Rule-Based Identity Requests for Low-Friction Account Access
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Solution Overview
Problem
Existing systems require users to create digital accounts and provide personal information to access services, which is cumbersome and prone to errors, and enterprises must secure and verify this information, creating a legal obligation.
Innovation Solution
An enterprise computing platform uses rule-based security identification to leverage previous user interactions with the enterprise and third parties, generating a dynamic identity data request based on calculated risk metrics to create an account and grant access to services without requiring users to set up a digital account or provide personal information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users create digital accounts and provide personal information to access services, then access control and security are improved, but user friction and complexity increase
Solution Approach 1:
The system enables self-service authentication by automatically identifying users through their devices and previous interactions with the enterprise organization. Instead of manually creating accounts or providing personal information, users are automatically recognized and granted access based on their device identity and interaction history, eliminating the need for manual account setup while maintaining security through automated verification processes
Solution Approach 2:
The system introduces an intermediary authentication mechanism that uses device-based identification and previous interaction records as mediators between the user and the service. Rather than direct user-provided credentials, the system uses device identifiers and interaction logs as intermediate verification elements to establish identity and grant access, reducing user friction while maintaining security
2Reliability
If enterprises request personal information from users, then account security and verification are improved, but data security obligations and complexity increase
Solution Approach 1:
The system extracts the authentication function from user-provided personal information and relocates it to device-based identification and automatic verification processes. By taking out the dependency on user-supplied credentials and personal data, the system reduces enterprise data security obligations while maintaining verification reliability through automated device-based authentication and interaction history analysis
Solution Approach 2:
The system replaces the mechanical process of manually collecting and verifying personal information with an automated electronic verification system. Instead of processing user-provided credentials and personal data, the system uses automated device identification, interaction log analysis, and rule-based verification algorithms to establish identity and grant access, reducing data security complexity while maintaining verification effectiveness
3Ease of operation
If enterprises use previous user interactions for authentication, then user friction is reduced, but security risk assessment complexity increases
Solution Approach 1:
The system changes the authentication parameters from user-provided personal information to device-based identifiers and interaction patterns. By parameterizing authentication through device IDs, interaction timestamps, and interaction types rather than personal data, the system reduces user friction while managing security risk assessment complexity through structured analysis of interaction parameters and automated risk evaluation rules
Data Source
AI summary
A method is provided. The method comprises: receiving user information comprising one or more identifiers associated with a user, wherein the one or more identifiers indicates a phone number associated with a user device; based on the user information, querying an internal data management system and an external data management system to determine previous interactions of the user; determining one or more calculated risk metrics associated with the user based on comparing the first previous interactions and the second previous interactions with one or more thresholds; generating a dynamic identity data request for the user based on the one or more calculated risk metrics; in response to providing the dynamic identity request to the user device, receiving, from the user device, dynamic identity data for the user; based on the dynamic identity data, authorizing the user access to one or more services.


