Abstract:

Along with the advancement of technology, safeguarding the accuracy, confidentiality, and clarity of Financial records has become more intricate. Frauds, data manipulations on documents, and inefficiencies on transaction processing are some of the issues that traditional record keeping systems face. This research looks into the impacts caused by the modification of Artificial Intelligence (AI) dual-purpose systems with Blockchain in automating the processes of Financial record keeping. While AI augments technology in data analytics, anomaly detection, and real-time decision-making, Blockchain offers a distributed ledger of transactions that is incorruptible and immutable. The union of the two technological processes creates a strong framework to counter automate verification and auditing processes. The technologies also have the ability of proactively flagging fraudulent activities hence, reducing the risk of financial frauds drastically. With the aid of extensive review on existing systems and detailed case study approaches, this paper demonstrates how strategic assumptions powered by AI and Blockchain transparency allow organizations to align laws for automated compliance, improve trust, and increase operational accountability. The union enables changes to be reconciled in real-time, teaches security protocols from transactional behavior patterns, and improves certain measures of the system on an ongoing basis. This research shifts paradigms on financial data management by proposing an advanced enduring model designed to counter strategically any identified limitations and shaped to advance secure financial ecosystems in the anticipated future.