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Title: Machine learning for money laundering detection
Authors: Huang, Peng
Keywords: Engineering::Computer science and engineering
Issue Date: 2020
Publisher: Nanyang Technological University
Project: SCSE19-0569
Abstract: Money laundering nowadays has become more severe and gained attention from regulations all over the world. With the development of technology, machine learning and data mining techniques have been adopted in the anti-money laundering system. However, banks face difficulties when investigating cross-bank transactions due to the restrictions in information sharing between them. This project first studies the typologies of money laundering activities based on international organizations’ information and constructs indicators to quantify red flags for potential money laundering activities. From that, we propose an anti-money laundering framework comprising of single-bank and multi-bank systems by using machine learning, homomorphic encryption, and secure multi-party computation techniques. Future work can be done for the real-world implementation of such a framework.
Schools: School of Computer Science and Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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