Let's say you add these digital signature variables to your credit risk scoring model anyway. The model then falls prey to confusing correlation with causation. What happens to the performance of the model?
I have no idea, as merely adding them may have no effect at all.
However, depending on them exclusively (or in substantial/majority part), which I believe is the main premise, the eventual performance will depend entirely on if the the actual causal relationship which created the correlation holds true. If it doesn't, the model would no longer be predictive.
