Ethical implications in money laundering detection: balancing privacy and accountability

Abstract

The obligation of businesses to submit suspicious transaction reports (STRs) in anti-money laundering efforts is a critical component of regulatory frameworks worldwide. Businesses increasingly look to technology, including artificial intelligence (AI) tools, to satisfy these obligations. While STRs remain a key component of compliance, they raise complex ethical issues involving client privacy and human rights. Employing AI technology in transaction monitoring and reporting processes exacerbates these issues. This chapter explores ethical dilemmas surrounding STR compliance, including the tensions inherent in balancing regulatory imperatives with individual rights. The role of AI in enhancing the efficiency and effectiveness of suspicious transaction monitoring is considered, alongside the ethical risks associated with algorithmic bias, lack of interpretability, and the potential erosion of human oversight. By synthesizing insights from theory and research, this chapter offers a comprehensive framework for navigating the ethical complexities of STR compliance.