As has been pointed out, improving the AUC and incorporating asymmetric costs/benefits are two different things. The AUC has to do with the ability of the model to classify correctly, while the profit matrix steers the classification errors towards where they do the least damage. If the AUC measure is not bad but the classifications are making costly mistakes (like failing to classify any of the 1 values), then you should try a different cutoff probability for the classification - that is what the profit matrix will do automatically, but you can also change the cutoff probabilities by hand to alter the misclassifications. If you still don't like what you can get, then you want a better model - one that will produce a higher AUC. Nothing about the misclassification costs will raise the AUC - only a better model can raise the AUC. So, if you need a better model, then try other techniques, transforming your variables, changing the model settings, etc. but don't use the profit matrix to try to improve the model itself.
