Here is a paper reviewing fraud detection methods. Fraud is a rare event, and there is low signal to noise (since fraudsters try to fly under the radar). Companies are trying to manage the risk of fraud, which implies risk analysis, which implies risk prediction. And yet none of the methods used to evaluate the modeling methods surveyed involve risk calibration. You think poorly-implemented machine learning is wasting resources in health care? You’re right. Think of how many billions must be wasted in tech and finance on bogus fraud detection models. It sickens me. Thanks to Pierre Allain for sharing the article https://www.researchgate.net/profile/Nick_Ryman-Tubb/publication/328665645_How_Artificial_Intelligence_and_machine_learning_research_impacts_payment_card_fraud_detection_A_survey_and_industry_benchmark/links/5d80effda6fdcc12cb96f205/How-Artificial-Intelligence-and-machine-learning-research-impacts-payment-card-fraud-detection-A-survey-and-industry-benchmark.pdf