How can you tell good orders from bad?

You can’t do it alone. But in the Community you can.

Fraudsters work around the clock to disguise themselves as the very thing you want most: good customers. And the great ones are experts at doing just that.

By using more sophisticated methods and better organizing their efforts, fraudsters are moving from site to site, stealing as they go—and getting off scot-free.

The worst thing about this is the better they get, the more you’re going to doubt each and every order coming through your site.

Their actions hurt your good customer relationships, and this ends up costing you far more.

On average, online businesses refer more than 27% of orders for manual review (source: 2007 CyberSource Survey). Of the number sent for review, two-thirds of merchants end up accepting over 80% of them.

It′s no secret that when a good customer’s order is held up or treated as potentially fraudulent, it makes for a bad customer experience—and it’s highly unlikely that customer will return.

Most tools attempt to sort out which orders are bad based on predictive scoring algorithms or evaluating other risk factors in your data and public records—all of which don′t provide sufficient information.

In other words, they guess. They don′t know. And this is the primary source of errors when both accepting bad orders and refusing good ones.

See Global Fraud Alliace Members >>