Optimizing Fraud Detection in Financial Services with Graph Neural Networks and NVIDIA GPUs

Originally published at: https://developer.nvidia.com/blog/optimizing-fraud-detection-in-financial-services-with-graph-neural-networks-and-nvidia-gpus/

Learn an end-to-end workflow showcasing best practices for detecting financial services fraud using GNNs and GPUs.

What batch sizes were used while scaling from 1 to 8 GPUs on the MAG240M dataset?

We used batch size of 8192 and this batch size gave us the best classification accuracy. We see similar speedups with lower batch sizes as well.

Can you share the full end-to-end code for fraud detection (including R-GCN building, training and downstream XGBoost applying)?