I suggest that it's not a big deal, because loan purposes that are statistically significantly related to default are absolutely included in the model. Admittedly, certain categories under- and over-perform. However, if many other characteristics about the loan suggests repayment, then sometimes even a small business loan can meet the expected return criteria (it's definitely more rare than just picking randomly off the platform).
This is an example of a fundamental difference between a multi-dimensional, simultaneously estimated model and a filter. In a filter, it's unilateral. The other (my) kind of of model allows us to use shades of gray. For example, if a small business loan was at 1000% interest, it might be worth the risk. There are a lot of moving parts.
Thanks for the question. I hope the answer was helpful.