All posts with the tag Machine Learning
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
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
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
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
It seems like every tech company is using machine learning these days. Or, at the very least, talking about it. It’s a cutting-edge concept that’s getting a lot of buzz. But what does it really mean? In this post, I’ll first explain the basics of what the term means, and then how Riskified uses machine learning to drive accuracy when vetting orders for fraud.
How does Netflix know what I want to watch?
Why is Netflix so popular? Yes, they have a great selection of old movies, and their original content keeps getting better. But one of the features that really sets them apart from the competition is the accuracy of their viewing suggestions, tailored to your taste based on what you’ve watched previously. Sometimes it feels like they know exactly what you want to watch. How did they do it?Read More
Global online retail sales are projected to exceed $2 trillion in 2017, and double to $4 trillion by 2020. Despite this rapid growth, selling online is not without its challenges, and eCommerce merchants are increasingly seeing their hard-earned revenue fall victim to CNP fraud and the associated chargebacks. A 2016 study confirmed this, with online merchants reporting that chargebacks accounted for much of their fraud-related revenue loss.Read More
Direct video surveillance of shoppers has long been the holy grail of fraud prevention, and today–after years in development–Riskified is thrilled to unveil the latest advent in fraud-prevention technology: ‘Cameo’. Cameo is a proprietary fraud detection technique powered by behavioral analysis of online shoppers, which can automatically determine the legitimacy of an order with extreme accuracy.
Early trials of Cameo have yielded exciting results, and we expect this surveillance data will allow us to dramatically improve our merchants’ approval rates while nearly eliminating CNP fraud.Read More