The FinTech-AI Nexus: A Paradigm Shift in Anti-Money Laundering Surveillance and Enforcement

This study examines how the convergence of FinTech capabilities and AI-driven solutions is reshaping Anti-Money Laundering (AML) surveillance and enforcement. Drawing on the Resource-Based View (RBV) and Institutional Theory (IT), it develops a framework to evaluate the role of technological capabilities and institutional pressures (NP) in strengthening AML outcomes. A theoretical model was constructed, and primary data will be collected from AML professionals, FinTech experts, and compliance officers in the banking and financial services. SmartPLS 4 will be applied to test the hypotheses and validate the conceptual model. The study is expected to demonstrate that FinTech and AI capabilities significantly improve AML surveillance efficiency, which in turn enhances enforcement outcomes. Regulatory support is expected to strengthen the link between surveillance and enforcement, while normative pressures may further drive the adoption of technology. The study contributes to digital financial governance by identifying the key enablers and constraints in technology-driven AML practices. The findings provide actionable insights for regulators, financial institutions, and technology developers, emphasizing that while advanced technologies are crucial, effective regulatory support remains essential for maximizing enforcement success and safeguarding financial integrity in the digital age.