Comparing Data Mining Techniques for Anti-Money Laundering

Abstract

Money laundering is a method used by criminals to give lawful appearance to funds obtained illegally. Due to the difficulty of identification using traditional methods of research, technology has played an important role in this process. The knowledge discovery techniques were used in an experimental research with the objective of verifying their effectiveness and accuracy in the identification of relationships in banking transactions from real money laundering investigations. The graph matching techniques obtained the best results but it was found that, despite the low efficiency, frequent pattern mining techniques are important and should not be avoided.