Authorized Views for Privacy Preservation in Payment Data Sharing
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Solution Overview
Problem
Data sharing between entities is challenging due to privacy and security concerns, particularly when sharing personally identifiable information (PII). Existing methods often require the sharing of PII, which is undesirable due to privacy and security risks.
Innovation Solution
The implementation of a data service that enables 'authorized views' for privacy preservation, allowing service providers to share data without exposing PII. This is achieved by using a centralized data storage that provides temporary access permissions, enabling service providers to access data while maintaining the security and privacy of PII.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is shared between service providers, then data sharing capability is improved, but privacy and security risks increase due to PII exposure
Solution Approach 1:
A data service acts as an intermediary between service providers, enabling data sharing without direct PII exposure. The data service receives datasets from providers, processes them to remove or abstract PII, and returns sanitized data for analysis while maintaining privacy and security
Solution Approach 2:
The system extracts and removes personally identifiable information from datasets before sharing. PII is identified, separated, and either removed entirely or replaced with abstracted representations, allowing data sharing while eliminating the harmful exposure of sensitive information
2Loss of information
If PII is shared for data analysis, then data utility is improved, but security and privacy are worsened
Solution Approach 1:
The system creates a sanitized copy of the dataset for analysis purposes. The copy contains the same analytical value but with PII removed or abstracted, allowing data utility to be maintained while security and privacy are protected from direct exposure
3Loss of information
If full datasets are transmitted for analysis, then data completeness is improved, but computing resources are consumed due to large data transmission
Solution Approach 1:
The system extracts only the necessary analytical data from full datasets, removing PII and redundant information. This allows transmission of minimal required data while maintaining data completeness for analysis purposes, significantly reducing computing resource consumption
Data Source
AI summary
Techniques described herein include providing personal data of users of a payment service to a data service when such users have granted sharing permissions. Then, a query may be configured to determine which of the users are eligible for a promotion from a third party service. The query may be sent to a data service and a query result may be received from the data service based on the third party service provisioning a temporary viewing permission to the payment service. Eligible promotions may be presented to individual users based on the query results.