Artificial Intelligence (AI): From the Internal Audit perspective

AI are tools, just like spreadsheets and pivot tables, and useful only when we understand how to use them to improve business processes. AI tools can only function properly when they are analyzing good data and evaluating it against valid criteria, hence fear that AI will replace Internal Audit is unfounded.

Through use of AI internal auditors will have the ability to work with large quantities of unstructured data, classify documents and content, and identify and extract relevant data points, a critical advancement over traditional methodologies in which data fields had to be clearly defined and automated processing was limited to only the most structured and trusted data sets

But for AI to complement internal audit, auditors will be required to apply their creativity and broad domain knowledge to evaluate risks while using AI tools to help them identify patterns and trends from large data sets (that might otherwise be hard or overly time-consuming to identify) and provide insight to support risk assessment, project scoping, sub-population identification, issue identification, quantification, and more.

Although most auditors are afraid that achieving this outcome requires a deep level of technical capability in IT the fact is that with limited technical skills Internal audit teams can apply limited configuration, algorithms such as k-means clustering, decision tree-based models and affinity analysis to identify items within a population that have a statistically meaningful similarity between them and, conversely, identify anomalies, or outliers, that don’t follow the rules and therefore warrant closer study.

Impact of AI in internal audit

Because of the data, budget and time requirements, the organizations that could most benefit from using AI in internal audit are the ones who already have a strong data analytics component to their audit function. Without data analytics as a foundation, you cannot build AI into internal audit notwithstanding the internal audit functions can benefit in.

1. With AI internal audit will be able to review and analyse large quantities of data that is both (un)structured hence reducing the amount of laborious work.

2. Increased testing coverage i.e. through the use of AI internal auditors are able to review up to 100% of all the transactions in a population

3. Creation of fraud testing environment with the ability to evaluate massive datasets internal audit is able to review all the anomalies noted hence increasing the chances of detecting fraud

4. AI can lead to significant risk and governance insights, and internal auditors can be at the forefront of delivering strategic suggestions to the board.

5. Through AI internal audit will be able to have improved timeliness testing and increased visibility as AI reviews and analyses data on a continuous mode or basis

Like any algorithm- and data-driven process, AI presents internal audit with a clear role in ensuring accuracy and reliability.