Crossref DOI: 10.31695/IJERAT
ISSN: 2454-6135
Email: editorijerat@gmail.com

International Journal of Engineering Research and Advanced Technology (IJERAT)

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Article: AI-based Models for Money Laundering Detection

Article Category: Computer Science & Engineering

DOI: 10.31695/IJERAT.2018.3355

Pages: 19-23

Author: Sathyanarayanan PSV,Yamunaa Balasubramaniam

Abstract: Fighting Money Laundering represents a noteworthy test for the monetary administrations industry and past. The United Nations Office on Drugs and Crime gauges that the yearly expense of tax evasion and related violations runs somewhere in the range of US$1.4 trillion to $3.5 trillion a year. Every day hostile to Anti Money laundering (AML) experts confront progressively complex dangers and are entrusted with breaking down a developing volume of information. However even as they endeavour to counter continuous dangers, they are overpowered with the large amounts of manual, monotonous, information serious errands that are wasteful and regularly neglect to upset criminal action. Positively AI can possibly empower a stage change in AML ability and give a way proportional and adjust to the cutting edge danger of tax evasion. However, in the meantime, numerous in the business are incredulous about the viability of AI arrangements and the degree to which AI could and ought to be confided in like human capacities. To completely investigate and understand the capability of AI, the money related administrations industry needs to all the more likely comprehend its capacities, dangers and confinements, and build up a moral structure through which the advancement and utilization of AI can be represented so these developing models can be demonstrated and at last trusted.




Keyword: Money Laundering, Artificial Intelligence, Predictive Analytics, Anomaly Detection.

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