DataConsultant helps finance, procurement, risk, compliance, operations, and technology teams establish governed legal entity records, reliable identifiers, defensible hierarchies, controlled onboarding, and traceable change processes. The service combines data assessment, entity resolution, master-data design, workflow, governance, integration, and operational support so critical decisions use a consistent view of organisations.
Legal entity master data is the governed information used to identify and relate organisations across finance, procurement, customer, risk, compliance, tax, legal, and operational processes. It typically includes registered names, company and tax identifiers, jurisdiction, addresses, status, ownership, parent relationships, and supporting evidence. DataConsultant helps data leaders and accountable business owners assess fragmented records, define the target model, establish matching and survivorship rules, design stewardship controls, and integrate trusted records into priority systems. The intended value is consistent entity identification, clearer ownership structures, more reliable reporting, and less manual reconciliation. Outcomes depend on source quality, stakeholder decisions, authoritative-data access, platform readiness, and continued stewardship.
The engagement can cover assessment, target-state design, implementation support, and ongoing stewardship. Scope is adjusted to the organisation’s systems, jurisdictions, control obligations, and priority business processes.
Review source systems, duplicate patterns, identifiers, hierarchies, workflows, ownership, policies, external data, integrations, and downstream usage.
Inputs: extracts, dictionaries, process maps, issue logs, audit findings, and stakeholder evidence.
Outputs: findings, data profile, control gaps, target scope, and prioritised requirements.
Define the entity model, identifier strategy, matching, survivorship, hierarchy, validation, workflow, stewardship, integration, and migration approach.
Client responsibility: approve definitions, provide system access, resolve policy choices, and assign accountable owners.
Outputs: specifications, configured rules, mappings, controls, test evidence, and transition plans.
Support exception queues, hierarchy changes, source onboarding, quality monitoring, release governance, rule tuning, reporting, and knowledge transfer.
Business value: preserves trust after launch and keeps entity records aligned with changing structures and obligations.
Start with business processes, control requirements, and entity decisions rather than a platform feature list.
Use controlled identifiers and matching rules to connect the same organisation across ERP, CRM, procurement, finance, risk, and reporting systems.
Separate legal ownership, ultimate parent, operating, commercial, and reporting structures while retaining effective dates and evidence.
Define who creates, verifies, approves, changes, monitors, and retires records, including escalation for ambiguous entities.
Preserve lineage from source records to golden records, match decisions, overrides, hierarchy changes, and downstream distribution.
Impact: payments, credit, spend, customer exposure, and reporting are split across multiple representations.
Response: profile data, define match rules, establish survivorship, and route uncertain cases to stewardship.
Impact: ownership, concentration, related-party, consolidation, and supplier-risk analysis can be incomplete.
Response: model legal relationships, effective dates, evidence, and hierarchy-specific use.
Impact: incomplete identifiers, inconsistent names, screening gaps, and rework enter operational systems.
Response: validate required attributes, approvals, evidence, segregation of duties, and exception handling.
Impact: nobody is accountable for definitions, disputes, or hierarchy maintenance.
Response: establish data owners, stewards, decision rights, service levels, and escalation routes.
Impact: teams cannot explain why one value is trusted or why a merge occurred.
Response: document authoritative sources, confidence, survivorship, lineage, overrides, and audit history.
Impact: corrected records are not distributed reliably to consuming applications.
Response: define publication events, APIs, batch interfaces, reconciliation, monitoring, and consumer contracts.
A focused discovery can identify the source systems, jurisdictions, processes, and entity attributes that need attention first.
Suitable for growing, complex, multi-system, multi-jurisdiction, or regulated organisations where entity identity and ownership affect material processes or reporting.
Validate registered identity, tax and company identifiers, parent relationships, status, duplicates, and screening references before activation.
Connect accounts to legal entities and groups to support exposure, credit, sanctions, KYC, and concentration analysis.
Maintain subsidiaries, branches, ownership changes, jurisdictions, effective dates, and reporting relationships.
Aggregate transactions across aliases, systems, and subsidiaries using governed entity and hierarchy keys.
Resolve overlapping entity records, preserve history, and establish crosswalks before system consolidation.
Use traceable entity identity and ownership structures to support scoped reporting and evidence collection.
Inventory systems, attributes, identifiers, formats, duplicates, completeness, conflicts, histories, relationships, and downstream consumers.
Define legal entity, branch, establishment, operating unit, parent, ultimate parent, status, jurisdiction, and relationship semantics.
Design deterministic and probabilistic matching, candidate thresholds, precedence, confidence, merge, unmerge, and manual review.
Model ownership and control relationships, effective dates, evidence, alternate hierarchy views, and change approval.
Define create, validate, approve, enrich, change, retire, dispute, escalation, queue management, and service reporting.
Design APIs, events, batch feeds, crosswalks, reconciliation, error handling, consumer contracts, and lineage.
| Deliverable | Purpose | Typical content |
|---|---|---|
| Current-state assessment | Establish evidence and priorities | System inventory, data profile, issues, controls, dependencies, maturity, and risks |
| Entity data model | Standardise definitions | Attributes, identifiers, statuses, relationships, hierarchies, effective dates, and metadata |
| Resolution rulebook | Control match and merge decisions | Rules, thresholds, source precedence, survivorship, confidence, exceptions, and unmerge controls |
| Governance and stewardship model | Assign accountability | Owners, stewards, RACI, workflow, service levels, escalation, access, and reporting |
| Integration and migration design | Move and distribute trusted records | Mappings, crosswalks, APIs, events, reconciliation, cutover, testing, and rollback |
| Operational control pack | Sustain quality after launch | KPIs, dashboards, runbooks, change control, issue management, training, and improvement backlog |
We can scope a concise assessment, an implementation-ready design, or end-to-end delivery support.
Objective: identify priority processes, obligations, entity decisions, and accountable stakeholders.
Output: agreed scope and evidence plan.
Objective: understand sources, duplicates, identifiers, hierarchies, quality, flows, and controls.
Output: current-state findings and risk priorities.
Objective: define entity semantics, ownership, stewardship, workflow, and control boundaries.
Output: approved target design.
Objective: specify matching, survivorship, validation, hierarchy, integration, and migration behaviour.
Output: implementation specifications and test criteria.
Objective: configure, migrate, integrate, test, reconcile, and resolve exceptions.
Output: validated release evidence and transition readiness.
Objective: establish runbooks, monitoring, stewardship, reporting, knowledge transfer, and improvement cycles.
Output: operated service and controlled backlog.
The service is platform-neutral. Relevant components are selected according to target architecture, data volumes, matching needs, operating model, licensing, security, and integration constraints.
Platform capability is only one part of a sustainable legal entity master data service.
Focused review of data, systems, governance, risks, quality, and options with prioritised recommendations.
Target model, governance, rulebook, architecture, roadmap, procurement support, and implementation assurance.
Configuration guidance, migration, integration, testing, reconciliation, release governance, and transition.
Exception handling, hierarchy maintenance, quality monitoring, source onboarding, reporting, and continuous improvement.
A multi-ERP organisation creates a governed supplier legal entity record, separates sites from legal organisations, links subsidiaries to ultimate parents, and introduces controlled duplicate review before vendor activation.
A financial-services team resolves customer accounts to registered counterparties and group structures, retaining source evidence and unresolved relationship flags for risk review.
A combined business establishes crosswalks between legacy entity identifiers, preserves historical ownership, and defines a phased migration to a shared master-data service.
| Outcome area | Illustrative KPI | Control consideration |
|---|---|---|
| Entity uniqueness | Confirmed duplicate rate; unresolved match queue | False merge and false split monitoring |
| Identifier completeness | Coverage of required registration and tax identifiers | Jurisdiction-specific validation and expiry |
| Hierarchy reliability | Coverage of approved parent and ownership relationships | Evidence, effective dates, and dispute handling |
| Operational service | Stewardship backlog, ageing, and resolution time | Priority, service level, capacity, and escalation |
| Distribution quality | Interface failures and reconciliation exceptions | Consumer acknowledgement and replay controls |
| Governance adoption | Policy adherence and accountable-owner participation | Decision logging and overdue approvals |
Business processes, entity types, countries, regulations, languages, and external data requirements.
System count, record volumes, history, duplicate patterns, identifiers, quality, lineage, and access.
Rule design, hierarchy modelling, workflow, integrations, migration, testing, security, and platform configuration.
Stewardship capacity, service levels, governance forums, training, onsite needs, and managed-support scope.
Pricing can be prepared after an initial discussion of systems, jurisdictions, priorities, and desired deliverables.
Connects legal entity definitions to finance, procurement, risk, compliance, operations, architecture, and platform requirements.
Records assumptions, evidence, match logic, hierarchy rules, ownership, exceptions, dependencies, and limitations.
Supports assessments, target design, implementation assistance, assurance, managed stewardship, and capability transfer.
Share the processes, systems, jurisdictions, and decisions that need a more reliable entity view.
Completeness, validity, uniqueness, consistency, timeliness, hierarchy integrity, and exception controls.
Role-based access, privileged actions, segregation of duties, encryption, logging, monitoring, and supplier access.
Purpose, minimisation, retention, residency, deletion, licensing, evidence handling, and individual-related attributes.
Control mapping, auditability, screening dependencies, regulatory reporting support, and authorised specialist review points.
ERP, CRM, procurement, customer onboarding, tax, treasury, risk, screening, data warehouse, and reporting platforms.
Company registries, tax sources, identifier providers, sanctions and risk data, commercial reference data, and client-maintained evidence.
Named owners and stewards, controlled access, support capacity, source agreements, release governance, monitoring, and consumer accountability.
Representative feedback is presented below to illustrate the delivery qualities organisations value in a Legal Entity Master Data Service engagement.
“The team helped us separate legal entities from supplier sites and trading names, which had been a recurring source of confusion. Workshops with finance and procurement produced clear definitions, a usable decision log, and a prioritised plan that our system owners could take forward.”
“Stakeholder discussions were handled carefully because different functions used the same entity terms in different ways. The consultants documented the conflicts, facilitated decisions, and revised the model after review without losing traceability. That made approval considerably more manageable.”
“We needed clearer accountability for parent relationships and ambiguous matches. The proposed stewardship workflow included ownership, escalation, supporting evidence, and service reporting. It was practical enough for operations while giving risk and compliance the control points they required.”
“The matching and survivorship principles were explained in business language rather than treated as a black box. We could see when exact identifiers should dominate, when name and address evidence was appropriate, and when a candidate needed human review instead of an automatic merge.”
“Implementation guidance covered migration crosswalks, reconciliation, release gates, and the transition into stewardship. The knowledge-transfer sessions gave our analysts a clear understanding of exception queues, hierarchy maintenance, and how rule changes should be tested before deployment.”
“Communication remained structured throughout the engagement. Actions, assumptions, dependencies, and unresolved policy points were visible in each review. Documentation was updated promptly after feedback, and the final pack was detailed enough for governance, procurement, and delivery teams to use.”
Answers cover scope, governance, technology, delivery, cost, controls, and ongoing operation.
Legal entity master data is the governed set of records used to identify organisations that a business owns, trades with, reports on, pays, regulates, or otherwise manages. It commonly includes registered names, identifiers, addresses, tax and registration attributes, ownership relationships, status, jurisdiction, and authoritative-source evidence.
The service can include current-state assessment, source-system and data-flow review, entity-definition design, identifier strategy, matching and survivorship rules, hierarchy modelling, stewardship workflows, data-quality controls, onboarding and change processes, integration design, migration planning, governance documentation, and operational reporting.
Sponsorship often comes from a chief data officer, CFO, COO, CIO, procurement leader, risk leader, compliance leader, or transformation executive. Delivery normally requires business owners from finance, procurement, sales, legal, compliance, tax, operations, data governance, architecture, security, and relevant system teams.
Common triggers include duplicate supplier or customer records, inconsistent company identifiers, unreliable group structures, onboarding delays, merger activity, fragmented ERP and CRM estates, regulatory reporting issues, sanctions-screening gaps, tax complexity, poor spend visibility, or repeated reconciliation work.
Matching can combine registration numbers, tax identifiers, legal names, addresses, domains, ownership links, source confidence, and jurisdiction-specific rules. Exact, deterministic, and probabilistic approaches may be used. Ambiguous candidates should be routed to controlled review rather than merged automatically.
A golden record is the governed representation of a legal entity assembled from approved sources using defined matching, validation, precedence, and survivorship rules. It retains traceability to source records and should not conceal uncertainty, conflicts, or unresolved evidence gaps.
Hierarchy design can represent immediate parent, ultimate parent, ownership percentage, control relationships, branches, subsidiaries, operating units, and historical changes. The model should distinguish legal ownership from commercial, reporting, and management hierarchies because these relationships may serve different purposes.
Depending on the environment, organisations may use MDM platforms, entity-resolution services, data-quality tools, workflow systems, data catalogues, integration platforms, graph databases, ERP and CRM hubs, cloud data platforms, and external reference-data providers. Technology selection follows requirements rather than leading them.
The design considers classification, access, retention, residency, lawful use, auditability, third-party licensing, screening obligations, segregation of duties, and evidence retention. The service supports control design but does not replace legal advice, statutory audit, certification, or formal regulatory approval.
There is no reliable fixed duration before discovery. Timing depends on the number of systems and jurisdictions, data volume and quality, hierarchy complexity, stakeholder availability, external-source access, target-platform readiness, integration dependencies, approval cycles, and whether implementation is included.
Pricing is influenced by assessment depth, source-system count, jurisdictions, record volumes, matching complexity, hierarchy requirements, workflow design, integrations, migration scope, technology configuration, operating-model work, documentation, training, and the selected advisory, implementation, or managed-service model.
Useful inputs include source extracts, data dictionaries, entity policies, registration and tax rules, hierarchy definitions, onboarding procedures, issue logs, audit findings, architecture diagrams, integration specifications, ownership information, system access, external-data contracts, and access to accountable business and technical stakeholders.
Relevant measures can include duplicate rates, unresolved match queues, identifier completeness, hierarchy coverage, source-to-golden-record traceability, onboarding cycle time, stewardship backlog, validation exceptions, integration failures, policy adherence, data freshness, downstream reconciliation effort, and adoption by priority processes.
Ongoing support can be structured around stewardship operations, exception management, quality monitoring, hierarchy maintenance, source onboarding, rule tuning, release control, reporting, and continuous improvement. Responsibilities, service levels, escalation routes, platform access, and retained client accountability are agreed during scoping.
