BLOCKCHAIN-BASED FRAUD PREVENTION IN THE U.S. FINANCIAL SECTOR: A LITERATURE REVIEW

Every year, financial institutions lose billions of dollars and public trust undermined since fraud remains a continuous challenge in the U.S. financial industry. Conventional mechanisms of fraud prevention such as compliance checks, manual audits, and transaction monitoring, have proven effective but insufficient due to their inefficiencies, delayed detection, and susceptibility to vulnerability. There is now a transformative approach to mitigating fraud incidences due to blockchain technology through its features of immutability, consensus-driven validation, transparency, and programmability via smart contracts. This paper reviews the application of blockchain in fraud prevention across banking, insurance, payments, and securities sectors, highlighting case studies of JPMorgan Chase, AIG, Visa, Mastercard, MetLife, NASDAQ, and others. It also examines regulatory and policy developments by agencies such as the Treasury, OFAC, FinCEN, and state-level regulators. Some of the key opportunities associated with blockchain are Know Your Customer (KYC) and Know Your Business (KYB) compliance, provenance verification, tokenized asset ecosystems, and automated fraud controls. There remain significant challenges in scalability, governance ambiguity, uncertainty to regulations, privacy conflicts with data protection laws, and smart contract vulnerabilities. The review concludes that blockchain provides robust tools for fraud detection and prevention but is not a panacea. Future research should explore the integration of blockchain with artificial intelligence (AI) and machine learning (ML), fraud detection models through privacy-preserving, regulatory harmonization, and cost–benefit analyses. By addressing these gaps, blockchain can evolve into a cornerstone of fraud prevention strategies within the U.S. financial sector.
Keywords: Blockchain Technology, Fraud Prevention, Financial Institutions, Machine Learning, Artificial Intelligence