Understanding Data Analytics for Internal Auditors - Global Practice Guide

Understanding Data Analytics for Internal Auditors - Global Practice Guide

Understanding Data Analytics for Internal Auditors - Global Practice Guide  

This Global Practice Guide examines how advanced data analytics is transforming the internal audit profession in response to technological innovation, increasing data availability, and growing business complexity.

The guide highlights the evolving role of internal auditors, who are expected to move beyond traditional assurance activities and provide strategic, data-driven insights. In line with The IIA’s Vision 2035, internal auditors are increasingly leveraging advanced analytics, artificial intelligence (AI), and emerging technologies to identify risks, detect trends, and support informed decision-making.

The document provides an overview of the key concepts underpinning data analytics in internal auditing, including:

• Different types of data analytics and their applications
• Data categories used in audit activities
• Data quality, governance, and extraction considerations.

Its objective is to help internal auditors develop the knowledge and capabilities required to operate effectively in a data-driven environment and enhance the value they deliver to their organizations.