Blackbox machine learning vs whitebox machine learning: What are the differences and why do they matter? And which is better for fraud detection?| SEON
Find the best fraud detection software. Compare 10 leading tools with AI, real-time monitoring, and AML features to protect your business.| SEON
In this extensive guide, we’ll investigate bonus abuse in detail and give you actionable tips and tactics to reduce risk at your iGaming company.| 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
Reducing fraud often means using different solutions. At SEON, we have created a new way for device fingerprinting. Read here why it works against fraud.| SEON
Using email, phone, and IP data collected during onboarding, SEON crafts a highly detailed digital footprint of each user so you can detect fraudsters before KYC.| SEON
Whitebox machine learning explanation. How is it different from blackbox machine learning? Why is it better for fraud detection & prevention?| SEON
Speak with an expert Stop Fraud Before It Happens Accurately detect fraud and money laundering across the entire customer journey using thousands of device intelligence, digital footprint and compliance signals. Get started within days using a single API to fast-track fraud detection. Schedule your meeting Onboard in days, not months “SEON significantly enhanced our fraud […]| SEON
Browser fingerprinting gathers hundreds of data points about your users' devices and browser configurations. But how does it stop fraud, and is it enough?| SEON