Interpretation of ROC AUC score
Did you evaluate the results in the training set? Or in the test set?

Those results are outstandingly good! Suspiciously good.

I think you tried your results in the training set only, so your results reflect overfitting on your data, which means your model learned the set, it was not generalized (which means it is unapplicable to any other dataset you may encounter in the future, which is not useful).

For comparing ROC between methodologies you should model them being careful for overfitting and try them on a test dataset (a dataset which you never knew before, which can be obtained partitioning your dataset).

In that way your comparison is not measuring which model learns by memory your data.