Which of the following should be an IS auditor ' s GREATEST concern if class...

Class imbalance occurs when one or more classes are underrepresented in the training data. The GREATEST concern is model bias (C): the model may learn to favor the majority class, leading to poor performance and unfair treatment for minority classes. In high-stakes applications (e.g., fraud detection, credit scoring, medical diagnosis), this can translate into systematic discrimination or incorrect decisions . AAIA highlights class imbalance as a common source of bias and stresses mitigation techniques (resampling, reweighting, threshold adjustments).

Data drift (A) refers to changes in data distributions over time—related but distinct. Data quality (B) is broader and may or may not be affected by imbalance. Overfitting (D) is a risk, but class imbalance more directly raises fairness and representativeness concerns rather than overfitting alone. Thus, bias arising from class imbalance is the auditor’s primary concern.