I am developing a logistic regression model on a large dataset consisting of 15 variables and 200k observations.
In initial model fitting, I find variables - "Purchase Frequency" and "Average Payment Amount" are highly correlated (GVIF values around 20) and both are significant in terms of p value.
When I remove one of these two variable, the other variable becomes insignificant and also few other variables (low VIF value) becomes insignificant from significant in previous case.

How should I proceed with this?