As more and more economic activity moves online, fraud is never far behind. Online fraud is in many ways more attractive to criminals as it can be committed at a safe distance from its targets and scales far better. It is therefore not surprising that online fraud has been growing rapidly, is well organized and technologically sophisticated.
There are two different possible responses to online fraud. On the one hand there is legislation and enforcement. That has proven difficult and problematic. Difficult because much of the fraud emanates from different jurisdictions altogether, some of which have shown little to no interest in enforcement. And problematic because of the unintended side effects of legislation, such as the overly restrictive CFAA.
On the other hand there is fighting fraud with technology. Almost two years ago a small team formed Sift Science with the goal of using the latest advances in machine learning to provide a fraud fighting solution to anyone operating on the Internet. Today Sift Science is making their solution publicly available with a self service sign up. Behind the scenes it has already been fighting fraud at such companies as AirBnB, Uber, Listia and Affirm as well as a several mobile applications, payment processors and online retailers.
Sift Science's machine learning algorithm constantly uncovers new fraud patterns. Because Sift Science operates as a network of participating companies, a pattern that is discovered in one part of the network is immediately recognized for all other participants. The results have been outstanding, with fraud losses reduced by as much as 90%. By offering such a powerful solution in a self service model, Sift Science is helping to address the large fraud protection gap that exists today. According to the Lexis Nexis 2012 "True Cost of Fraud" study, less than a quarter of merchants use automated transaction scoring. Sift Science's self service signup and an easy to use API can make a big difference here.
For all of these reasons we are thrilled to be investors in Sift Science. You can read more about Sift Science's technology and service offering on their blog. Or you can simply go ahead and sign up for their service.
Source: http://www.usv.com/2013/03/sift-science.php
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