5 Ways to Make Your Fraud Protection Better
June 5, 2014
Inc.com recently reported that small businesses that use mobile do not use enough fraud-prevention measures, though mobile fraud costs them three-times more that the value of the stolen product. Often, robust fraud protection is seen by smaller businesses as cost-prohibitive, but it’s also a matter of simply not knowing what’s available. Today’s fraudster is savvy, technologically advanced, and able to easily mask their identity, and fraud management needs to be multi-faceted to be keep pace. Developing a risk management infrastructure is complicated and nuanced, but here are a few key practices merchants of all sizes can put in place to better identify fraud and prevent chargebacks.
1. Proxy Detection (& Evaluation)
If you aren’t doing it already, proxy detection is a very important first step in evaluating an order for fraud. Services that perform real time analysis for proxy detection are usually the best and most accurate way to detect a proxy. If you don’t plan to use such a service, simply doing a web search for IP address alongside keywords, such as “proxy,” will allow you to see if it is a current proxy on any public warning lists.
2. Geo Location
A second data point that helps identify fraud is geo location; the endpoint of an IP address can tell you the location of the customer placing the order, if you feel sufficiently confident that there is no proxy. There are many free online services that can identify IP location. The real power of IP information, though, is using it in conjunction with other data points, like shipping or billing addresses and AVS results.
3. Address Verification Service (AVS)
Using AVS data in conjunction with IP address, or other data points, is another way to evaluate the validity of an order. For example, an IP address that is geographically close to the AVS address, could be a sign that the order is valid. But, AVS matches can sometimes be misleading. Do you feel confident that there is no proxy? Does the shipping address match the AVS data? A full AVS match with a different shipping address is essentially meaningless, while an order with no match can be explained by a recent move or a college student shipping to a temporary residence.
4. Data Linking
Keep records of all relevant order data, such as email, billing address, shipping address, and phone number. A recent industry analyst study says that “Big Data” is the best way to combat online fraud; linking data is a simple method that can provide valuable insights about a customer’s order pattern and help you notice negative indicators (signs that the order might be fraud) such as: order velocity, changing credit cards, machine ID, and IP connections and addresses that may have been used with other customer IDs.
5.Hire an Expert
There are a variety of cost-effective ways that even small businesses can better protect themselves, and hiring a third party expert can save you a lot of time, money and headaches later. You can find a number of tools in the Magento app store to help protect your store, whatever the size of your business or budget, and they can reduce some costs associated with building out an entire risk management team. Some services provide specific order information; others provide review tool administrators. Other services are turnkey risk management platforms that take care of the entire order review process.
No matter the size of your store, order review and risk management are not challenges to take lightly. Especially if your dedicated team resources are limited, implementing these tips will help you protect your store against chargebacks and fraud.
Riskified offers the first risk enablement platform that increases sales for e-commerce companies by verifying, approving and guaranteeing high risk transactions. Retailers determine which transactions to review and pay only when a transaction is approved. All approved transactions carry a 100% money back guarantee. Its proprietary technology enables online retailers to capture billions in what would otherwise be lost revenue each year.