What would the GLM predict as an outcome? UMAP is fine for dimension reduction, but it doesn't output classes. Clustering, prediction (class or value), and dimensionality reduction are all trying to get at different aims with at best a little bit of overlap.
I would say to look at credit utilization as a function of the other variables. Or more generally each variable as a function of the other variables. There is a bit of this in the initial correlation analysis, but a GLM is more robust.