Identify fraudulent actors and prevent revenue loss
Key Capabilities
AI-based fraud detection
AI-based fraud detection
- Detect fraudulent activity in near real-time using advanced machine learning and anomaly detection techniques to prevent revenue loss and other operational risks
- Identify emerging fraud patterns and new risk typologies to improve the detection of fraudulent behavior over time
Holistic fraud monitoring
Holistic fraud monitoring
- Monitor fraud prevention performance and investigation effectiveness across configurable dashboards and KPIs
- Unify data from disparate internal and external source systems to form a 360-degree client and operational view
- Access a summary of the work queue, prioritized cases, and a geospatial view of fraudulent activity occurrences
AI recommendations and alerts
AI recommendations and alerts
- Use AI-based risk scores to prioritize investigations
- Observe automatic updates in AI model predictions and changes in behavioral patterns as new data arrive
Explainable AI and evidence packages
Explainable AI and evidence packages
- Guide field teams and increase investigation effectiveness via interpretable AI outputs and evidence packages
- Provide closed-loop feedback to enable AI models to improve over time and identify new patterns
End-to-end workflow support
End-to-end workflow support
- Manage investigations with comprehensive workflow support that enables assignment, collaboration, escalation, and investigation auditing
- Configure and track KPIs by fraud modes
- Streamline the investigation process by integrating with external systems and pushing AI-based insights into workflows
Scope
C3 AI Fraud Detection addresses a wide range of use cases in the utilities, healthcare, financial services, and many other industries.
Use cases
Energy theft
Insurance fraud
Identity theft
Employee misconduct
Tax evasion
Industries
Utilities
Healthcare
Financial Services
E-commerce
Public Sector
Benefits for C3 AI Fraud Detection Users
Fraud Investigators
Quickly identify and act on the emerging risks to prevent revenue loss using the unified data, fraud analytics, and intelligent visualizations of customer activity.
Fraud Managers
Prioritize suspicious activity and mobilize investigation teams. Review operational performance, detect potential loss, optimize investigation assignments, and track investigation outcomes.
Data and Architecture
