I have a dataset that contains a credit card flag for members(1/0) and certain set of characteristics. I have a final set of 60 variables which I applied in logistic regression and obtained an roc of 0.99. I thought this might be happening as any of the variable might be strongly related to dependent variable, so I started by introducing one by one variable and observed the ROC and it was increasing like 0.51,0.55,0.58,0.61......0.99. About in 8 variables I reached 0.92. I select some random 10 variables and same thing is happening for them as well. This gives the impression that its not the variable information, but just addition that is giving such ROC.
Pop Size: 450,000(98% negative cases and 2% positive cases) Hosmer and Lemeshow goodness of fit test is significant.
Any idea, why I am observing such a result? Please let me know, if you need any additional information.