Cognitive Auditing Architecture for Money-Laundering Risk Detection: Evidence from Emerging and Advanced Economies

Purpose and Design This study develops a 5IR-driven Auditing Architecture designed to enhance the detection of money-laundering risks within both emerging and advanced economies. Anchored in risk-governance theory and human–AI collaborative assurance, the architecture introduces an integrated multilayer system that shifts auditing beyond traditional continuous auditing—associated with Industry 3.0—towards adaptive, cognitive, and autonomous assurance consistent with the Fifth Industrial Revolution (5IR). Method and Approach The study employs a comparative applied methodology combining: (1) cross-country benchmarking of AML regulatory and auditing practices. (2) expert evaluations from regulators, auditors, and AML specialists. (3) a prototype cognitive risk-signalling module tested on real-world AML cases from selected markets. A mixed-methods design is used to validate the architecture through predictive accuracy, expert judgement, and analytical modelling. Findings Results show that the proposed cognitive auditing architecture significantly improves the detection of high-risk money-laundering patterns compared to conventional digital or continuous auditing approaches. It enhances the identification of red-flag indicators, strengthens real-time risk scoring, and supports more consistent, explainable, and adaptive auditor decision-making across di-verse regulatory contexts. Originality and Value The study provides the first integrated 5IR-based architecture combining cognitive intelligence, adaptive risk-signalling, and hu-man–AI collaboration for AML auditing. It bridges a major gap in contemporary auditing research, which remains dominated by outdated continuous auditing models. Theoretical, Practical and Social Implications Theoretically, the study advances cognitive assurance theory by proposing a multilayer 5IR auditing architecture. Practically, it provides regulators, auditors, and AML units with an actionable system that improves oversight quality. Socially, the architecture contributes to combating financial crime, enhancing transparency, and strengthening financial stability.