I’ve worked in credit risk modeling and it is rather strict the predictors that can be used and well documented. Data comes in from a variety of sources and it is favorable to be skilled in established models than to try something obscure that isn’t intuitive. The models have to work across different sets of time and the varying business processes that may have been in place. Fraud modeling is more flexible, but seemed to have fairly similar results although more trendy things like random forests and neural nets would show up.