulatory breadth, number of reports and entities, data complexity, lineage depth, control assessment or implementation needs, documentation quality, stakeholder workshops, onsite requirements, tool support, training, and the selected engagement model.
Yes. The service can work alongside internal teams, systems integrators, platform vendors, auditors, and other advisers. Existing catalogues, lineage tools, quality platforms, reporting systems, GRC tools, ticketing systems, and repositories can be assessed and incorporated into the target approach.
Yes, for data-governance elements such as accountability, risk data inventories, critical data, lineage, quality controls, issue management, reporting governance, evidence, KPIs, and remediation coordination. Formal compliance conclusions and regulatory interpretations remain the responsibility of authorised client or independent specialists.
Useful inputs include obligation and report inventories, organisation and committee structures, policies, data definitions, lineage, architecture, control catalogues, quality results, reconciliations, issue logs, audit findings, system documentation, change portfolios, evidence samples, and access to accountable stakeholders.
Yes. Managed support can include governance coordination, owner and steward enablement, KPI reporting, issue monitoring, committee packs, evidence maintenance, regulatory-change impact support, control monitoring coordination, training, and continuous improvement under clearly documented client accountability.
The governance design can include classification, access, segregation of duties, retention, residency, transfer, vendor dependency, outsourced processing, incident, and evidence requirements. Specific legal, security, and regulatory conclusions require review by authorised specialists.
