no code implementations • 5 Jul 2022 • Susie Xi Rao, Piriyakorn Piriyatamwong, Parijat Ghoshal, Sara Nasirian, Emmanuel de Salis, Sandra Mitrović, Michael Wechner, Vanya Brucker, Peter Egger, Ce Zhang
The scientific publication output grows exponentially.
Apart from rule-based and machine learning filters that are already deployed in production, we want to enable efficient real-time inference with graph neural networks (GNNs), which is useful to catch multihop risk propagation in a transaction graph.
At online retail platforms, detecting fraudulent accounts and transactions is crucial to improve customer experience, minimize loss, and avoid unauthorized transactions.
Massive account registration has raised concerns on risk management in e-commerce companies, especially when registration increases rapidly within a short time frame.
At online retail platforms, it is crucial to actively detect the risks of transactions to improve customer experience and minimize financial loss.