Version 1
: Received: 19 January 2018 / Approved: 22 January 2018 / Online: 22 January 2018 (04:46:20 CET)
How to cite:
Alexandre, C.; Balsa, J. A Multi-Agent System Based Approach to Fight Financial Fraud: An Application to Money Laundering. Preprints2018, 2018010193. https://doi.org/10.20944/preprints201801.0193.v1
Alexandre, C.; Balsa, J. A Multi-Agent System Based Approach to Fight Financial Fraud: An Application to Money Laundering. Preprints 2018, 2018010193. https://doi.org/10.20944/preprints201801.0193.v1
Alexandre, C.; Balsa, J. A Multi-Agent System Based Approach to Fight Financial Fraud: An Application to Money Laundering. Preprints2018, 2018010193. https://doi.org/10.20944/preprints201801.0193.v1
APA Style
Alexandre, C., & Balsa, J. (2018). A Multi-Agent System Based Approach to Fight Financial Fraud: An Application to Money Laundering. Preprints. https://doi.org/10.20944/preprints201801.0193.v1
Chicago/Turabian Style
Alexandre, C. and João Balsa. 2018 "A Multi-Agent System Based Approach to Fight Financial Fraud: An Application to Money Laundering" Preprints. https://doi.org/10.20944/preprints201801.0193.v1
Abstract
The anti-money laundering (AML) process has failed both in identifying suspicious cases in due time as in assisting the AML analysts in decision making. Starting from a new generic anti-fraud approach, this article presents the main aspects related to the development of a multi-agent system that goes beyond the capture of suspicious transactions, seeking to assist the human expert in the analysis of suspicious behaviour. First, a transactional behavioural profile of clients is obtained in a data mining process. A set of rules, obtained through data mining over a real database, in conjunction with specific rules based on legal aspects and in the expertise of the AML analysts make up the agents' knowledge base. The cases for which the system was unable to suggest a decision are flagged as requiring more detailed analysis. The system analysed 6 months of real transactions and indicated several suspicious profiles, a set of these suspects was investigated by the AML analysts who proved the suspicion of several cases, including some that had not been identified by the systems in execution.
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
