Blackbox machine learning vs whitebox machine learning: What are the differences and why do they matter? And which is better for fraud detection?| SEON
Boost decisions, fight fraud, and cut friction with data enrichment. Learn how smart signals turn basic data into powerful business insights.| SEON
APP fraud is rising with real-time payments, costing billions. Learn how AI, ML, and monitoring tools help detect and prevent these scams.| SEON
Payment fraud prevention isn't simply useful to boost profits. It's now a primordial business decision. Here's how to do it right at your business.| SEON
Discover the principles of digital footprinting, how it uncovers online fraud patterns, and best practices for analysis.| SEON
Synthetic identity theft and synthetic identity fraud confound online businesses. Here's how your fraud prevention tools should help.| SEON
Better fraud prevention starts with better fraud scoring. Here's how it works, and where you could improve yours with a whitebox system.| SEON
It seems machine learning technology is particularly effective in these fields. The algorithms know how to look for patterns in data, extract them and apply rules that refine themselves overtime. So does that mean you can just go ahead and invest in ML (machine learning) to solve all your fraud detection needs? Not necessarily.| SEON
Uncover complex fraud patterns and continuously improve your fraud detection with proven AI insights from whitebox and blackbox machine learning models.| SEON