Just like good customers, fraudsters must provide a shipping address in order to receive merchandise. But fraudsters’ need to evade detection and efficiently resell stolen goods leaves a trace in the shipping addresses they use. The minFraud network collects data on shipping addresses and uses it to identify any high risk shipping addresses associated with the transactions you submit for minFraud review.
This blog post investigates some high risk shipping addresses known to MaxMind, as well as provides some general fraud review tips for identifying them.
As a merchant, you’ll frequently see cases where multiple orders with different billing addresses and payment methods are placed from the same IP address, and it’s not clear whether or not this indicates fraud.
Such activity could be a sign of fraud, with a fraudster testing multiple compromised credit cards. It could also be a sign that a fraudster is using a proxy to obscure his identity. There are times though when such activity is expected and flagging such transactions as fraudulent would mean denying good orders and frustrating customers.Continue reading →
The new year has arrived. With transaction history from a busy holiday season on hand, this is a great time to take a look your historical transactions with a fresh and critical eye.
Reviewing your chargeback data to identify fraud patterns is a good way to get started. In this month’s blog post, we provide a case study of an online penny auction business, which improved their bottom line by doing just that. Continue reading →
In this blog post, we continue our discussion of best practices for manual review. Today’s topic is assessing IP address risk.
A fraudster (or indeed, anyone) placing an order on a website uses a device (computer, mobile phone or tablet) and this device is associated with an IP address.
In our last blog post, we discussed how the physical location of the IP address can be matched against other location information to see if anything looks suspicious. For example, it’s best to closely scrutinize orders where the location of an IP address is in one country and the billing address in another.
Fraudsters recognize the power of geolocation in identifying fraud, so they act to hide their actual IP address and, by extension, their geographic location. The best way for them to take cover is to connect to the Internet using a proxy server. Popular hiding places include open proxies, hosting providers and VPNs. Continue reading →
In our last blog post, we discussed how you can use a risk score to automate fraud screening, saving you time and money.
In this blog post, we begin our discussion of manual review best practices.
Studies show that, in North America, one in four orders on average receive extra scrutiny through the manual review process. The goal is to prevent the expense of chargebacks and customer issued credits associated with fraud. At the same time, you need to ensure that legitimate orders are not rejected unnecessarily, and estimates suggest that this is the case with up to 10% of orders. Rejecting good orders negatively impacts the bottom line, and drives away good customers.
During manual review, fraud analysts examine data associated with an order to assess how likely it is to be fraudulent. One key area of data points to consider is that of geolocation. Continue reading →