Dynamic Trust Scoring for Low-Friction Authentication Requests
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Solution Overview
Problem
Conventional authentication systems are inefficient and prone to false positives, leading to increased transactional costs and decreased user satisfaction due to fraudulent authentication action requests.
Innovation Solution
A method for dynamic trust score determination using machine learning models to evaluate authentication action requests, incorporating device trust scores and authentication action request metadata to generate trust scores, and provide authentication action responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional authentication systems are used to evaluate authentication requests, then security verification is performed, but false positives occur and user satisfaction decreases
Solution Approach 1:
The system dynamically changes authentication parameters by computing risk scores based on multiple factors including device characteristics, location data, behavioral patterns, and request metadata. This allows the authentication system to adapt its stringency based on the computed risk level, reducing false positives for low-risk requests while maintaining security for high-risk requests
Solution Approach 2:
The authentication system transitions from static verification to dynamic risk-based authentication. The risk score is computed in real-time based on current device state, historical behavior, and request context, allowing the system to adjust authentication requirements dynamically rather than applying uniform verification to all requests
2Reliability
If conventional authentication systems prompt users for additional authorization operations, then security is maintained, but transactional costs increase
Solution Approach 1:
The system applies partial authentication actions based on risk level. For low-risk requests, minimal or no additional authorization is required. For high-risk requests, full multi-factor authentication is applied. This partial action approach reduces unnecessary authentication overhead and transactional costs while maintaining security where needed
3Reliability
If conventional authentication systems evaluate all authentication requests with the same process, then consistent security is provided, but authentication efficiency decreases
Solution Approach 1:
The authentication system segments requests into different risk categories based on computed risk scores. Low-risk requests follow an expedited approval path, medium-risk requests undergo additional verification, and high-risk requests require full multi-factor authentication. This segmentation maintains security consistency through risk-appropriate verification while significantly improving efficiency for the majority of low-risk requests
Data Source
AI summary
Methods, apparatuses, and computer program products are provided for dynamically determining a trust score for an authentication action request. An example method includes receiving an authentication action request from a user device. The method further includes determining a device trust score associated with the user device and generating an action trust score for the authentication action request based at least in part on the device trust score. The method further includes providing an authentication action response to the user device based at least in part on the trust score for the authentication request. The authentication action request metadata may include one or more of event data, user device information, location data, user biometric information, user device interaction information.