Please explain. If you removed "profiling features" from your analysis, but then through other means ended up with a "similar performant model," then aren't you still profiling, just with less obvious data inputs?

If Group A is low credit risk and Group B is high credit risk, won't your new model still make it much harder for Group B to be approved? If not, it's not "similar." If you are able to dissect the Groups and pull individual high/low risks from within the groups, that would be a superior model, which is not what you claimed. So how are you not profiling, and how does it make a difference in terms of who gets approved/rejected?