Careem developed a machine learning model to intelligently apply temporary holds on transactions that are likely to be fraudulent. Instead of using fixed rules that can frustrate legitimate users, the model classifies transactions based on behavioral and contextual signals to decide when a hold is warranted. This reduces the number of false positives, improves fraud detection, and preserves a smooth experience for the majority of users. The system continuously learns and updates based on new fraud patterns and customer behavior.