Real-time fraud detection in banking is primarily enabled by machine learning algorithms. These technologies analyze transaction patterns and detect anomalies, allowing banks to respond quickly to potential fraudulent activities. By continuously learning from new data, these systems can adapt to emerging threats and improve their accuracy over time, enhancing the security of financial transactions.