Transaction Fraud Screening with Data Obfuscation and Risk Modules
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Solution Overview
Problem
In the context of financial transactions, especially in banking, there is a challenge in balancing security and privacy needs, as existing systems often require excessive information sharing, which can compromise user privacy and expose sensitive data, while also struggling to effectively detect fraudulent activities.
Innovation Solution
A transactional system comprising a risk module and an obfuscation module that negotiates between security and privacy needs by uncovering only necessary risk-relevant data for assessment, requesting user consent, and aborting transactions if excessive information is required, thereby protecting customer data and ensuring fraud detection without data exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If extensive information is transferred to service providers for fraud detection, then fraud detection capability is improved, but user privacy is compromised
Solution Approach 1:
The patent extracts only the essential risk-relevant data from transactions for fraud detection, separating necessary security information from unnecessary personal data. The risk module identifies and transmits only specific risk indicators (such as transaction amount, frequency, and pattern anomalies) while leaving out sensitive personal information, thus achieving fraud detection without comprehensive data exposure.
Solution Approach 2:
The patent applies different levels of data sharing to different aspects of transaction information. Sensitive personal data is protected with higher privacy levels while risk-relevant transaction characteristics are shared with service providers. This localized differentiation allows the system to maintain privacy for personal identifiers while still providing sufficient information for effective fraud detection.
2Measurement precision
If comprehensive transaction data is shared with multiple banks and service providers, then fraud detection accuracy is improved, but data exposure risk increases
Solution Approach 1:
The patent introduces a risk module as an intermediary between the banking system and service providers. This module processes transaction data locally, identifies risk indicators, and transmits only these processed risk signals to service providers and other banks. The intermediary prevents raw personal data from being exposed while still enabling collaborative fraud detection through shared risk information.
Solution Approach 2:
The patent creates simplified copies of transaction data that contain risk indicators but exclude sensitive personal information. Instead of sharing actual customer data, the system generates abstracted representations that preserve fraud detection capabilities while eliminating privacy risks. These copies can be safely shared across multiple institutions without exposing real customer identities.
3Measurement precision
If more information is uncovered for risk assessment, then risk assessment quality is improved, but privacy protection is weakened
Solution Approach 1:
The patent applies partial action by uncovering only the necessary portion of transaction information required for risk assessment. The risk module selectively identifies and transmits specific risk-relevant data points (such as transaction patterns, amounts, and frequencies) without exposing complete customer profiles. This partial information sharing achieves sufficient risk assessment quality while maintaining privacy protection for unnecessary data.
Data Source
AI summary
Methods, computer program products, and systems are presented. The methods include customer specific information exchange and an adjustment of the privacy level of this information. For this purpose an abstraction layer and an obfuscation module are introduced. Using a “fraud vector” a risk assessment is performed on the obfuscated transaction data.