Guidance on data quality and assurance
Тип публикации: 
Guidance note
Published Date: 
July, 2016

Guidance note 24 on data quality and assurance

Relates to requirement 4.9 

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Since the guidance note is quite large (7 MB) we have included a lighter version (1.4 MB) containing less sharp images.


The EITI Standard seeks to ensure a credible EITI reporting process that produces reliable data. While data quality issues are relevant to all aspect of EITI implementation, the EITI Standard puts a particular emphasis on whether the data on company payments and government revenues (within the scope of EITI reporting) are subject to credible, independent audit, applying international auditing standards.

To achieve this, the EITI seeks to build on existing audit and assurance systems in government and industry, and to promote adherence to international practice and standards. In countries with weak audit and assurance systems (in government and/or industry), EITI Reporting can play a key role in identifying these issues, encouraging reforms and monitoring progress.

In countries with strong audit and assurance systems, the EITI Reporting procedures should not duplicate existing internal controls or impose time- consuming reporting requirements. The detailed requirements are set out in Requirement 4.9 and in the standardised Terms of Reference for Independent Administrators.

This guidance note provides guidance on how to improve the quality and reliabililty of information. It incloudes a checklist and several country examples. 


1. Summary

2. Guidance

Step 1 - review audit and assurance practices.
Step 2 – agree on assurances to be provided by reporting entities to the Independent Administrator.
Step 3 – Document the assessment of auditing processes, options considered when developing quality assurance procedures, and the rationale for agreed assurances
Step 4 – Assess compliance with quality assurance procedures and the materiality of any omissions
Step 5 – Validation of data quality and assurance procedures

3. Checklist for data quality and assurance

Review of auditing and assurance systems
Assessment of auditing practices
Quality assurance procedures

Annex: Country examples