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. cside's Device Intelligence draws on a baseline of 250+ browser, device, and network signals per session, with no cookies, and weights them into a stable, privacy-preserving device identifier. Because cside identifies the device itself rather than an IP or a logged-in identity, it catches fraud that reuses one machine across many accounts or attempts: account takeover, multi-accounting, trial abuse, and bots. It runs from a single first-party cside script and flags high-risk sessions in real time.
How does cside handle browser-based fraud detection for fintech companies?
cside's Device Intelligence captures a baseline of 250+ browser, device, and network signals per session to build a privacy-preserving device identifier, with no cookies.
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.