Review of artificial intelligence-based applications for money laundering detection
Year: 2025
Type: article
Study design: Systematic Review
Abstract: Since studies of pattern recognition for detecting money laundering have overflowed with various outcomes, effective applications of artificial intelligence (AI) for delivering précised outcomes are still emerging. In this paper, we evaluate AI-based approaches for their performance measure (e.g., accuracy), data requirement, processing speed, and cost-effectiveness in detecting money laundering activities, find related gaps, and suggest possible courses of action. Adopting a smart literature review analysis, including PRISMA and a topic modeling technique, this study examines published peer-reviewed and conference articles from 2015 to June 2023. The study identifies dominant topics in the period, concluding that AI-based solutions have increasingly been deployed in detecting money laundering, though they face various challenges in application. It also emphasizes that AI solutions are required to be evaluated to measure their performance before applying to large-scale problem-solving.
Authors: Seyedmohammad Mousavian, Shah J Miah
Institution: University of Newcastle Australia
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,790
OpenAlex ID: W4413289626