Cross-Platform Fraud Tracking With Automated Risk Scoring
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Solution Overview
Problem
Current systems for tracking fraudulent activity lack connectivity across platforms, leaving entities vulnerable to fraud and failing to provide secure access to confidential information.
Innovation Solution
An apparatus and method for tracking fraudulent activity using a user database, processor, and memory to receive identification data, generate a fraud score, and initiate security parameters, with features like facial recognition and machine learning to identify and alert potential fraud.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current tracking systems are used, then device complexity is reduced, but reliability of fraud detection deteriorates due to lack of connectivity across platforms
Solution Approach 1:
The patent merges multiple independent tracking systems into a unified platform that shares fraud data across different platforms. The system combines user profiles, identification data, and fraud risk factors from multiple sources into a centralized database, enabling cross-platform connectivity and improved fraud detection reliability without proportionally increasing complexity
Solution Approach 2:
The tracking system is designed with multi-functionality to handle various types of identification data (biometric, document-based, device identifiers) and operate across different platforms simultaneously. The system generates universal fraud scores that can be applied across multiple contexts, reducing the need for separate tracking systems for each platform
2Reliability
If comprehensive fraud detection is implemented, then security is improved, but ease of operation deteriorates due to additional security parameters
Solution Approach 1:
The system automatically performs fraud detection by comparing identification data against stored user profiles and generating fraud scores without requiring manual intervention. The automated generation of security parameters and alerts reduces the operational burden while maintaining high security standards through continuous automated monitoring
3Measurement precision
If fraud scoring is generated for all users, then measurement precision of fraud risk is improved, but loss of time increases due to processing requirements
Solution Approach 1:
The system pre-generates and stores user profiles containing baseline information during initial user interactions, so that when fraud detection is needed, the system can quickly compare current identification data against pre-prepared profiles. This preliminary data preparation reduces processing time during actual fraud detection events while maintaining assessment accuracy
Data Source
AI summary
An apparatus and method for tracking fraudulent activity that will impact financial and economic integrity, the apparatus including a user database, at least a processor, and a memory containing instructions and communicatively connected to the processor. The memory containing instructions may configure the processor to implement a method for tracking fraudulent activity that will impact financial and economic integrity. The method may include receiving one or more identification data, receiving, from the user database, a user profile associated with one or more identification data, receiving, from the user database, one or more local fraud risk factors, securely identifying an individual as a function of the score and one or more identification data, initiating one or more security parameters, and generating an alert as a function of the user profile.