Self-Service POS Fraud Detection via Action and Input Matching
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Solution Overview
Problem
Full self-service POS terminals in retail stores are vulnerable to fraudulent activities by customers, necessitating the development of techniques to prevent such acts.
Innovation Solution
A monitoring apparatus connected to a camera and point-of-sale terminal that recognizes customer actions and input operations, detects fraudulent acts, and outputs alerts to the attendant terminal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a full self-service POS terminal is implemented, then personnel expenses are reduced and infection control is improved, but the system becomes vulnerable to fraudulent activities by customers
Solution Approach 1:
The patent introduces a monitoring apparatus as an intermediary system between the customer and the POS terminal. This apparatus includes a camera that captures images of the customer's actions and a processor that analyzes these images to detect fraudulent behavior. The monitoring apparatus acts as a mediator that provides fraud detection capabilities without requiring additional human personnel at the terminal, thus maintaining the self-service model while addressing security concerns
Solution Approach 2:
The patent replaces the mechanical system of human supervision with an automated image recognition system. Instead of having personnel physically monitor customers at the POS terminal, the system uses cameras to capture images and a processor to automatically analyze these images for fraudulent actions. This substitution eliminates the need for human personnel while providing continuous fraud detection capability
2Productivity
If a full self-service POS terminal is implemented, then personnel expenses are reduced, but the system requires additional monitoring equipment to detect fraud
Solution Approach 1:
The monitoring apparatus is designed to perform multiple functions using a single integrated system. The camera captures images that are used for both security monitoring and fraud detection purposes. The processor analyzes the captured images to identify various types of fraudulent behaviors including product swapping, theft, and improper scanning. This multi-functional approach consolidates what could be multiple separate systems into one unified apparatus, reducing overall complexity
Solution Approach 2:
The monitoring apparatus operates autonomously without requiring human intervention. The camera automatically captures images of customer actions, and the processor independently analyzes these images to detect fraudulent behavior. The system generates alerts automatically when fraud is detected, eliminating the need for human operators to manually monitor each transaction. This self-service operation minimizes the complexity of human-machine interaction while maintaining effective fraud prevention
3Reliability
If real-time fraud detection is implemented, then fraudulent transactions are reduced, but the system requires continuous image analysis which increases processing load
Solution Approach 1:
The system performs preliminary actions by capturing and storing images of customer actions during the transaction process. These images are captured in real-time as the customer interacts with the POS terminal, preparing the data for subsequent analysis. The system pre-processes the images by identifying key features and actions, so that when fraud detection is needed, the analysis can be performed more efficiently on pre-processed data rather than raw images
Solution Approach 2:
The monitoring apparatus is designed to quickly analyze images and detect fraudulent actions without delaying the customer's transaction. The processor uses efficient algorithms that can rapidly identify fraudulent behavior patterns in the captured images. When fraud is detected, the system immediately generates an alert and can interrupt the transaction, skipping unnecessary processing steps to respond quickly. This rushing through of critical detection processes ensures real-time fraud prevention while minimizing overall processing time
Data Source
AI summary
A monitoring apparatus includes a camera interface, a terminal interface, a communication interface, and a processor. The processor is configured to recognize actions of a settler at a point-of-sale terminal based on images from a camera, recognize input operations performed at the point-of-sale terminal by the settler based on information from the point-of-sale terminal and detect fraudulent acts based on a recognized action and a recognized input operation at the point-of-sale terminal. The processor outputs a fraud detection image corresponding to a detected fraudulent act to at least one of the point-of-sale terminal and an attendant terminal.