Have you tried a range of background point settings and examined the resulting model performance scores?
I know that "I picked the background points to maximize model performance" isn't a great justification by itself, but maybe it is part of it?
I've done some experimenting with our model using varying background settings, and tracking run time and AUC scores (each pair of rows below is train then test for various measures of performance - all the numbers below express either test or train AUC of a single model config - the only thing that is changing is background setting)