C- Means Clustering for Anti Money Laundering using Client Profiling

Nowadays, with the developing of information technology in the world banking system, money laundering in this industry is expanding and Money laundering imposes large costs to banks. So detection of money laundering is one of the important issues facing banks. Systems that detect money laundering is Anti-money laundering system. The purpose of this paper is to design a detection system for money laundering using customer profiles for Iran. For this reason, using Clients profiles from one of private banks and Fuzzy C- Means inference system, we propose Anti Money Laundering System. Then using Sugeno Type Fuzzy inference system, Test data to validate the model. Results shows trnRMSE is 0.01699 and ChkRMSE is 0.01699. So the model performs well on checking data

Keywords:

Data mining , Anti Money Laundering , Clustering , Fuzzy techniques