It seems like you could use something like the Hosmer & Lemeshow test for goodness of fit. It works with predicted risk under the logistic regression model. H&L is not a very powerful test, so I prefer to use a visual analogue to it. Sort the predicted scores, divide into deciles (quintiles if the N is small), and then plot the midpoint of each decile against the proportion of positive outcomes for the observations in that decile.
If your risk score fits well the line through those 10 points will be reasonably straight. It's basically testing the reliability of your risk driver(s).
Doc Muhlbaier
Duke