“I would say Riskified changed our lives.”
Eileen Shulock, VP eCommerce at Kirna Zabête
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All posts with the tag eCommerce Fraud Protection

The holidays are only a few weeks away, and fraud teams are gearing up for yet another record-breaking season; sales forecasts call for a 10% to 16.6% volume increase over last year. To help fraud teams prepare for the order surge, we took a close look at last year’s holiday shopping and fraud patterns. Here’s what we found.

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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.

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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…

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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.

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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.

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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.

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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.

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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.

The technology that makes this customer tracking possible is both simple and ingenious. When you register with Google Analytics, you give permission to Google to embed a small snippet of javascript – called a web beacon – on each page of your website. When a shopper visits your site this beacon transmits data to Google.

But it turns out that this web beacon is good for more than just analytics.

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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 why rejecting orders solely based on AVS information is a bad idea.

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Ecommerce revenue for fashion merchants has been growing at an annual average of 17.3% over the last six years. In 2016 it was worth $73 billion in the US alone, second in sales value only to consumer electronics. But this rapid growth raises the stakes on fraud detection for fashion retailers.

When it comes to accurately vetting fashion orders for fraud, there’s no substitute for experience. Riskified provides fraud management services to some of the world’s leading fashion brands, including Fortune 500 companies, and is familiar with the intricacies of safe and fraudulent online shopping patterns within the industry. We analyzed our data to compile a report for fashion retailers, providing insights and best practices for detecting fraud while maximizing online revenue. In this post, I share some of the findings that appear in the full report

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