Agent-oriented ontology for monitoring and detecting money laundering process

Criminal elements in today's technology-driven society are using every means available at their disposal to launder the proceeds from their illegal activities. To effectively and efficiently prevent and detect such diverse and complex activity, an Anti-Money Laundering (AML) solution should establish comprehensive, solid and fundamental knowledge framework of the monitoring and detecting process. This paper proposed an agent-oriented ontology for monitoring and detecting money laundering process (MDMLP). It provides explicit formal presentation of fundamental components of certain knowledge and relationships among them. Agent-oriented methodology is applied to deal with the dynamic, complex, and distributed MDMLP.