I understand what they're implying by "adjusted accuracy". My point is that I'm not sure that metric really makes sense, because "accuracy" isn't a particularly useful metric to begin with. It depends entirely on the sample distribution. "Always guess not fraud" will be 99.9% "accurate" for most use cases.

I'm asking what the literal metric is.

edit: and I don't think your explanation really works for accuracy, because accuracy isn't a relative measure, like, say, R2.