The rapid digitalization of financial systems has led to an exponential rise in electronic transactions—andacorresponding escalation in sophisticated online fraud. Traditional machine-learning models, while effective at identifyinganomalous behavior, suffer from low interpretability, mutable evidence logs, and difficulty in maintaining integrity duringdisputeinvestigations. This paper proposes an AI-led blockchain-based framework designed to achieve high-recall frauddetection,explainable decision reasoning, and tamper-proof evidence management. The architecture integrates a cost-sensitiveensemblemodel for rare-event detection, an explainable AI layer for transparent reasoning, and a permissioned blockchainledgerforimmutable evidence anchoring and dispute-resolution tracking. Performance targets emphasize sub-second real-timeprocessingand verifiable audit trails that meet regulatory expectations for accountability and transparency. The proposed frameworkaimstoadvance payment-integrity assurance by combining the predictive power of artificial intelligence with the trust guaranteesofblockchain technology. Keywords: Artificial Intelligence, Blockchain, Fraud Detection, Explainable AI, Financial Transactions, Payment Integrity,Tamper-Proof Evidence, Real-Time Analytics