Federated Associate Identifier for Cross-Domain Identity Resolution
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Solution Overview
Problem
Current systems face challenges in positively identifying business associates across multiple domains and applications with different identifiers, leading to incomplete and inaccurate monitoring results due to manual intervention and incomplete, outdated, or inaccurate associate data.
Innovation Solution
An automated method and system that determines if an associate accessing one domain/application using an application-specific identifier is the same associate accessing another domain/application, generating a unique federated identifier to positively identify the associate across all domains, eliminating the need for manual analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual intervention is used to positively identify associates across different domains, then identification accuracy can be improved, but productivity and time consumption deteriorate due to painstaking manual analysis
Solution Approach 1:
The patent replaces the manual mechanical analysis process with an automated computer-based system that uses data matching algorithms to positively identify associates across different domains. The system automatically compares associate identifiers, names, and other data fields between systems of record, eliminating the need for manual painstaking analysis while maintaining identification accuracy.
Solution Approach 2:
The system enables self-service automated identification by having the computer system autonomously perform data correlation and associate matching across multiple business applications. The automated process independently analyzes data from different systems of record, generates matches, and creates federated identifiers without requiring human intervention, thereby improving productivity while maintaining accuracy.
2Reliability
If manual analysis is performed to correlate associate data, then identification reliability can be improved, but time consumption increases significantly
Solution Approach 1:
The patent substitutes manual analysis with an automated computer-based system that reliably correlates associate data across different domains. The system uses structured data matching algorithms that consistently apply identification criteria, eliminating human error and variability while maintaining high identification reliability. This automated approach dramatically reduces the time required compared to manual analysis.
Solution Approach 2:
The system performs preliminary automated data correlation and preliminary identification matching before final positive identification is required. By pre-processing and pre-matching associate data across systems of record, the system prepares identification results in advance, reducing both time consumption and maintaining reliability when actual identification decisions are needed.
3Adaptability or versatility
If multiple application-specific identifiers are used across different business applications, then adaptability of the system is improved, but the complexity of identifying the same associate across applications increases
Solution Approach 1:
The patent implements a universal federated identifier that functions across multiple different business applications and domains. The system creates this universal identifier by correlating application-specific identifiers from different systems of record, enabling the same associate to be reliably identified across diverse applications. This maintains system adaptability while reducing identification complexity through standardization.
Solution Approach 2:
The system introduces a federated identifier as an intermediary that bridges multiple application-specific identifiers. This intermediary identifier serves as a common reference point that simplifies the identification process across different domains, reducing the complexity of directly correlating multiple disparate identifiers while preserving system adaptability to various business applications.
4Measurement precision
If data from multiple systems of record is analyzed manually, then measurement precision can be improved, but the loss of time increases due to data field length and system configuration differences
Solution Approach 1:
The patent replaces manual data analysis with an automated computer-based system that precisely matches data fields across different systems of record. The automated system handles variations in data field lengths and system configurations through programmed data normalization and comparison algorithms, maintaining measurement precision while dramatically reducing the time required to analyze and correlate associate data across multiple sources.
Data Source
AI summary
Methods, apparatus, systems and computer program products are described and claimed that provide for automatically and positively determining that an associate accessing a business domain/application using an application-specific associate identifier is the same associate that is accessing another business domain/application using another application-specific associate identifier. Once the positive determination of same associate is made, a federated identifier key is generated and applied to all of the platforms in which the associate can be positively identified, so as to globally identify the associates across multiple enterprise-wide domains/applications. As such, the present invention eliminates the need to manually analyze associate data to determine if an associate interfacing with one domain/application is the same associate interfacing with another domain/application.