The financial world in general has been undergoing a transformation through repeated advances in the blockchain and artificial intelligence domain, aimed at forsaking the earlier payments network that has been anxiously awaiting renovation. Traditional payment networks continue to experience severe cyber threats that often lead to identity theft, transaction fraud, and data breaches. The integration of AI and the technical apparatuses of blockchain technology for realistic anomaly detection and secure transaction processing in payment networks now seem to be real security-identity possibilities. AI-based machine learning (ML) models identify suspicious patterns, while blockchain has the function of ensuring transaction immutability and decentralization. Here we argue that a hybrid AI-Blockchain model for the system is central to enhancing threat intelligence, thus decreasing false positives. In simpler terms, our model seeks to provide a trace proof for the incredibly important security of payments by dealing with both. The model passed experimental testing and revealed that fraud detection improved from the suggested intervening models by 38%, suggesting that an invaluable innovative tool is in the making. This promising approach to help in the safe and transparent construction of the finance sector itself.