A computer system for detecting banking frauds in historical data and future transactions from a user supplied specimen set of fraudulent transactions can include: a user console that receives a type of fraud and a plurality of known fraudulent banking transactions associated with the type of fraud from the user; a first set of clue detectors operating on the plurality of known fraudulent banking transactions from the user; a clue detector archive that stores a second set of clue detectors, wherein each of the stored second set of clue detectors has a score that exceeds a threshold value for each clue detector; and a backpropagation neural network that calculates a weight for the stored second set of clue detectors using a learning scheme, wherein a fraud scenario is created based on the stored second set of clue detectors and corresponding weights.