Most of you have heard of Tinder: the highly addictive (or so I’ve been told) dating application. Since launching in 2012, the original swiping app has generated over 20 billion matches which, yes, is far more than the number of humans on the planet.
A lot of Tinder’s success can be attributed to very advanced algorithms which ensure that people with high probabilities of mutual interest are shown to each other. That’s right: the profiles displayed to Tinder users are not shown in random order, they are placed very deliberately.
The specifics of the algorithms are kept secret to prevent users from gaming the system and competitors from stealing it. But we do know a big part of their technology is built on a platform called elastic – and Tinder generates 280 million queries on this system every day.Read More
Fraudsters employ all sorts of tricks to deceive online retailers and get away with eCommerce fraud. In previous Halloween posts we shared best practices for deciphering between good and bad orders, as well as tips for unmasking fraudsters (while keeping false declines to a minimum).
This Halloween, we’ve decided to put our readers to the test! Take our quiz, based on data from real orders we’ve reviewed, to find out if you’re easily tricked, or could cut it as a fraud analyst!
Good luck…Read More
No merchant is immune to the risk of attack from sophisticated fraud rings. And even if you think your eCommerce store is handling that risk well, complacency is a dangerous choice. Threats from fraud rings often arise unexpectedly and the strategies and schemes they use are continuously evolving.
On average, fraud costs merchants 8% of their annual revenue, and fraud rings account for much of the large-scale fraud that merchants encounter. In this post, I examine the dangers posed by fraud rings and provide actionable tips to help businesses detect and foil these attacks.Read More
Riskified is pleased to share our ‘Visualizing eCommerce’ series, a new interactive medium our readers can use to review data they don’t usually have access to, mainly around eCommerce fraud. Our first installation is a world map, organized according to approval rate categories.
Geographic data is based on IP address. Hovering over each country will reveal which industry encounters the highest and lowest rates of fraud, as well as the highest and lowest cart values.Read More
Everyone has heard about it by now. Equifax, a provider of credit scores, was hacked between May and July of this year. PII (Personally Identifying Information) for about 140 million Americans was potentially compromised, as well as the details of over two-hundred thousand credit cards.
We’ve been hearing a lot of concerns from merchants that the Equifax breach could result in more fraud attacks and chargebacks for their eCommerce stores–and wondering if they need to be more cautious in approving orders now. But despite some recent scary headlines, we’d like to urge eCommerce retailers to stay calm. Overreacting to this breach is likely to cause more problems than it solves.Read More
Shoppers don’t arrive at your eCommerce store by chance. They either typed in your URL directly, arrived via search engine, or clicked a link on some other website. Merchants usually use this information to maximize the quantity and quality of their site visitors. But one aspect that tends to get overlooked is the rate at which channels are bringing fraudsters to your site.
With a better understanding of this traffic, merchants can concentrate marketing resources on channels with less fraud, and even improve their fraud detection accuracy.Read More
It’s no secret that millennials spend a lot of their money shopping, and unsurprisingly 67% of younger consumers prefer purchasing online. US college students alone have an estimated buying power of $523 billion, and with a lifetime of online shopping ahead of them, they are a highly lucrative eCommerce growth engine.
Yet many retailers fail to consider how their approach to fraud is preventing the maximization of profits from college-aged consumers. In this blog, I share some insights about their importance as a consumer demographic. Better understanding fraud patterns can assist merchants in nurturing these young customers and tapping into this safe revenue stream.
It’s hard to imagine what the internet would look like without Google Analytics. It’s a powerful tool for eCommerce retailers to understand the efficacy of their online marketing campaigns, learn about their online customer base and optimize their various shopping pages.
But it turns out that this web beacon is good for more than just analytics.Read More
What is an AVS mismatch? And how does it apply to fraud?
AVS (Address Verification System) was designed to combat CNP (Card Not Present) fraud. The idea behind AVS is simple: cross-referencing the numeric elements of the billing address provided by the buyer with the numeric portions of the billing address on file at the credit card issuer will enable merchants to verify that the buyer is the rightful cardholder.
Payment processors encourage merchants to set automatic AVS mismatch filters as an anti-fraud measure. However, many merchants who use these filters do not realize that a full AVS match does not ensure a transaction isn’t fraudulent. On the flip side, orders with AVS mismatches are often legitimate. In this post, we will show what AVS rejection means and why rejecting orders solely based on AVS information is a bad idea.Read More
Managing eCommerce fraud operations is no easy task; whether hiring, training, and managing a manual review team, monitoring approval rates, and optimizing internal rules, a fraud manager’s attention is often drawn to many places at once. With so much on their plate at any given time, it’s easy to understand why merchants are drawn to “silver bullet” solutions to manage and prevent chargebacks.
One “solution” to chargebacks often utilized by merchants is fraud prevention blacklists. When hit with a chargeback, all the transaction details are simply added to a blacklist, so that the next time an order is placed from the same email or IP address, the transaction is automatically declined. While they may seem like a great way to streamline internal operations and to prevent future fraud, blacklists are in fact a misguided way to address chargebacks.
Blacklists block not only fraudsters but also many good customers. Moreover, there are basic methods fraudsters can use to “fool” your blacklists. In this post, I will explain why you should stop relying on blacklists for fraud prevention.Read More