Money Laundering Detection using Synthetic Data
| Document type: | Conference Papers |
|---|---|
| Peer reviewed: | Yes |
| Full text: | |
| Author(s): | Edgar Alonso Lopez-Rojas, Stefan Axelsson |
| Title: | Money Laundering Detection using Synthetic Data |
| Conference name: | Annual workshop of the Swedish Artificial Intelligence Society (SAIS) |
| Year: | 2012 |
| Pagination: | 33-40 |
| Publisher: | Linköping University Electronic Press, Linköpings universitet |
| City: | Örebro, Sweden |
| Other identifiers: | ISSN (print): 1650-3686 |
| Organization: | Blekinge Institute of Technology |
| Department: | School of Computing (Sektionen för datavetenskap och kommunikation) School of Computing S-371 79 Karlskrona +46 455 38 50 00 http://www.bth.se/com |
| Authors e-mail: | edgar.lopez@bth.se, stefan.axelsson@bth.se |
| Language: | English |
| Abstract: | Criminals use money laundering to make the proceeds from their illegal activities look legitimate in the eyes of the rest of society. Current countermeasures taken by financial organizations are based on legal requirements and very basic statistical analysis. Machine Learning offers a number of ways to detect anomalous transactions. These methods can be based on supervised and unsupervised learning algorithms that improve the performance of detection of such criminal activity. In this study we present an analysis of the difficulties and considerations of applying machine learning techniques to this problem. We discuss the pros and cons of using synthetic data and problems and advantages inherent in the generation of such a data set. We do this using a case study and suggest an approach based on Multi-Agent Based Simulations (MABS). |
| Subject: | Computer Science\Artificial Intelligence Computer Science\Electronic security Computer Science\Effects on Society |
| Keywords: | Machine Learning, Anti-Money Laundering, Money Laundering, Anomaly Detection, Synthetic Data, Multi-Agent Based Simulation |
| Note: | Linkoping Press http://www.ep.liu.se/ecp_article/index.en.aspx?issue=071;article=005 |
