[talawahdotnet]

I currently use Maxmind's midfraud service. It is useful for identifying KNOWN fraudulent email addresses and proxy servers but not much else. It is just one of the signals that I currently use as a part of a fairly manual fraud review process.

I have evaluated a number of different options and I am about to start using Sift Science[1]. In addition to using standard ip address/email based information they also use social data and machine learning to identify fraud.

Their API/data model is the most well thought out and comprehensive one that I have come across and they allow you to back-fill up to 12 months of historical data for free to help improve your detection rates. They also have a console to assist with optional manual review workflows and store integration apis to allow full automation.

On top of all that they offer scalable pricing that works for both large and small business at 6c per transaction.

Obviously I can't vouch for their results yet, but what I have seen so far looks pretty good. If you have a fraud issue you should at least check them out.

[1]https://siftscience.com/

[joshmn]

I'll say that I like Sift better than MaxMind, but it still doesn't cover a lot of things that it should. I won't go into details, as I'm in the middle of building a platform to solve this issue myself, but as someone who used to be on the other end of credit card fraud, it's really laughable how many things these companies don't see.

[jasontan]

Hi Josh, Jason here, CEO of Sift Science. Would love to hear your feedback on what we could do better, whether publicly or privately - jason at siftscience dot com. We want to do better.