My read on this was that you can just dump the lagged values as inputs and let the network figure it out just as well as the other, time series specific models do, not that time doesn't matter.

I assume the time series modelling is used to predict normal non-fraud behaviour. And then simpler algorithms are able to highlight deviations from the norm?