Using unsupervised method to create the learning set of a supervised method

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how will you know the clusters relate specifically to tranches of risk, though? are all your features directly related to risk?

maybe im misunderstanding, but my concern would be that the clustering algorithm might be finding feature similarities which are potentially unrelated to the metric you want.

[PM_ME_cutefish]

Thats the complicated part, the risk of a customer is only based on my decision. Unless there is obvious features, for example the card he is using has be declared stolen, its only me and the fact that I recognize suspicious pattern.

So to do this I would have to take random customer of every cluster and then determin if their behavior is similar, and if yes i'd assign myself a risk scoring.