What data points are essential for building a passkey intelligence engine?

A passkey intelligence engine requires specific data points to optimize authentication flows and provide a seamless user experience. Here are the essential data types:

• Operating System and Browser: Identify the user’s OS and browser version to ensure compatibility with passkeys.
• Hardware Capabilities: Detect device features like biometric sensors, Bluetooth support, and LocalStorage availability.

• Existing Passkeys: Track registered passkeys, their locations (e.g., local device, cloud-synced), and cross-device availability.
• Authentication History: Log successful and failed login attempts to understand patterns and improve decision-making.

• Interaction Trends: Monitor how users interact with passkey prompts, including time to authenticate and frequency of errors.
• Fallback Usage: Record instances where fallback options, such as passwords or OTPs, are utilized instead of passkeys.

• Network Conditions: Assess latency and connection stability to predict and mitigate potential authentication disruptions.
• Geolocation Data: Analyze location patterns to identify anomalies and improve fraud detection.

• Success Metrics: Track passkey login success rates and correlate them with specific devices, browsers, or contexts.
• User Feedback: Incorporate feedback to refine the intelligence engine and align with user expectations.

• Authenticator Details: Store authenticator-specific metadata, such as AAGUIDs, attestation type, and signature counts.
• Suspicious Behavior: Detect and log irregular authentication attempts that may indicate potential fraud.

By collecting and analyzing these data points, a passkey intelligence engine can dynamically adapt authentication flows, maximize success rates, and provide a user-centric, secure experience.