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Thanks for this writeup. Whenever people complain about some service removing or making it harder to try out a free tier, I think they don't realize the amount

Thanks for this writeup. Whenever people complain about some service removing or making it harder to try out a free tier, I think they don't realize the amount of abuse that needs to be managed by the service providers. "Why do things suck?" Because parasites ruined it for the rest of us. > We have to accept a certain amount of abuse. It is a far better use of our time to use it improving Geocodio for legitimate users rather than trying to squash everyone who might create a handful of accounts Reminds me of Patrick McKenzie's "The optimal amount of fraud is non-zero" [1] (wrt banking systems) Also, your abuse-scoring system sounds a bit like Bayesian spam filtering, where you have a bunch of signals (Disposable Email, IP from Risky Source, Rate of signup...) that you correlate, no? [1] https://www.bitsaboutmoney.com/archive/optimal-amount-of-fraud/ https://www.bitsaboutmoney.com/archive/optimal-amount-of-fra...

dehrmann 2y ago
> "The optimal amount of fraud is non-zero" [1] (wrt banking systems) It's a bit like how each 9 of runtime is an order of magnitude (ish) more expensive to achieve, and most use cases don't care if it's 99.999% or 99.9999%.
mjwhansen 2y ago
Co-Founder of Geocodio here who designed the scoring system :) I suppose you could call it inspired by Bayesian inference since we're using multiple pieces of independent evidence to calculate a score, though that makes it sound a bit fancier than it is and we aren't using the Bayes' theorem. But it's possible I had that in the back of my head from a game theory class I took long ago. But for the fun of it, let's model it that way: Probability (Spam | disposable email domain, IP address, etc... ) = [probability(disposable email domain, IP address, etc... | spam) x prior probability(spam rate)] / probability(disposable email domain, IP address, etc...) Or something like that. Also — it's a delight to have one of Patrick's articles mentioned in connection with this!

dehrmann 2y ago

> "The optimal amount of fraud is non-zero" [1] (wrt banking systems) It's a bit like how each 9 of runtime is an order of magnitude (ish) more expensive to achieve, and most use cases don't care if it's 99.999% or 99.9999%.

mjwhansen 2y ago

Co-Founder of Geocodio here who designed the scoring system :) I suppose you could call it inspired by Bayesian inference since we're using multiple pieces of independent evidence to calculate a score, though that makes it sound a bit fancier than it is and we aren't using the Bayes' theorem. But it's possible I had that in the back of my head from a game theory class I took long ago. But for the fun of it, let's model it that way: Probability (Spam | disposable email domain, IP address, etc... ) = [probability(disposable email domain, IP address, etc... | spam) x prior probability(spam rate)] / probability(disposable email domain, IP address, etc...) Or something like that. Also — it's a delight to have one of Patrick's articles mentioned in connection with this!