💡 A. Analysis of the full population of existing data is the best technique to identify very small control and transaction anomalies. Traditional sampling methods may miss rare or subtle anomalies, but analyzing the entire dataset allows auditors to detect even minor irregularities that could be exploited for material breaches. Techniques such as data analytics, machine learning, and anomaly detection can be used for this purpose. B. Verification of the completeness and integrity of existing data is important for ensuring that data is reliable, but it does not necessarily help in identifying small anomalies. It focuses more on data accuracy rather than detecting unusual transactions or control weaknesses. C. Continuous monitoring on a repetitive basis is useful for ongoing risk management, but it may not be the best approach for detecting small anomalies in historical data. It is more effective for identifying trends or ongoing issues rather than deep analysis of past transactions. D. Analysis of the databases of partners, such as suppliers may help in detecting fraud or compliance risks related to external entities, but it does not directly increase the likelihood of detecting small internal control and transaction anomalies.