Domain E · Area E-CA3 · Data quality, comparability, lineage and system controls

E.7Validate, reconcile and investigate sustainability information

Working Draft version 1.1

Purpose and scope

This unit covers the capability to design and perform completeness, accuracy, validity, consistency, reconciliation, variance, reasonableness and exception procedures over sustainability information. It includes expected-population checks, source and system reconciliations, trend and benchmark analysis, outlier investigation, correction, root cause, residual exceptions and evidence of review.

Applied competency statement

Can validate, reconcile and investigate sustainability information using proportionate data-quality, variance, reasonableness and exception procedures and retain a clear correction and review trail.

Boundary and escalation

This unit owns validation, reconciliation and investigation of sustainability data and information. F.2 owns formal reporting control design and operation, I.6 owns AI-output grounding and verification and G.1 performs analysis after data-quality conclusions are reached. The unit does not provide independent assurance, internal audit, system audit or specialist measurement validation.

Key quality risks

Checking only arithmetic accuracy while missing incomplete populations or wrong definitions; reconciling to a source with the same underlying error; unexplained material variances; thresholds that exclude high-risk exceptions; outliers removed without investigation; benchmark comparisons used without context; errors corrected only in the final report but not the source or system; reviewer comments closed without evidence; and unresolved exceptions hidden in an aggregate result.

Required knowledge · 6

E.7-K01

Understands completeness, accuracy, validity, consistency, timeliness, uniqueness, reasonableness, integrity and traceability and how the relevant dimensions vary by metric and source.

Knowledge Type: Data-quality dimensions · Normative Weight: Core

E.7-K02

Understands format, range, type, permissible-value, cross-field, duplicate, population, boundary, unit, formula, factor, cut-off and evidence checks.

Knowledge Type: Validation methods · Normative Weight: Core

E.7-K03

Understands source-to-report, system-to-system, entity-to-group, operational-to-financial, current-to-prior and request-to-submission reconciliation and the need for independent or corroborating evidence.

Knowledge Type: Reconciliation · Normative Weight: Core

E.7-K04

Understands trend, variance, ratio, intensity, benchmark, outlier, distribution and plausibility analysis and their contextual limitations.

Knowledge Type: Analytical review · Normative Weight: Core

E.7-K05

Understands thresholds, risk-based sampling, root cause, correction, override, residual exception, re-performance, review, escalation and closure evidence.

Knowledge Type: Exception investigation · Normative Weight: Core

E.7-K06

Understands validation-plan approval, reviewer competence, documentation, correction at source, issue and deficiency linkage and the distinction from assurance.

Knowledge Type: Governance and boundary · Normative Weight: Core

Applied skills · 5

E.7-S01

Define data-quality assertions, expected populations, validation rules, reconciliation points, thresholds, owners and review evidence.

Skill Type: Core applied capability · Observable Output or Result: Data validation and reconciliation plan

E.7-S02

Perform automated and manual checks for completeness, validity, consistency, duplication, formula, factor, unit, cut-off and evidence.

Skill Type: Validation execution · Observable Output or Result: Validation results

E.7-S03

Reconcile information to suitable sources and systems and perform trend, variance, ratio, benchmark and reasonableness analysis.

Skill Type: Reconciliation and analytics · Observable Output or Result: Reconciliation and analytical review

E.7-S04

Investigate exceptions, determine root cause, correct source and reported information, assess downstream effects and retain closure evidence.

Skill Type: Investigation and correction · Observable Output or Result: Validation, exception and investigation log

E.7-S05

Evaluate residual exceptions and data-quality limitations, obtain review and communicate remediation, disclosure and assurance-readiness implications.

Skill Type: Conclusion and remediation · Observable Output or Result: Data-quality conclusion and remediation record

Professional behaviours · 3

E.7-B01

Does not accept a value as reliable merely because it was system-generated, previously reported or submitted by a senior owner.

Behaviour Type: Professional scepticism · Non-compensable Requirement: No

E.7-B02

Does not close an exception or reviewer comment without evidence that the cause and affected outputs were addressed.

Behaviour Type: Evidence-based closure · Non-compensable Requirement: No

E.7-B03

Uses risk-based thresholds without hiding severe, unusual or high-impact exceptions and keeps residual limitations visible.

Behaviour Type: Proportionality and transparency · Non-compensable Requirement: No

Typical tasks · 4

E.7-T01

Define assertions, populations, rules, thresholds, reconciliations, analytical procedures, owners and evidence for each material metric or dataset.

Primary Output Link: E.7-O01

E.7-T02

Run or perform validation checks and reconcile submissions and calculations to source, system, operational or financial evidence.

Primary Output Link: E.7-O02

E.7-T03

Investigate material variances, outliers, duplicates, gaps and inconsistent values and determine root cause and affected outputs.

Primary Output Link: E.7-O02

E.7-T04

Correct information at the appropriate source, reperform checks, assess residual limitations and obtain review and remediation approval.

Primary Output Link: E.7-O03

Expected outputs · 3

E.7-O01

Data validation and reconciliation plan

Output Type: Professional work product

E.7-O02

Validation, exception and investigation log

Output Type: Professional work product

E.7-O03

Data-quality conclusion and remediation record

Output Type: Professional work product

Proficiency indicators

Level 1 · Foundation

E.7-L1-01

Can perform approved validation and reconciliation procedures, record exceptions and update correction and closure evidence.

Indicator Dimension: Task execution

E.7-L1-02

Can identify obvious unexplained variances, incomplete populations, duplicated or invalid values and escalate material or specialist exceptions.

Indicator Dimension: Quality, judgement and accountability

Level 2 · Practitioner

E.7-L2-01

Can independently design and operate validation, reconciliation and investigation for a moderately complex reporting dataset.

Indicator Dimension: Task execution

E.7-L2-02

Can select proportionate analytical procedures, resolve routine exceptions, assess root cause and explain residual limitations and remediation to owners and reviewers.

Indicator Dimension: Quality, judgement and accountability

Level 3 · Advanced Practitioner

E.7-L3-01

Can design or critically review enterprise data-quality and reconciliation methods across complex groups, systems, metrics and reporting channels.

Indicator Dimension: Method design and review

E.7-L3-02

Can challenge superficial or circular reconciliations, resolve systemic data-quality failures and advise governance bodies on residual risk, disclosure and remediation priorities.

Indicator Dimension: Leadership and governance

Illustrative evidence · 6

E.7-E01

Data validation and reconciliation plan with assertions, rules, thresholds, owners and evidence.

Evidence Type: Work product

E.7-E02

Validation, exception and investigation log with root cause, correction and closure fields.

Evidence Type: Work product

E.7-E03

Data-quality conclusion and remediation record with residual limitations and approval.

Evidence Type: Work product

E.7-E04

Reconciliation, variance, trend, outlier, re-performance and correction trail.

Evidence Type: Process evidence

E.7-E05

Documented source-owner, methodology, finance, IT, quality, internal-control or management review and the practitioner's response.

Evidence Type: Review evidence

E.7-E06

Observed investigation and defence of a material data exception or unexplained variance.

Evidence Type: Observed performance

Assessment · 3

E.7-A-L1

Validation exercise, reconciliation and situational judgement

Correct procedures; exception identification; reconciliation; evidence and escalation awareness.

E.7-A-L2

Integrated data-quality case and professional memorandum

Validation-plan design; reconciliation and analytics; investigation and correction; residual limitations and communication.

E.7-A-L3

Complex systemic-quality case, portfolio and oral defence

Method design; independence of evidence; systemic root cause; challenge and governance communication; oral defence.

Relationships · 13

From	To	Type	Rationale
E.2	E.7	Method, data and analytical linkage	Validation procedures test the implementation and results of the approved methodology.
E.5	E.7	Method, data and analytical linkage	Population, duplicate, unit and reasonableness review validates the consolidated information.
E.6	E.7	Method, data and analytical linkage	Sensitivity, plausibility and back-testing support validation of estimated and modelled information.
E.7	I.6	Boundary distinction	E.7 validates and reconciles sustainability data and calculations; I.6 verifies AI-assisted outputs and should invoke E.7 where AI creates, transforms or analyses reporting data.
E.7	F.2	Risk and control linkage	Validation and reconciliation procedures may operate as formal reporting controls.
E.7	F.3	Evidence and traceability linkage	Data-quality conclusions depend on relevant, reliable and sufficient corroborating evidence.
E.7	F.6	Risk and control linkage	Systemic or unresolved data-quality exceptions may constitute control deficiencies requiring remediation.
E.7	G.1	Method, data and analytical linkage	Validated information provides the basis for trend, variance and performance analysis.
F.2	E.7	Risk and control linkage	Validation and reconciliation procedures may operate as preventive or detective reporting controls.
F.3	E.7	Evidence and traceability linkage	Validation and reconciliation results may provide corroborating reporting evidence.
G.1	E.7	Prerequisite	Performance analysis should use validated, reconciled and investigated sustainability information.
H.2	E.7	Method, data and analytical linkage	Validation and reconciliation exceptions require questioning and evidence-based challenge.
I.6	E.7	Method, data and analytical linkage	AI-generated classifications, calculations and tables may require data validation, reconciliation and reperformance.

Role profiles for this unit

Role	Target level	Relevance	Evidence expectation
Corporate Sustainability Reporting Practitioner	Practitioner	Required?	A case or work sample demonstrating independent performance, documented judgement and a reviewable professional output.
Sustainability Reporting Manager or Lead	Practitioner	Required?	A case or work sample demonstrating independent performance, documented judgement and a reviewable professional output.
Sustainability Reporting Adviser or Consultant	Practitioner	Required?	A case or work sample demonstrating independent performance, documented judgement and a reviewable professional output.
Sustainability Data, Systems and Controls Specialist	Advanced Practitioner	Role-defining?	A complex case or verified portfolio, supplemented by oral or observed defence, demonstrating method design, challenge and governance capability.
Assurance Readiness and Reporting Quality Specialist	Advanced Practitioner	Role-defining?	A complex case or verified portfolio, supplemented by oral or observed defence, demonstrating method design, challenge and governance capability.
Investor, Capital Markets and Ratings Disclosure Specialist	Practitioner	Required?	A case or work sample demonstrating independent performance, documented judgement and a reviewable professional output.