NeuroID provides an end‑to‑end fraud protection platform that uses device intelligence, network fingerprinting, and real‑time behavioral biometrics to identify bots, account takeovers, mule activity, and other third‑party attacks across the entire user journey. A single SDK integrates into web and mobile apps, continuously profiling micro‑interactions such as keystrokes and cursor movements to generate risk scores without adding friction for legitimate users, helping financial services, fintech, e‑commerce, and other online businesses reduce fraud and manual review workload.
Funding
Funding not disclosed
Founders
Product
Problem
Online businesses face increasing fraud from sophisticated bots, account takeover attempts, and other third‑party attacks that bypass traditional rule‑based defenses, leading to revenue loss and degraded user experience.
Solution
NeuroID delivers an end‑to‑end fraud protection platform that combines device intelligence, network signals, and real‑time behavioral analytics to identify malicious actors at any point in the user journey. A single SDK integrates into web and mobile applications, continuously profiling interactions such as mouse movements, typing patterns, and device characteristics without adding friction for legitimate users. Machine‑learning models evaluate these signals to detect fraud rings, generative‑AI bots, mule activity, promo abuse, and account takeover attempts from the first interaction. Detected threats are blocked or flagged for review, reducing manual verification workload and preventing fraudulent transactions while preserving a seamless user experience. The solution provides coverage across onboarding, login, profile updates, and checkout, enabling businesses to protect the entire lifecycle with one integration.
Target Audience
NeuroID is aimed at financial services, fintech platforms, digital banks, e‑commerce sites, and any online business that requires secure, frictionless user onboarding, authentication, and transaction processing.
Features
- Real‑time behavioral biometrics that capture micro‑interactions (e.g., keystroke dynamics, cursor movement) to distinguish humans from bots
- Device and network fingerprinting that aggregates hardware, OS, browser, and connectivity data for robust identity verification
- AI‑driven risk scoring engine that continuously learns from emerging fraud patterns, including generative‑AI and fourth‑generation bots
- Unified API/SDK for web and mobile that requires a single integration to protect signup, login, profile changes, and transaction flows
- Invisible protection mode that operates without adding steps or delays for legitimate users, preserving conversion rates
- Automated alerts and case management tools that reduce manual review volume and streamline fraud investigation