ISO 21378:2019

Overview

ISO 21378:2019 - Audit data collection defines a common, ERP‑independent approach to identify and extract accounting and audit‑relevant data. The standard provides shared definitions of accounting data elements and specifies the information auditors and IT teams need to extract relevant audit data. It is intended to bridge understanding among auditors, auditees, software developers and IT professionals, and to serve as a foundation for local data extraction across core financial domains such as general ledger, accounts receivable, sales, accounts payable, purchase, inventory, and property, plant and equipment (PPE).

Key topics and technical requirements

• Common data definitions: Standardized accounting data elements to reduce ambiguity when mapping data across different systems.
• Modules, tables and fields: A modular structure (Base, GL, AR, Sales, AP, Purchase, Inventory, PPE) with table and field-level guidance to support extraction and mapping.
• Naming conventions: Prescribed conventions to promote consistency when exporting or transforming accounting data.
• Representation and datatypes: Specification of how data elements should be represented (datatypes and formats) to enable reliable automated processing.
• Base module examples: Includes foundational elements such as BAS_Chart_Of_Accounts, BAS_Business_Segment and BAS_Employee used across modules.
• Module examples: Concrete tables such as GL_Details, AR_Open_Accounts_Receivable, SAL_Invoices_Generated, AP_Open_Accounts_Payable and INV_On_Hand are documented for profiling and extraction.
• Data profiling and questionnaires: Standard profiling reports and questionnaires to assess data availability, quality and extraction feasibility.

Practical applications and who uses it

ISO 21378 is used to:

• Standardize audit data collection and streamline audit data extraction across heterogeneous ERP and accounting systems.
• Support audit automation, data analytics, continuous auditing and evidence gathering by ensuring extracted datasets are consistent and well‑documented.
• Guide software developers and IT teams when building extraction scripts, connectors or ETL processes that feed audit tools.
• Help external and internal auditors, compliance officers and audit managers define data requirements and reduce time spent reconciling dataset differences.

Practical benefits include faster audit preparation, clearer data mapping between systems, improved repeatability of audit tests, and better support for analytics-driven audit procedures.

Related standards (if applicable)

ISO 21378 complements organizational data governance and accounting system documentation practices and is intended to work alongside internal IT controls and data protection requirements. It supports interoperability when extracting accounting data from various ERP platforms without prescribing specific system implementations.