Yeah, I'd assume someone with a [email protected] email and a web presence is probably an indicator it's legit rather than fraud :)
That's correct, but not at all correlated with us being likely to commit fraud.
It's 79% certain the office LAN NAT gateway IP is a VPN/proxy/bad.
My work desktop's static IP gets 23%, so that's something.
My home IP gets 60%.
(Is this thing just connected to a random number generator?)
At order time I create a Google Map of the delivery address and this shows on checkout success. It also shows in the admin side with a live Google Map. If Google can get the address right then the postman probably can is the thinking.
This reduces delivery problems immensely as anything that cannot be shown on a map goes on automatic hold.
Money wasted on delivering the wrong products to people, e.g. after they have managed to cancel their order, plus the costs of back room accounting/customer service is a far bigger cost than fraud.
In your experience did you have savings to be made in your operation in shipping/customer service, to optimise that before tightening up on fraud prevention?
Or do you sell expensive items in a low-ish volume where a single fraud wipes out all of your profits rather than just cost $20 or so?
We ended up disabling the AVS system and implementing our own internal system which has been nearly perfect - but we still lose a number of legitimate customers who are unable to pass the automated verification.
Meanwhile, people who are simply trying to get flexible--or, in the case of someone using a Google Voice number on a Google account with 2FA and a strong password, a more secure phone number than T-Mobile could provide--communications are needlessly punished.
- Orders are placed with stolen credentials with correct billing info that matches AVS.
- Shipto address are located near billing info, typically in the same state/metro area.
- They are often rural addresses, trailer parks, what appear to be rent houses that may be empty.
- Phone number provided has correct area code and rings a call center that has stolen billing info available and will confirm billing address order details verbally.
- Ip is geolocated at/near the billing info area via a proxy.
- Email addresses are often setup on custom domains.
We catch them, but only because they don't vary the pattern much and we know what to look for. I don't know how fraud tools would be able to effectively filter in these cases without a lot of false positives.