Fraud risk propagation in large scale network
You could try applying a graph convolutional network to do some semi-supervised learning. See Kipf and Welling's paper "Semi-Supervised Classification with Graph Convolutional Networks". It probably depends on how unbalanced your dataset is though. If the dataset is too large, you could train a sample of it, and train the GCN on that subset. I'd try to find some exemplar data points and create a train set from that.