Welcome to your interview.
The question is on your right: Evaluate Imbalanced Classification Models. Take a moment with it first.
Talk your thinking through with me if you like - when you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes). Discussion and graded submissions share your five interviewer interactions, so spend them well.
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?