Agentic fraud intelligence platform that unifies signals across the fraud ecosystem to detect threats faster, automate investigations and improve accuracy
Overview
Fraud attacks evolve in minutes. Your response must too.
IBM Cyber Fraud is the fraud intelligence layer that unifies signals across fraud, AML, security and operational systems to create a single detection and investigation workflow. Using AI-driven orchestration, it helps teams investigate faster, automate routine actions and continuously improve fraud detection outcomes.
Accelerate fraud investigations
Modern fraud investigations require analysts to manually connect data across multiple systems, creating delays and inconsistent outcomes. IBM Cyber Fraud unifies signals across the fraud ecosystem, automatically reconstructs attack patterns and delivers investigation-ready intelligence that enables faster, more accurate decisions at scale.
Features
AI-powered fraud investigation
IBM Cyber Fraud unifies fraud, payment, identity and security signals into a single investigation workflow. With AI-powered orchestration, it correlates events, surfaces relevant insights, automates routine actions and learns continuously from investigator activity to improve outcomes.
Accelerate fraud investigations to reduce losses and operational costs with AI‑driven, end‑to‑end automation.
A unified, single-pane experience that brings together data from all connected systems and enables natural language interaction—no switching between tools required.
Train the system to learn from investigator behavior. It learns, adapts and acts autonomously on routine cases—freeing analysts for high‑value work.
Every alert arrives pre‑enriched with cross‑system context—device risk, transaction history, identity signals and threat intelligence—all in a single view.
Unified intelligence from Trusteer, Safer Payments, QRadar® and third‑party systems delivers new insights and accelerates resolution.
AI-driven integration connects IBM and non-IBM solutions without forced data centralization. Onboard in days, not months.
One pane of glass delivering cross‑system insights and enabling natural language investigation—built for analysts, not data scientists.
An adaptable investigation agent that adjusts to your specific fraud typologies, workflows and business rules.
Minimize data usage and eliminate the risk and complexity of moving data to a single location.
Integrations
Built to integrate. Built to scale.
IBM Cyber Fraud offers native integration with Trusteer and Safer Payments and open connectors to your existing fraud and security ecosystem. No forced data centralization. No disruptive migration.
| Native IBM integrations | Deployment principles |
|---|---|
| Trusteer (device and session risk) | No data centralization required |
| Safer Payments (transaction monitoring) | Interoperability by design |
| QRadar (security monitoring) | Rapid extension and onboarding |
| FTM (financial transaction management) | Flexible deployment (cloud and on-premises) |
| MaaS360® (device and endpoint visibility) | No rip-and-replace of existing stack |
IBM Trusteer for device and session risk
Trusteer® continuously assesses digital channels for device integrity and session behavior to identify and pinpoint scams, mules, account takeover and device takeover attempts. It does this analysis before a user logs in or the transaction ever reaches your core systems.
Key signals:
- Device risk posture and fingerprinting
- Malware and RAT detection
- Behavioral biometrics and session anomalies
IBM Safer Payments for transaction monitoring
Safer Payments delivers real-time payment fraud detection with machine learning models that adapt to your transaction patterns. It monitors every payment channel—card, ACH, wire and instant payments—with sub-millisecond decisioning.
Key capabilities:
- Real-time transaction scoring across all channels
- Adaptive ML models with low false-positive rates
- Coverage across key payment fraud typologies (APP, CNP and ATO)
Resources
Resources
Can AI detect fraud in milliseconds? Martin Keen and Jeff Crume dive into how an ensemble of AI models combines predictive machine learning and encoder LLMs to transform fraud detection. See how structured and unstructured data power precise, real‑time decisions.