Abstract
In this project we going to cover best practices of the anti-money laundering techniques and methods, such a customer segmentation based on suspicious behaviour and fraud detection machine learning algorithms. The goal of the project is to define what payment instrument used for the money laundering the most, so financial institution can reinforce their fraud detection process for this specific payment method and work closely with the bank provider. We going to implement and compare different machine learning classification and clustering algorithms and find out what method is more accurate and suits better for crime detection problem on the specific financial instrument.
