Question 1: Can you detect, identify, and stop synthetic identities at account creation?

New account fraud (NAF) allows fraudsters to exploit systems by creating fake accounts using stolen or synthetic identities. This can lead to abused promotions, fraudulent credit applications, and stolen funds.

• Identity Verification: Liveness detection and government ID proofing to ensure legitimate users.
• Dynamic Fraud Detection: Analysis to flag bot activity, automated registrations, and questionable patterns.
• Progressive Profiling: Collect data gradually to minimize friction while building trust.
• Customizable Orchestration: Workflows that dynamically trigger fraud checks during high-risk registrations.

Question 2: Are our defenses multi-layered to meet AI-driven threats?

Advanced identity fraud techniques, including deepfakes and malicious bots are becoming harder to detect. These methods compromise user accounts and security systems, leading to fraud and operational disruption.

• Risk-Based Authentication Policies: Adjust authentication based on device, location, and behavior.
• Adaptive MFA: Trigger additional security layers for high-risk sessions.
• Real-Time Risk Evaluation: Constantly assess session risk for step-up requirements.
• Presentation & Injection Detection: Detecting masks, screen-to-screen, and camera injection attacks.

Question 3: Can we adjust fraud detection thresholds dynamically?

Evolving attack strategies and vectors can bypass static fraud detection measures, leaving systems vulnerable. Organizations need dynamic, context-aware systems that adapt to new threats to minimize disruption and risk.

• Composite Risk Scoring: Systems that aggregate multiple risk signals in real-time.
• Real-Time Adaptability: Tools to adjust risk predictors and enforce appropriate security measures.
• Orchestration Engines: Dynamic decision-making based on combined risk predictors.
• Threat Intelligence Integration: Real-time data from global threat feeds to enhance risk scoring.

Question 4: Do we leverage adaptive authentication and real-time risk signals?

Static security measures can frustrate legitimate users and fail to block sophisticated attacks. Adaptive authentication aligns security with risk, balancing protection and convenience.

• Real-Time Risk Evaluations: Assess current sessions, devices, and network conditions in the moment.
• Step-Up Authentication: Additional authentication for medium and high-risk actions.
• Fraud & Risk Signaling: Data from multiple sources and tools that create a composite risk score.
• Immediate Response: Take action immediately in high-risk scenarios by enforcing additional security measures.

Question 5: Are our workflows designed for seamless, omnichannel CX?

A disjointed customer experience can drive churn, increase cart abandonment, and even weaken security. Fraud prevention workflows must integrate smoothly across devices and platforms to balance security and usability.

• Simple Workflow Design: Visual flow designer with drag-and-drop interfaces for building custom workflows.
• Pre-Built Templates: Connectors, APIs, and templates for common services and journey customization.
• No-Code Orchestration: Rapid deployment and adjustment of user flows across devices and platforms.
• Cross-Device Continuity: Tools to maintain session consistency across multiple devices and touchpoints.

Question 6: How do we monitor for anomalies in user behavior?

Fraudulent activity often involves changes in user behavior or device characteristics. Monitoring for anomalies helps detect and mitigate threats in milliseconds before they escalate.

• User Behavior Analytics: Tools to identify deviations from normal patterns, like navigation or typing speeds.
• Device Fingerprinting: Capabilities to detect device changes and assess risks in real time.
• Session Monitoring: Solutions to observe and respond to suspicious mid-session behavior dynamically.
• Adaptive Mitigation: Flexible workflows to escalate security measures for high-risk activity.

Question 7: Can our fraud prevention differentiate legitimate users from bad actors?

Real-time differentiation prevents automated attacks, such as account takeovers and credential stuffing, ensuring a seamless experience for genuine users.

• Bot Detection: AI-powered solutions to identify and block bot-driven activity instantly.
• Risk-Based Decisioning: Scalable tools to differentiate genuine user behavior from potential fraud attacks.
• Device & Network Intelligence: Identifies access patterns of known fraudulent devices or high-risk geolocations.
• Automated Fraud Response: Mitigation to immediately block or flag suspicious users and terminate sessions.

Question 8: Is our system scalable for future growth in users, transactions, and data?

As businesses grow, systems must handle increased traffic without compromising performance or security. Scalability is critical for long-term success.

• Elastic Infrastructure: Cloud solutions that scale automatically with user demand.
• High Availability: Systems with uptime guarantees and failover mechanisms.
• Geo-Redundancy: Distributed data centers to balance loads and ensure performance globally.
• Rate Limiting: Protections against API overload while prioritizing critical operations.

Question 9: Can our current fraud, verification, and access tools integrate seamlessly?

Orchestration with existing tools and IAM infrastructure ensures new fraud prevention capabilities complement existing systems, reducing friction and maximizing efficiency. Your identity solution must integrate seamlessly with your built environment.

• Standards Support: Compliance with open identity standards for broad interoperability.
• API and SDK Support: Resources to embed solutions into custom-built and legacy systems.
• Flexible Deployment: Options for on-premises, cloud, or hybrid environments.
• Unified Platform: Tools to consolidate and streamline multiple legacy IAM systems.

Question 10: Are our fraud prevention strategies aligned with business objectives?

Effective fraud prevention not only protects assets but also builds trust and improves efficiency. To continuously reduce operational costs and enhance your customer journey, data-driven insights are essential.

• User Analytics: Insights to optimize user journeys and reduce abandonment rates and ATO fraud.
• Behavioral Insights: Tools to identify friction points in user interactions.
• Cost Efficiency: Solutions that leverage existing investments and minimize disruptions.
• Real-Time Reporting: Dashboards to measure the impact of fraud prevention on business outcomes.