That tells you how sensitive the model is along its decision boundary to permutations in the input -- but it isnt a relevant kind of reason why the application was rejected, since this decision boundary wasnt crafted by any person. We're here looking for programs which express prior normative reasoning (eg., "you should get a loan if...") -- whereas this decision boundary expresses no prior normative reason.
It is simply that, eg., "on some historical dataset, this boundary most relibaly predicted default" -- but this confers no normative reason to accept or reject any individual application (cf. the ecological fallacy). And so, in a very literal way, there is no normative reason the operator of this model has in accepting/rejecting any individual application.
It is simply that, eg., "on some historical dataset, this boundary most relibaly predicted default" -- but this confers no normative reason to accept or reject any individual application (cf. the ecological fallacy). And so, in a very literal way, there is no normative reason the operator of this model has in accepting/rejecting any individual application.