IBM Trusteer provides a cloud‑based fraud‑prevention platform that uses AI‑driven risk scoring to evaluate web and mobile user sessions. It combines device hygiene checks, network metadata, behavioral biometrics, and transaction patterns with a global intelligence network of anonymized device fingerprints and dark‑web feeds, delivering real‑time alerts and API integration for banks, fintechs, and large enterprises.
Funding
Funding not disclosed
Founders
Product
Problem
Financial institutions and digital service providers face increasing fraud threats such as account takeover, malware‑injected overlays, and credential stuffing, which are difficult to detect with traditional rule‑based tools. These attacks span web and mobile channels and often exploit gaps in device, network, and behavioral data, leading to financial loss and regulatory risk.
Solution
IBM Trusteer delivers a unified fraud‑prevention platform that combines cloud‑based intelligence with lightweight endpoint agents for web and mobile applications. The solution continuously evaluates each user session using AI‑driven risk scoring that incorporates device hygiene checks, network provenance, behavioral biometrics, and account transaction patterns. A global intelligence network of millions of anonymized device fingerprints and dark‑web threat feeds enriches the analysis, enabling real‑time detection of anomalous activity. Results are streamed to a cloud analytics service where security teams can view actionable alerts, drill down into forensic data, and integrate decisions via APIs into existing authentication or transaction workflows. The platform scales on an agile cloud infrastructure, supporting cross‑organizational deployment and centralized policy management.
Target Audience
Primary customers are banks, digital‑only financial institutions, and fintech platforms that require continuous fraud detection across web and mobile channels. The solution also serves large enterprises and online merchants seeking to protect high‑value transactions and user accounts from credential‑based attacks.
Features
- AI/ML risk engine that fuses device attributes, network metadata, behavioral biometrics (keystroke dynamics, swipe patterns, mouse movement) and transactional data into a real‑time fraud score.
- Endpoint SDKs for web browsers and native mobile apps that perform on‑device malware, emulator, screen‑overlay, and remote‑access‑tool detection before session initiation.
- Network analysis module that identifies VPN usage, proxy locations, carrier anomalies, and call‑in‑progress signals to flag social‑engineering vectors.
- Global intelligence network leveraging a persistent fingerprint for each device, continuously updated with threat intel from dark‑web monitoring and IBM’s fraud research team.
- Cloud‑hosted analytics dashboard with configurable alerts, trend visualizations, and API endpoints for integration with identity‑verification, transaction processing, or SIEM systems.
- Scalable, multi‑tenant cloud architecture that supports unified policy enforcement across web, mobile, and account‑opening channels.
- End‑to‑end encryption and role‑based access controls to ensure compliance with data‑privacy regulations.