Which of the following is a key component of data analytics in internal auditing?

Trend analysis is a key component of data analytics in internal auditing because it allows auditors to identify patterns and changes in data over time. By analyzing trends, auditors can detect anomalies, assess the effectiveness of internal controls, and provide insights about potential risks or opportunities for improvement. This technique helps in understanding how certain variables behave across different time periods, which is critical for assessing the impact of past events and predicting future outcomes.

In contrast, static reports do not provide insights into changes over time, which limits their analytical value. Infrequency of data review hinders the ability to identify trends, undermining the effectiveness of the audit process. Manual calculations can be prone to errors and inefficiencies, especially when handling large datasets, making automated data analytics methods far superior in delivering accurate and timely insights. Thus, trend analysis encapsulates the dynamic and proactive approach necessary for effective internal auditing in today's data-driven environment.