Regulation 18 — Audit Regulations 2020
Original Rule Text
# 18. IT assisted audits
(1) IT assisted audits involve the use of various IT tools including, but not limited to, traditional data analysis tools [also referred to as Computer Assisted Audit Techniques (CAATs)] and data analytics/ big data analytics for supporting the achievement of the audit objectives. (2) Such analysis or analytics is applied on data provided by the auditable entity, which may be available in a variety of structures and formats, as well as external or third party data. (3) Adequacy and effectiveness of IT and non IT controls for ensuring data integrity and non-repudiability of such data may be duly considered by the audit office, while examining the reliability of such data. (4) The insights which may be drawn from data analysis/ analytics include, but are not limited to, exceptions, trends, patterns, deviations, inconsistencies, and relationships among data elements identified through analysis, modelling or visualization, can be used while planning, conducting and reporting audits.
Regulations on Audit and Accounts 2020
(5) Depending on the gaps in automation, the level of offline documentation, and the adequacy and effectiveness of controls, the reliability of findings through data analysis/ analytics may need to be validated through field examination and verification of a sample of cases.
Regulations on Audit and Accounts 2020
Chapter 4 Right of access to Audit and Responsibilities of the auditable entity
What This Means
Audit teams can use IT tools, data analytics, and big data techniques to support their audit work. This includes analyzing data from the auditable entity — in any format — as well as external or third-party data. Insights such as exceptions, trends, patterns, and inconsistencies discovered through data analysis can be used during planning, conducting, and reporting audits. However, depending on the reliability of the data and adequacy of IT controls, findings from data analytics may need to be validated through physical field examination.
This explanation was generated with AI assistance for educational purposes. Always refer to the official gazette notification for authoritative text.
Key Points
- 1IT-assisted audits use CAATs, data analytics, and big data tools to enhance audit effectiveness
- 2Data can come from the auditable entity or third-party/external sources in any format
- 3Audit offices must assess IT and non-IT controls for data integrity before relying on findings
- 4Insights include exceptions, trends, patterns, deviations, and relationships among data elements
- 5Field verification of a sample may be needed to validate data analytics findings
Practical Example
The AG (Audit) office in Delhi is conducting an IT-assisted audit of the Income Tax Department. The audit team uses data analytics tools to analyze the department's taxpayer database, identifying 2,500 cases where refunds exceeded a threshold without proper approval. Before including these findings in the audit report, the team selects a sample of 100 cases for physical verification at the field offices to confirm the data's reliability.
This explanation was generated with AI assistance for educational purposes. Always refer to the official gazette notification for authoritative text.
Frequently Asked Questions
What are CAATs mentioned in this regulation?▼
Can audit rely solely on data analytics findings without field verification?▼
Is the auditable entity required to provide data in a specific format for IT-assisted audits?▼
This explanation was generated with AI assistance for educational purposes. Always refer to the official gazette notification for authoritative text.