Due to spurious correlations, it could still be helpful for the insurance assessor so that they can use bias mitigation techniques. Otherwise, it might learn so

Due to spurious correlations, it could still be helpful for the insurance assessor so that they can use bias mitigation techniques. Otherwise, it might learn something about zip code or something else that leads to a similar outcome as having race as an input variable. Just removing a sensitive variable does not suffice for preventing unwanted bias.