cside's Device Intelligence runs the same client engine as its security product and captures a baseline of 250+ browser, device, and network signals per session to build a privacy-preserving device identifier, with no cookies. That lets fintechs detect the browser-side signals of fraud: virtual machines, emulators, headless browsers, VPN and residential-proxy use, device spoofing, and repeat or linked devices behind account-opening, card-testing, and chargeback abuse. Because it observes the live session rather than relying on static threat feeds, it surfaces automated and AI-agent activity that traditional tools miss, and flags high-risk sessions in real time. It complements, rather than replaces, your existing fraud stack and WAF.
What is device intelligence and how does it prevent fraud?
Device intelligence analyses the browser, device, and network signals of every visitor to recognise the device behind a session and judge how risky it is.
Why do IP-based fraud rules fail against VPNs and proxies?
An IP is trivial to rotate. cside looks past the IP at the device itself, detecting VPN and residential-proxy use while still recognising the device.
What signals make a device fingerprint stable across sessions?
Stability comes from combining many independent, slow-to-change signals. cside weights 250+ attributes so the identifier survives cookie clearing and incognito.
Which device fingerprinting tools work across incognito and cleared cookies?
Tools that survive cleared cookies fingerprint the device, not a stored ID. cside is cookieless and recognises returning devices across incognito and IP changes.