[mehrdadn]

> so the primary reason might be that the IP is in country X, but that doesn’t mean there’s a blanket ban on X—just that that reason combined with everything else we saw across thousands of signals resulted in our giving the payment a high score

It might not be that one reason, but could it be something like the following two? Because that would be practically equivalent in terms of unacceptability:

1. Customer IP is in a high risk location, and

2a. Vendor rarely does business successfully with people in that location, OR

2b. Vendors around this region don't usually do business successfully with customers in that region.

("Does business successfully" here was meant to both encompass lack of transactions as well as lots of unsuccessful transactions; I'm asking about both possibilities.)

[mlm]

In short, no.

A little more color: Stripe’s incentives are aligned with those of our users in that we want to let through as many legitimate customers as possible. We keep a very close eye on false positives.

Our machine learning models examine thousands of attributes for each payment and make predictions based on how frequently the observed attributes were associated with fraud in the past. The comparison here is never just on one or two or three attributes (as in your example), and no logic is hard-coded.