My friend taught me to use Relative Risk as a guide to check if my coefficients make sense. For example, I have a propensity to default model, where the variable fl_default is equal to 1 if the individual defaulted and equal to zero if he didn't default. I also have the region where individuals belong: A, B, C, D and E - and other variables. In the figure below, I have the number of people that defaulted in each region and their relative risk, and what I understand is that people in region A, B and D are good customers, they have more propensity to pay.
However, if I run a logistic regression and the coefficient for the predictor REGION is the opposite of this Relative Risk, should I treat this variable (make some modification) or it is possible that the coefficient gives a different direction than the relative risk? What could be happening with my model?