Rules vs. Machine Learning: Why You Need Both to Win

Rules-based fraud prevention systems have a number of drawbacks when compared to the sophistication of machine learning, but is a machine learning-based system the be-all and end-all of fraud prevention? Can rules actually prove to be beneficial while making the transition to machine learning? We explored these and other questions in our webinar, Rules, Machine […]

Build vs. Buy: 5 Capabilities You Need in a Fraud Tool

When considering whether to build or buy your fraud prevention tools, there are a lot of criteria to assess. What is your in-house level of technical expertise? What are your time constraints? Would developing this technology be a core competitive advantage? And more… In our recent webinar, Building versus Buying: Understanding the Right time for […]

Improved developer experience: New API reference

Successful fraud fighting starts with a seamless integration, and we want to ensure you’re set up for success. We recognize the importance of well-thought-out documentation, which is why we’re excited to launch a redesign to our API reference. Based on feedback we collected from customers, as well as our team’s own experience using our documentation, […]

Machine Learning for Fraud Prevention: What’s Next

Advancements in technology – including improvements in computing power and wide-scale availability of big data – have radically changed how companies use machine learning. Fraud prevention is a major area in which machine learning is transforming both workflows and outcomes, allowing organizations to stay ahead of increasingly technologically advanced criminals. How can you take advantage of […]

News Roundup 5/22: Eddie’s stolen password database, the perfect Twizzler, and new malware

“Eddie’s” stolen password database discovered Fraudsters often rely on databases of stolen data to carry out their schemes, buying and selling emails and passwords over the dark web. Security researchers recently found one of these databases…and it’s huge. This particular database contains 560 million stolen passwords and emails. Some of the information was collected from site […]

10 Things You Need to Know about Digital Natives

The generation born after the invention of the internet is native to two worlds: the physical world, and the virtual. If that seems overly dramatic, consider this statistic: Millennials spend over 7 hours a day online! Education consultant Marc Prensky coined the term digital native to describe this generation, which is growing increasingly influential. So, […]

10 Surprising Ways Machine Learning is Being Used Outside Tech – Part 2

As machine learning (ML) continues to take over the tech world, companies and researchers outside the tech bubble have started using ML in strange and surprising ways. We already covered a few unusual ML applications, from diagnosing psychopathy to getting an edge in the Tour de France. Here are five more unexpected ways machine learning […]

News Roundup 5/1: Getting dressed with machine learning, billion-dollar hacking, and Senate security flaws

Amazon’s Echo Look dresses you up with machine learning Unless your closet looks like Mark Zuckerberg’s, you’ve probably spent ten minutes in front of the mirror deciding whether you really want to wear those pants today. Amazon’s solution to your indecisiveness? The Echo Look. The Echo Look uses machine learning to help Alexa (Amazon’s Siri-like […]

News Roundup 4/24: Fake Facebook accounts, hotel data breaches, and fingerprint scanners

Facebook purges 30,000 fake accounts ahead of French election Wondering how many fake social media accounts you interacted with today? If you’re a Facebook user, that number is lower than it was yesterday. To prevent fake news from influencing the French presidential election, Facebook is cracking down on fake accounts across 14 countries. They’ve already […]

10 Surprising Ways Machine Learning is Being Used Outside Tech – Part 1

Machine learning is taking the tech world by storm. 2016 began with an announcement that Google was open-sourcing Tensor Flow, their machine learning (ML) software, and Microsoft quickly followed suit. Baidu and Amazon unveiled their own deep learning platforms a few months later, while Facebook began supporting the development of two ML frameworks. But the […]