Multi-Agent Based Anti-Money Laundering System

Abstract

Most countries have legal frameworks that require financial institutions to monitor transaction activities by their customers with the objective of identifying suspicious money laundering activities. Such frameworks further require that once suspicious money laundering activities are identified, they are reported to a regulator. In Kenya for instance, financial institutions are required to report all suspicious activities to the Financial Reporting Centre (FRC). The FRC is a financial intelligence unit whose main mandate is to investigate money laundering cases in Kenya. Most financial institutions in the world exist in a regulatory environment that makes it a legal requirement for them to put in place systems detect and report suspicious money laundering activities. This project researches on a Multi-Agent Based Anti-Money Laundering System for use in a typical financial institution. The system is comprised of a group of software agents that work together to prevent and detect money laundering. It also provides a framework for reporting suspicious money laundering activities within a financial institution. Among the software agents are be the data collecting agents which gather internal and external data. The system also comprises of analysing agents which use data collected by the .data collecting agents to intelligently detect suspicio~s money laundering activities