• K.Ramya
• S . Shenija
• Dr.S Sajitha Banu
• M Sabari Ramachandran
• G Balamurugan

With billions of dollars and Rupees worth of assets being laundered every year, the problem of money laundering is growing. In order to detect this illegal activity and prevent it from happening, a network of banks needs to work together. However, most existing approaches have failed to achieve this goal primarily because they do not allow any third-party access to information connecting one bank with another. The paper proposes a novel solution which follows three essential principles: preserving privacy, and enabling ML detection at massive scale. This paper also implements the comparative analysis of the ML Algorithms and depicts the same on graphical illustration with the accuracy level of each of the algorithm in a specialized approach to detect Money Laundering using the Latest ML Applications

Money Laundering Detection, Machine Learning, Malicious Application, Python, Random Forest, Laundering

"Comparative Analysis & Implementation of AI Algorithms for Money Laundering Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 8, page no.e700-e704, August-2022, Available :http://www.jetir.org/papers/JETIR2208484.pdf

"Comparative Analysis & Implementation of AI Algorithms for Money Laundering Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 8, page no. ppe700-e704, August-2022, Available at : http://www.jetir.org/papers/JETIR2208484.pdf