Detection of Money Laundering using DataMining Techniques

Authors : Leela C P; Dr Pushpa Ravikumar; Bhavana D E; Keerthishree

Volume/Issue : Volume 8 - 2023, Issue 8 - August

Google Scholar :

Scribd :


The illegal act of hiding the source of money obtained illegally through a complex web of financial transfers or commercial transactions is known as money laundering. All things considered, this process implies and indirectly gives the money launderer back the "clean" money. Money laundering is the process of changing the hue of money. It is also a virus that affects the finance sector. The three steps are integration, layering, and placement. There are several methods used globally to identify money laundering at various phases. This is our new approach, which is more accurate and starts with deep learning. Here, we have some algorithms Randoms Forest, Decision Tree and also ANN techniques to detect fraud by implementing in a code. We can detect money laundering is occurred or not if yes it will show the alert message. Numerous financial institutions and industries profit from this, particularly banks.

Keywords : Money Laundering, Decision Tree(DT), Random Forest(RF), Artificial Neural Network(ANN).


Paper Submission Last Date
31 - December - 2023

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.