[npcomplete]

(I work for balanced, I wrote the blog and handle fraud) I am sorry you had to deal with this. Of course, we look at all other signals and of course we use machine learning. What I posted was partial information. the list by no means is complete. When dealing with opening up on fraud, you deal with two conflicting things - (1) If you open your algorithms/data and make it completely open source, the fraudsters have all the access as you do and (2) If you shut down all access and keep it closed, there's no exchange of information. Most payment processors opt for (2), we really wanted to strike a middle ground. If I can't expose the fact '@apple.com' email address is more trustworthy than a throwaway email address and regard this piece of information as the bed rock of fraud protection, I am nuts. Summary: you expose something, gain knowledge, hide the rest. There are several more signals we look at when dealing with fraud (esp. digital goods). We have built a machine learning system that has learned (is learning) from our data. We also built visualization layers on top of that. Send us an email at [e-mail] and I will provide more information.