What outcome is often pursued through the use of data analytics in auditing?

The pursuit of increased operational efficiency through data analytics in auditing is grounded in the ability of technology and analytical tools to streamline processes, identify trends, and uncover insights from large volumes of data. By leveraging data analytics, auditors can quickly analyze transactions and operations, enabling them to identify anomalies and areas of concern more efficiently than manual methods would allow. This leads to saving time and resources, ultimately enhancing the effectiveness of the audit process.

Furthermore, data analytics facilitates a more in-depth examination of business operations and risks. This level of analysis often leads to the implementation of recommendations that improve processes and controls, thereby increasing overall effectiveness. In contrast, the other options do not align with the typical objectives of using data analytics in auditing. The elimination of all risks is unrealistic, as some level of risk will always remain in any business environment. Repetition of manual processes contradicts the goal of enhancing efficiency, and reduction of employee interactions is not a primary purpose of data analytics, which often aims to support and improve decision-making rather than replace human interaction entirely.