HOW DATA SCIENTISTS CAN BRING THEIR OWN MACHINE LEARNING TO FIGHT FRAUD
The problem is that the most advanced fraud-fighting vendors often constrain your data scientists with singular data science environments and proprietary frameworks. That’s why Feedzai built the OpenML Engine. We believe your data scientists should have the flexibility to build models in any language, using any library, and on any platform. They they should be free to import these approaches to a platform that was purpose-built, from the ground up, to fight new and evolving financial crime.
HOW PSD2 CHANGES THE WAY YOU FIGHT FRAUD: A GUIDE FOR BANKS
The PSD2 transformation promises to make life better for customers. But will these changes come at a cost? As PSD2 disrupts commerce, it threatens standard fraud prevention strategies too. We all know that fraud evolves constantly, and without an established risk plan to guide you through the new world of open banking, your organization is exposed.
THE ACQUIRER’S PLAYBOOK FOR MANAGING RISK
How to fight fraud, increase business and stay competitive.
It’s no secret that our push towards technological innovation in digital payments has made fraud a clear and present danger for acquirers. According to the Association of Financial Professionals, 74% of organizations have experienced attempted or actual payments fraud in 2016.
FIGHTING ACCOUNT OPENING AND APPLICATION FRAUD WITH MACHINE LEARNING
Retail banks face unique challenges at the point of account opening. There’s a “thin-file problem” due to gaps in historic data, and bad digital experiences as customers travel between silos. It’s no surprise that 74% of financial institutions stated having multiple independent projects underway to improve customer experience.
WHAT’S NEXT FOR MACHINE LEARNING FOR FRAUD
What’s the current state of explainability in machine learning for fraud? In this ebook, read about the critical need for an AI system that can share its thought process with us in perfectly human terms, so we can transform machine learning into machine teaching.
OPERATIONALIZING MACHINE LEARNING FOR FRAUD
Read this free 11-page report and get actionable insights to help you create a strategy for taking charge of the AI disruption that’s well underway.
CHOOSING A MACHINE LEARNING PLATFORM FOR RISK (BANKING)
Download this report to peek into the future of fraud. Learn more about precise segment-of-one profiling, explainable whitebox AI, better enterprise fraud protection, and how to future-proof data ingestion.
HOW MERCHANTS CAN CHOOSE A MACHINE LEARNING PLATFORM FOR RISK
WDownload this report to peek into the future of fraud. Learn more about how merchants can use explainable Whitebox AI, precise segment-of-one profiling, Future-proof data ingestion, and better enterprise fraud protection.
ONLINE ACCOUNTS: THE NEW RISK PARADIGM
Download this E-book to learn: The Four Types of Risks in Online Accounts, An Omnichannel Risk Prevention Strategy, and An Omnichannel Machine Learning Solution.
MACHINE LEARNING FOR FRAUD
Learn how to eliminate high maintenance rules based engines, reduce false positives & make better decisions with machine learning basics.