When using computer-assisted audit techniques (CAATs), which attribute of evidence is most affected?

When utilizing computer-assisted audit techniques (CAATs), the attribute of evidence that is most affected is reliability. CAATs are designed to automate and enhance the audit process by analyzing large volumes of data and identifying anomalies or patterns that may indicate issues like fraud or misstatements.

The reliability of evidence refers to the degree to which the information can be depended upon to accurately represent the facts. With CAATs, the methods used for data extraction and analysis often involve automated algorithms and processes that can significantly reduce the risk of human error, thus enhancing the trustworthiness of the audit findings.

Moreover, the reliability of evidence obtained through CAATs can also be bolstered by the ability to re-test or validate findings through multiple iterations or by cross-referencing with different data sources. This quality of CAATs ensures that the findings or evidence presented are robust and can be relied upon for making informed decisions.

While other attributes of evidence such as usefulness, relevance, and adequacy are important, they are less directly influenced by the implementation of CAATs compared to the reliability aspect. Hence, the greatest impact of CAATs is observed in the reliability of the evidence they generate.