Your question is Evaluate Imbalanced Classification Models. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You are evaluating a classification model for a finance use case where the positive class is rare. Accuracy looks high, but the team is not confident it reflects real performance on the minority class. The business wants to know which metrics matter most and how to judge whether the current threshold is appropriate.
How would you evaluate a classification model on an imbalanced dataset common in finance?