People with higher incomes probably buy more expensive phones. You already have their income on a loan application, so you don't need a blackbox NN model to confirm it.
Throwing in a bunch of corrolated features into a model won't help improve accuracy.
But if you throw in a bunch of weak features that together sum to a predictor of race (or other protected attributes), then aside from being grossly unethical, may well be illegal.
Contextually there is no reason to suspect that a phone operating system has anything to do with anyone's ability to repay a loan, anymore than the color of their car or their eye color.
Income and existing debt does, obviously.
What you don't want, and what is not legal, is denying a loan because of nonsense predictors that happen to be very strongly corrolated to race and very weakly corrolated to the ability to repay a loan.
If color of car, or operating system, is a strong predictor then the model is probably being overtrained on the training data and probably wouldn't generalise well in the real world.
1) Will it continue to be legal?
2) Do I care about ethical concerns and does something being legal make it ethical?
Other people who are in a different position from you will be exploring this to determine if #1 should be changed.