A bank's binary classifier flags card transactions as fraudulent so analysts can review them. A missed fraudulent transaction costs the bank far more than an analyst spending a few minutes on a legitimate one. The team wants the evaluation metric that best shows how many of the actual fraud cases the model catches. Which metric should they prioritize?