Sarcouncil Journal of Economics and Business Management

Abstract: Financial due diligence (FDD) plays a crucial role in corporate finance and mergers and acquisitions, because it is traditionally hampered by inefficiencies, human mistakes, and fractured verification mechanisms. The review examines how Artificial Intelligence (AI) can be used in combination with blockchain to increase automation, transparency, and accountability in financial investigations. Its main task is to examine how predictive analytics, anomaly detection, and immutability options of AI can reduce the level of human bias, speed up decision-making, and enhance compliance assurance. Using two prominent case studies of JPMorgan Chase and Wells Fargo, the study compares successful and unsuccessful integrations to determine what makes integrations effective. JPMorgan Liink platform showed considerable improvements in efficiency such as cross-border payment latency went down by 70% whereas the project at Wells Fargo was terminated because it failed in its governance and interoperability. Results indicate that AI-blockchain implementation boosts the integrity of financial data, automates risk assessment, and is helpful in creating auditability in real-time. But still, scalability, explainability, regulatory harmonization, and privacy concerns remain limited. The research concludes that long-term implementation needs permission blockchain systems, explainable AI, strong rules of governance, and convergence of regulation. Financial due diligence can be a proactive, resilient, and data-driven compliance system implemented in the future through transparency and ethical oversight and a federated learning process.