Payment Device Cloned Card Detection via Image Analysis
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Solution Overview
Problem
Current technologies do not effectively detect cloned payment cards, relying on attributes like location, transaction amount, and merchant details, which fail to identify suspicious cards, especially blank or reprogrammed cards, leading to potential fraudulent transactions.
Innovation Solution
A payment device equipped with on-board circuitry and machine learning capabilities to analyze images of payment cards in real-time, generating a characterization score to determine if a card is suspicious, and alerting financial institutions to prevent fraud.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image capture and analysis capabilities are added to the payment device, then detection capability is improved, but device complexity increases
Solution Approach 1:
The system divides the fraud detection function into separate modules: image capture device, image analysis device with machine learning models, and payment processing device. This segmentation allows each component to specialize in its function while reducing the complexity burden on any single device.
Solution Approach 2:
The patent introduces an intermediary image analysis device that acts as a bridge between the payment device and fraud detection. This intermediary handles the complex image processing and machine learning analysis, allowing the core payment device to remain relatively simple while still achieving advanced detection capabilities.
2Reliability
If real-time image analysis is performed, then fraud prevention effectiveness is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by capturing images of the payment card before the actual payment transaction occurs. The image analysis and fraud detection are completed in advance, allowing the payment process to proceed without delay if the card is verified as legitimate.
Solution Approach 2:
The patent replaces traditional mechanical fraud detection methods with optical image capture and digital machine learning analysis. This substitution enables faster, more accurate real-time analysis compared to physical inspection methods, improving both speed and accuracy of fraud detection.
Data Source
AI summary
Aspects of the disclosure relate to a payment device to detect real-time suspicious payment cards. Prior to a transaction, a payment device detects suspicious payment cards based on captured images of the payment card. An alert may be generated upon detection of any suspicious or fraudulent payment card. In some arrangements, institutions may share information regarding suspicious payment cards to prevent fraud. The payment device may utilize machine learning models or machine learning capabilities to detect suspicious payment cards. A characterization score may be generated and used to determine if a payment card is suspicious. The characterization scores may be updated based on different card issuer criteria and transaction use of each payment card.