Fraud Detection Algorithm

For a leading digital bank, we developed a highly accurate fraud detection system. The model analyzes millions of transactions daily, identifying suspicious patterns and flagging potential fraud in milliseconds. We used a combination of supervised and unsupervised learning techniques to stay ahead of evolving fraud tactics. The system has significantly reduced false positives while increasing the detection rate of actual fraudulent activity.