Memory-Jogging Visual Units for Fraudulent Operation Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems lack an effective method to help users recognize fraudulent computing operations in a timely and efficient manner, leading to unnecessary investigations and resource wastage.
Innovation Solution
An authorizing entity server displays a log of computing operations to users, allowing them to indicate fraudulent activities, and generates memory-jogging visual units with metadata to aid recognition, ranking them by attributes like location or entity name to facilitate user recall.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users are presented with detailed logs of computing operations to identify fraudulent activities, then the accuracy of fraud detection improves, but the time required for users to review and identify fraudulent operations increases
Solution Approach 1:
The patent segments the computing operations log into individual discrete entries, each representing a separate operation. This segmentation allows users to review operations in manageable units rather than overwhelming continuous data, improving both accuracy of identification and efficiency of review process
Solution Approach 2:
The system performs preliminary filtering and organization of computing operations before presenting them to users. Operations are pre-processed to highlight relevant information and arrange them in a logical sequence, reducing the time users need to spend on review while maintaining detection accuracy
2Reliability
If comprehensive logs of all computing operations are maintained for fraud detection, then the reliability of fraud identification improves, but the device complexity and resource requirements increase
Solution Approach 1:
The patent extracts only the essential and relevant information from computing operations logs for presentation to users. Non-essential data is excluded or summarized, maintaining fraud identification reliability while reducing system complexity and resource requirements for storing and processing comprehensive logs
Solution Approach 2:
The system creates simplified copies or representations of the original computing operations data for user review. These copies contain the critical information needed for fraud detection in a more compact and manageable format, reducing the complexity burden while preserving reliability
3Measurement precision
If users manually review computing operation logs to identify fraudulent activities, then the measurement precision of fraud detection improves, but the productivity of the fraud detection process decreases
Solution Approach 1:
The patent implements feedback mechanisms where user interactions with the log review interface provide information back to the system. This feedback enables the system to learn from user behavior, adjust the presentation of operations, and potentially automate aspects of fraud detection, thereby improving productivity while maintaining precision
Solution Approach 2:
The system dynamically adapts the presentation and filtering of computing operations based on user preferences, historical data, and detected patterns. This dynamic adjustment optimizes the review process in real-time, improving both the precision of fraud detection and the productivity of the overall process
Data Source
AI summary
A method includes displaying on a graphic user interface (GUI) of a computing device of a user, a log of computing operations performed by the user at computing terminals of entity servers respectively managed by entities. The user uses a unique authorization identifier provided by the authorizing entity to authorize the computing operations at the computing terminals of the entity servers. The user provides a fraud indication through the GUI that at least one computing operation in the log is fraudulent. Memory-jogging visual units are displayed on the GUI to the user that cause the user to recall performing the at least one computing operation identified as being fraudulent. An entry of the at least one computing operation in an operation database is marked as a valid operation authorized by the user when receiving a recognition indication and potentially fraudulent when no recognition indication by the user.