… credit card transactions which define an implicit bipartite graph … We demonstrate that
embedding these transactions can lead … application of graph-embeddings to financial transactions. …

… In this paper, we propose a dynamic embedding method, DynGraphTrans, which … from
financial transaction graph. Dynamic graphs can be generated for every account in a transaction …

… network graph data, an improved node feature embedding method is used … financial
transaction network risk prediction model. Experimental results show that the loss value of the graph …

… Therefore, we set our goal to design a graph-level embedding method which can …
embedding and graph-level anomaly detection steps in turn. Role-guided subgraph embedding …

… Additionally, KGs facilitate automated risk assessment by linking financial transactions,
com… For instance, by using knowledge graph embeddings, financial institutions can identify …

… DeepTrax was used to compute embeddings for merchants on a credit card (point of sale)
transaction … with complex non-bipartite financial transaction networks containing multiple node …

… DeepTrax was used to compute embeddings for merchants on a credit card (point of sale)
transaction … interactions between the accounts on the bank's transaction data, we defined the …

… financial transactions using graph and sequence-based topologies. Our results show that
these embeddings … We deploy DeepGRASS in PayPal, and train it on multitude of transaction …

… The first introduced a financial transaction embedding framework known as DeepTrax using
… will apply it to the inferred embeddings of transaction graphs from subsequent weeks. Fig. 2 …

… In our case, the considered network of bank transactions does not have an explicit … outputs
embedded transactions and use them as node feature vectors \(X\) in all the considered graph …