I have a highly imbalance churn dataset i.e 99.5% to .5 % bias. I got an AUC of around 88% with 3 independent variables.The problem is that the probabilities are clustered around .004 to .005. Can I ignore this and order probabilities in descending order and take top N values as people most likely to churn and present it to the business or do i need to do any other validation? It is a boosting model. Logistic regression has also got the same issue but AUC is around 78% with just one independent variable. I do not want to do under or oversampling.