Artificial Intelligence
Author: Jian Zhang
Modernize fraud prevention: GraphStorm v0.5 for real-time inference
In this post, we demonstrate how to implement real-time fraud prevention using GraphStorm v0.5’s new capabilities for deploying graph neural network (GNN) models through Amazon SageMaker. We show how to transition from model training to production-ready inference endpoints with minimal operational overhead, enabling sub-second fraud detection on transaction graphs with billions of nodes and edges.
Mitigating risk: AWS backbone network traffic prediction using GraphStorm
In this post, we show how you can use our enterprise graph machine learning (GML) framework GraphStorm to solve prediction challenges on large-scale complex networks inspired by our practices of exploring GML to mitigate the AWS backbone network congestion risk.
Build a GNN-based real-time fraud detection solution using Amazon SageMaker, Amazon Neptune, and the Deep Graph Library
Fraudulent activities severely impact many industries, such as e-commerce, social media, and financial services. Frauds could cause a significant loss for businesses and consumers. American consumers reported losing more than $5.8 billion to frauds in 2021, up more than 70% over 2020. Many techniques have been used to detect fraudsters—rule-based filters, anomaly detection, and machine […]