Sift Science is excited to announce that we’ve launched a podcast, Trust & Safety in Numbers! On Trust & Safety in Numbers, our host, Evan (that’s me!), and our trust and safety guru, Kevin Lee, will chat with people on all sides of the online fraud fight: fraud analysts, FBI agents, security consultants, former hackers, rogue cyborgs (okay, […]
New Forrester Report: Mitigating Threats Beyond Payment Fraud
We’re all competing in the new digital economy. Customers’ expectations are higher than ever. Businesses are under more pressure to deliver a fast, simple, and safe experience. And fraudsters are diversifying their tactics, looking for inventive new ways to cash out. How can businesses be prepared? Sift Science commissioned Forrester Consulting to find out more […]
5 Ways Blockchain Will Make Payments More Secure
If you’re into technology, you probably already know about the blockchain. It’s the decentralized database technology behind bitcoin that’s predicted to become as “big as the internet,” disrupting the way we trade and track goods and services. How does blockchain work? Essentially, it’s a decentralized database accessed by a peer-to-peer network of computers and people […]
Sift Science Fraud-Fighting Trends 2017
Fraud-fighting is the ultimate balancing act. On one side, you have risk – in the form of fraudsters, scammers, and other bad actors looking to leverage any opening they can to exploit your business for their own gain. On the other side, you have the goal of optimizing user experience – a priority for any modern online business that […]
Machine Learning Isn’t Always a Black Box
There are a number of common myths about machine learning, which we touched on in a previous post. Now, we want to dive deeper into one of those myths: that machine learning is a black box. While it’s true that many machine learning platform companies do not provide any insights about results or explain how their […]
6 Things We Learned About Fraud Last Year – And What’s Next for 2017
When it comes to fraud and cyberthreats – and most things, in fact – 2016 was a doozy. Will next year be even doozier? (Please, no!) After last year’s tongue-in-cheek fraud predictions post, we decided to gather some more earnest thoughts about what 2017 might hold. 1. Account takeover will be the next frontier of fraud From […]
New Visa Attack Hole Demands New Fraud Defenses
Evan Schuman is a guest contributor to the Sift Science blog. When security researchers recently published that multi-merchant attacks gave them unlimited attempts at guessing Visa card fields (but not Mastercard fields), it was a reminder of the inherent fragility of payment card security today. One way to successfully defend against such an attack is by […]
“The Big Data Opportunity May Be Even Bigger Than People Thought” – Q&A with Matt Turck
“In a tech startup industry that loves its shiny new objects, the term ‘big data’ is in the unenviable position of sounding increasingly ‘3 years ago’,” wrote Matt Turck, Managing Director of FirstMark Capital, in a widely-read blog post in early 2016. Now that we’re edging towards 2017, has anything changed? We talked to Matt – […]
Mobile Commerce, Payments, and Fraud By the Numbers
Does it feel like more and more people are working on the go, totally tapped into palm-sized screens? That’s because they are. Consider how often you pull out your phone, whether to check a message, log a mile, get directions, or play a game. Mobile use is at an all-time high, and as a result more […]
6 Myths About Machine Learning
Machine learning is everywhere – but many people aren’t even aware of it. It’s on smartphones, automatically tagging photos and powering the voice-activated intelligent assistant. It’s on numerous websites, powering chatbots and providing personalized recommendations. It’s in connected cars, allowing drivers to control the infotainment system using voice-activated commands. Let’s start with a basic definition: Machine learning is a […]