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I agree the post looks a little AI written but generally this kind of analysis is quite common. Leaving aside human heuristics that are generally too well known
by janpeuker 5mo ago
I agree the post looks a little AI written but generally this kind of analysis is quite common. Leaving aside human heuristics that are generally too well known to catch real scammers (like time travel or "7 days", which is bad because often weekly patterns are important so at the very least look at 10 days) and actually have low precision, what I find odd it that all results just return a user ID.
So this is really just surfacing cases, but with not enough context to be useful to prioritise. I would expect a score to be included.
Apart from that it misses a lot of signals like refunds, declines, disputes etc [1].
1) https://stripe.com/gb/guides/improve-fraud-management-with-radar-for-fraud-teams-and-stripe-data https://stripe.com/gb/guides/improve-fraud-management-with-r...
- stripefan 5mo ago[flagged]
- janpeuker 5mo agoThanks for clarifying the rule - I wasn't aware of that and follow it next time. But I also don't think it's a marketing link. The post explains why specifically in the cases of transaction fraud other signals are important, with specific SQL examples, and that should translate to any other payment provider.
- stripefan 5mo ago[flagged]
- dang 5mo agoThere's no such rule.