Privacy-Preserving Consumer Scoring via Data Segmentation
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Solution Overview
Problem
There is a need to generate behavioral scores for consumers based on transaction data while maintaining their privacy, as existing methods often compromise personal information and violate regulations.
Innovation Solution
A system and method involving multiple computing systems where consumer characteristics are encrypted and disguised to prevent personal identification, allowing for the generation of behavior prediction scores without revealing personally identifiable information, by using one-way encryption and mapping encrypted account identifiers across systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If entities gather detailed consumer information including transaction data, then they can better target advertisements and understand consumer behavior, but consumer privacy is compromised and regulatory requirements are violated
Solution Approach 1:
The system segments consumer data processing across multiple computing systems: a first computing system holds encrypted account identifiers and consumer characteristics, while a second computing system holds transaction data. This segmentation ensures no single system possesses both personally identifiable information and transaction data, preventing privacy violations while enabling behavioral analysis through coordinated processing.
Solution Approach 2:
The patent introduces encrypted account identifiers as an intermediary element that bridges the gap between consumer identification and transaction data. These encrypted identifiers allow the system to link consumer characteristics with transaction behavior without exposing actual consumer identities, thus maintaining privacy while enabling targeted advertising and behavioral scoring.
2Measurement precision
If consumer characteristics are kept in plain form for accurate scoring, then behavior prediction accuracy is improved, but personally identifiable information is exposed
Solution Approach 1:
The system changes the parameter state of consumer characteristics by applying encryption transformations. Consumer characteristics are stored and processed in encrypted forms (e.g., hashed account identifiers, encrypted demographic data) that preserve the statistical and behavioral patterns needed for accurate scoring while eliminating personally identifiable information. The encryption parameters are chosen to maintain data utility for behavioral analysis while ensuring privacy protection.
Data Source
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AI summary
A method for maintaining consumer privacy in behavioral scoring includes a first computing system and a second computing system. The first computing system disguises consumer characteristics and maps disguised consumer characteristics to unencrypted account identifiers, and then transmits the data to the second computing system. The second computing system encrypts the account identifiers upon receipt, and maps the encrypted account identifiers to anonymous transaction data. The second computing system uses the transaction data to calculate consumer behavioral scores, and then generates a scoring algorithm that uses disguised consumer characteristics to calculate consumer behavior scores based on the calculated consumer behavioral scores and corresponding disguised consumer characteristics. The generated algorithm is then returned to the first computing system, with the second computing system not receiving any unencrypted account identifiers, any undisguised consumer characteristics, or any personally identifiable information