The false positive is, out of the ones they found, how many weren't fraud.
So if there are 10 real fraud attempts and they identity 9 of them, but find 90 others as well, then they still have a 90% fraud detection level, but they just hampered 90 customers who did nothing wrong. This would be an extreme case, but it should make the point. This applies in medical science at lot when false positives can mean lots of time and money spent on patients who don't really have the disease that was tested for.