It's easy for ML to pick up on proxies that are related to race even if you exclude what the race is explicitly - zip code and names are two common ones, but this can appear in a lot of different ways.

It's particularly insidious too since a model that accidentally is making credit decisions based on race helps to perpetuate the inequity in the future data.