Technology used for real-time fraud detection in banking involves sophisticated machine learning algorithms and AI analytics that continuously monitor transactions for suspicious activity. These systems analyze large datasets to identify patterns indicative of fraudulent behavior. By leveraging predictive analytics, banks can respond quickly to anomalies, minimizing losses and improving customer security. This proactive approach helps maintain trust and protects both the institution and its customers from financial losses.