TRACIO creates a persistent hardware-level device identity that survives cookie deletion, IP rotation, and card changes — helping you detect fraud rings before fraudulent payments are approved.
TRACIO intercepts fraud before the payment processor ever sees the transaction.
Every checkout visitor receives a persistent device trace. The identifier survives cookie clears, incognito mode, and browser switches.
TRACIO instantly retrieves the device's full history: previous accounts, past chargebacks, velocity patterns, and linked devices across your entire platform.
Device signals, IP intelligence, behavioral anomalies, and historical fraud patterns merge into a single risk score returned in real time.
High-risk transactions are blocked or routed to manual review. Low-risk returning devices pass through with zero friction — no CAPTCHA, no step-up.
Payment fraud is no longer about stolen card numbers. Modern fraud rings operate with real devices, residential proxies, and valid credentials purchased on dark-web marketplaces. They clear cookies between transactions, rotate IP addresses every session, and use anti-detect browsers to appear as unique visitors.
Legacy fraud prevention relies on rules built around IP reputation, AVS matching, and velocity checks. These signals are trivially spoofed. The result: legitimate customers get blocked while sophisticated fraudsters sail through checkout.
The missing layer is persistent device identity. When you can tie every transaction back to a physical device — across sessions, browsers, and VPN hops — fraud rings lose their primary evasion tool: anonymity.
Each pattern exploits a blind spot in session-based fraud tools. TRACIO closes the gap with persistent device memory.
Fraudsters test stolen card lists with small transactions before making large purchases. TRACIO links every test to the same device trace, flagging the pattern before the big charge hits.
Organized rings share devices and accounts across members. Cross-device graph analysis exposes hidden connections between seemingly unrelated transactions.
Commercial anti-detect tools generate a unique browser fingerprint per session. TRACIO's hardware-level signals see through the spoofed canvas, WebGL, and AudioContext values.
Attackers create fake identities by combining real and fabricated data. Device history reveals when a 'new customer' is actually a known bad actor on a recycled device.
Ranges below are drawn from published industry research and are illustrative for early-access deployments.
reduction in payment fraud losses
Aite-Novarica / Datos Insights, 2024
drop in manual review queue volume
Signifyd case studies / industry benchmarks, 2024
false positive rate after tuning
Experian Fraud Research, 2024
ROI vs. subscription cost
Forrester TEI methodology, 2024
Results vary by industry, traffic volume, and existing fraud stack. Figures represent ranges observed across published industry research and are not guarantees.
projected merchant losses to online payment fraud between 2023 and 2028 — driven by AI-powered attacks and emerging-market e-commerce growth.
Juniper Research, 2023 five-year forecast
Identify every checkout visitor with 99.5% accuracy. The trace survives cookie clears, incognito mode, and anti-detect browser spoofing.
Real-time risk assessment combining device signals, IP intelligence, velocity analysis, and behavioral biometrics.
Automatic linking of related devices across accounts. Expose fraud rings operating with shared hardware and credentials.
Detect headless browsers, Selenium, Puppeteer, and Playwright. Flag DevTools usage and automation framework artifacts.
Identify VPN, Tor, residential proxy, and datacenter traffic. Detect IP-device mismatch patterns in real time.
Track transaction frequency, account creation speed, and payment method rotation per device — not per cookie.
A few lines of code, one API response with everything you need.
import { Tracio } from '@tracio/sdk'// Initialize on page loadconst tracio = Tracio.init({ publicKey: "5ca175fc..." })// Read the identification result at checkoutconst result = await tracio.getResult()// Send to your backend with payment dataconst res = await fetch("/api/checkout", { method: "POST", body: JSON.stringify({ visitorId: result.visitorId, botDetected: result.bot.detected, cardToken: stripeToken, amount: cart.total, }),})Related products
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