The role of training data in this context is to provide the algorithm with a large set of unlabeled transactions containing only features such as sender and receiver addresses, transaction amounts ...

GANs create data by using one algorithm to generate data patterns and a second algorithm to test them. Then they form an adversarial competition between the two to find optimal patterns.

For this, the data must first be divided into a larger training set and a smaller test set—the former is used for the model to learn, and the latter is used to check its reliability.