ABSTRACT
This chapter aims at providing a brief overview of the money laundering, evolution, common tactics processes, and anti-money laundering (AML) models and techniques. In this era of digitally connected world, the nature and quantum of money laundering are changing very rapidly, and the traditional methods of AML are not able to keep pace with the rate of fraud. The study focuses on understanding the rule-based model, the future-based model, data-driven model, and risk-based model which financial institutions have been implementing for AML techniques in India for many years. The chapter also discusses the emerging trends in the AML space by adopting machine learning, data analytics, web and cyber analytics, and behavioral analytics to combat the criminal activities of money laundering. The major objective of the chapter is to identify and propose the best practices in customer risk rating models for Indian financial institutions which help in strengthening their AML efforts.
