Context Service System for Cross-Subscriber Customer Data Association
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Solution Overview
Problem
Fragmented and incomplete customer information within organizations leads to a degraded level of service, increased time and effort in providing services, and higher costs, as existing systems struggle to associate different elements of customer data without exposing sensitive information.
Innovation Solution
A context service system that generates a shared data partition to associate different elements of customer information across multiple subscribers, allowing querying to determine if a first element is associated with another known element without exposing unknown customer information, using encryption and hashing to protect sensitive data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If customer information is stored in separate organizational silos, then each organization can maintain control over its data and protect sensitive information, but the customer record becomes fragmented and incomplete, degrading service quality
Solution Approach 1:
The system segments customer information into separate data partitions maintained by different organizations, with each partition containing specific customer data elements. This allows each organization to maintain control over its own data while the system as a whole provides a complete customer view through coordinated access to multiple partitions.
2Loss of information
If customer information is shared across multiple organizations, then complete customer records can be assembled, but sensitive personally identifiable information may be exposed or disseminated
Solution Approach 1:
The system introduces an intermediary matching service that acts as a mediator between organizations. This service uses hashed identifiers and cryptographic techniques to enable cross-organization data matching without exposing sensitive personally identifiable information. The intermediary coordinates data access while maintaining privacy protections throughout the process.
3Loss of information
If traditional data matching methods are used to associate customer information, then associations can be identified, but the process requires manual intervention and increases time and effort
Solution Approach 1:
The system implements self-service automated data matching using cryptographic hash functions and probabilistic record linkage algorithms. The matching process occurs automatically without manual intervention, enabling rapid association of customer information across partitions. The system autonomously identifies matches based on hashed identifiers and data element comparisons.
4Reliability
If manual customer identification processes are used, then customer records can be retrieved, but additional information must be requested from customers and service costs increase
Solution Approach 1:
The system performs preliminary automated matching of customer information using hashed identifiers and data element comparisons before any manual intervention is needed. By pre-establishing associations between customer data elements across partitions through automated processes, the system eliminates the need for manual customer identification steps and reduces service delivery time.
Data Source
AI summary
The disclosed technology relates to a context service system configured to receive, from a subscriber, a shared customer lookup request that includes a first customer data identifier and identify, in a shared data partition, a second customer data identifier associated with the first customer data identifier. The context service system is further configured to determine that the second customer data identifier is associated with customer information in a subscriber data partition and transmit, to the subscriber system, the customer information from the subscriber data partition.