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I am working on a fraud detection algorithm using a banking dataset which has large number of transactions. The number of true fraud cases are very small (<1%). So accuracy is not a good measure as if we say there is no fraud at all, we will still have over 99% accuracy. I learnt that AUC can be a good measure in such cases but I don't understand why. Can someone explain why?