The Central Bank of Malaysia highlighted gaps in anti-money laundering (AML) compliance programs and risk management practices in financial institutions, particularly emphasizing the importance of high-quality suspicious transaction reports (STR) in the National Risk Assessment (NRA) 2020. The study examines the factors influencing compliance officers' judgment and decision-making in dealing with money laundering risks. The research adopts a quasi-experimental research design to gain a comprehensive understanding of money laundering risk judgment and decision-making. The findings suggest that the judgment and decision-making of compliance officers are influenced by their technical competency and customer risk profiling effectiveness. The study employs Partial Least Squares of Structural Equation Modelling to analyse data from 124 participants. Importantly, the research confirms that technical competency alone does not directly impact money laundering decision-making without prior assessment and judgement on money laundering risk. However, it does show that technical competency and customer risk profiling significantly influence the decision making with mediating role of assessment and judgements. The study contributes to the existing knowledge in this field by validating the theoretical foundation underlying behavioural judgment and decision-making. Additionally, it introduces the Money Laundering Diagnostic Thinking (MoLDiT) Model, which incorporates assessment – judgment – decision making as money laundering risk information processing. Nevertheless, the research has some limitations, such as the sample population, research techniques, methodology, scope, and theory, which should be addressed in future studies. Overall, this research sheds light on the critical role of compliance officers in the fight against money laundering and provides valuable insights for improving AML measures in the financial sector.