A Multi-Agent System Based Approach to Fight Financial Fraud: An Application to Money Laundering

A Multi-Agent System Based Approach to Fight Financial Fraud: An Application to Money Laundering Claudio Alexandre 1,∗ ID and João Balsa 1 1 Faculdade de Ciências da Universidade de Lisboa (BioISI-MAS), Campo Grande, 1749-016, Lisboa, Portugal * Author to whom correspondence should be addressed. Academic Editor: name Version December 19, 2017 submitted to Appl. Sci. Abstract: The anti-money laundering (AML) process has failed both in identifying suspicious cases in 1 due time as in assisting the AML analysts in decision making. Starting from a new generic anti-fraud 2 approach, this article presents the main aspects related to the development of a multi-agent system 3 that goes beyond the capture of suspicious transactions, seeking to assist the human expert in the 4 analysis of suspicious behaviour. First, a transactional behavioural profile of clients is obtained 5 in a data mining process. A set of rules, obtained through data mining over a real database, in 6 conjunction with specific rules based on legal aspects and in the expertise of the AML analysts make 7 up the agents’ knowledge base. The cases for which the system was unable to suggest a decision are 8 flagged as requiring more detailed analysis. The system analysed 6 months of real transactions and 9 indicated several suspicious profiles, a set of these suspects was investigated by the AML analysts 10 who proved the suspicion of several cases, including some that had not been identified by the systems 11 in execution. 12