Payment Card OCR and 3D Verification for Fraud-Resistant Entry
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Solution Overview
Problem
Consumers face difficulties entering credit card information on mobile devices due to small screen sizes and cumbersome keyboard interfaces, leading to errors and increased vulnerability to fraud during mobile payments.
Innovation Solution
A character recognition system that uses optical character recognition (OCR) and computer vision to generate 3D models of payment instruments, eliminating the need for manual input by capturing images from multiple angles and comparing them to stored data for verification and fraud detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual credit card information entry is used on mobile devices, then payment processing can be performed, but the process becomes cumbersome and error-prone due to small screen sizes and keyboard interface limitations
Solution Approach 1:
The patent replaces the mechanical manual entry process (typing on keyboard) with an optical recognition system using camera-based image capture and OCR technology. The system captures images of the payment instrument and automatically extracts card information through optical character recognition, eliminating the need for manual typing and significantly improving ease of operation while reducing entry time
Solution Approach 2:
The system creates a digital copy of the payment instrument information by capturing an image of the physical card and extracting data through OCR. This digital copy is then used for payment processing, replacing the need for manual transcription of card details and enabling automatic information retrieval
2Reliability
If manual credit card information entry is used on mobile devices, then payment processing can be performed, but vulnerability to fraud increases due to potential errors and security risks
Solution Approach 1:
The system implements verification feedback mechanisms by comparing the extracted card information against stored reference data and validating the captured images. The system can verify that the correct payment instrument is being used by comparing real-time image data with previously stored card images, providing a feedback loop that enhances security and reduces fraud vulnerability
Solution Approach 2:
The system performs preliminary verification of the payment instrument by capturing and analyzing images before processing the payment. By pre-validating the card information and comparing it against stored data, the system prevents fraudulent transactions before they occur, rather than reacting to fraud after it happens
3Adaptability or versatility
If multiple payment instruments need to be processed, then payment versatility is improved, but the complexity of information entry and processing increases significantly
Solution Approach 1:
The system implements a universal image capture and processing workflow that handles multiple types of payment instruments (credit cards, debit cards, stored value cards) through the same OCR-based extraction process. This multi-functional approach allows the system to process various card types without requiring separate manual entry procedures for each, thereby improving versatility while keeping the processing mechanism relatively simple and consistent
Data Source
AI summary
Techniques described herein are directed to generation and use of a system that allows a payment service to read payment objects, onboard users, and detect fraud using data from the payment objects. The systems and methods may include receiving instructions to obtain images of a payment instrument and generating data representing those images, which may include a 3D model of the payment instrument. A comparison of the generated data and previously stored data may be performed and the results of this comparison may be utilized to determine a likelihood that a fraudulent event is occurring with respect to the payment instrument.