Scalable Graph Learning for Anti-Money Laundering: A First Look

Scalable Graph Learning for Anti-Money Laundering: A First Look

30 November 2018

Mark Weber

Jie Chen

Toyotaro Suzumura

C. E. Leiserson

Papers citing "Scalable Graph Learning for Anti-Money Laundering: A First Look"

9 / 9 papers shown

Title
2SFGL: A Simple And Robust Protocol For Graph-Based Fraud Detection Zhirui Pan Guangzhong Wang Zhaoning Li Lifeng Chen Yang Bian Zhongyuan Lai FedML 27 2 0 12 Oct 2023
The GANfather: Controllable generation of malicious activity to improve defence systems Ricardo Pereira Jacopo Bono João Tiago Ascensão David Oliveira Aparício Pedro Ribeiro P. Bizarro AAML 21 2 0 25 Jul 2023
Catch Me If You Can: Semi-supervised Graph Learning for Spotting Money Laundering Md. Rezaul Karim Felix Hermsen S. Chala Paola de Perthuis Avikarsha Mandal 19 4 0 23 Feb 2023
Machine Learning in Transaction Monitoring: The Prospect of xAI Julie Gerlings Ioanna D. Constantiou 17 2 0 14 Oct 2022
Detecting Anomalous Cryptocurrency Transactions: an AML/CFT Application of Machine Learning-based Forensics Nadia Pocher Mirko Zichichi Fabio Merizzi Muhammad Shafiq S. Ferretti 21 32 0 07 Jun 2022
Fighting Money Laundering with Statistics and Machine Learning R. Jensen Alexandros Iosifidis 28 13 0 11 Jan 2022
Graph Computing for Financial Crime and Fraud Detection: Trends, Challenges and Outlook Eren Kurshan Hongda Shen GNN 21 32 0 02 Mar 2021
Financial Crime & Fraud Detection Using Graph Computing: Application Considerations & Outlook Eren Kurshan Honda Shen Haojie Yu GNN FaML 32 26 0 02 Mar 2021
Towards Federated Graph Learning for Collaborative Financial Crimes Detection Toyotaro Suzumura Yi Zhou Natahalie Barcardo Guangann Ye Keith Houck ... Yuji Watanabe Pablo S. Loyola Daniel Klyashtorny Heiko Ludwig Kumar Bhaskaran FedML 25 70 0 19 Sep 2019