Personalized Fraud Detection Rules on User Devices
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Solution Overview
Problem
Current financial transaction processing centers lack the capability to deploy and manage unique, custom fraud detection rules for individual users, as they do not possess the necessary compute power or resources to effectively manage and update rules in real-time based on user-specific needs.
Innovation Solution
Utilizing the processing power of a user's electronic device, such as a smart device, and the speed of communication networks to enable personalized fraud detection rules that are under user control, allowing for real-time customization and privacy of user data, while extending and personalizing server-based fraud detection rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If processing centers use complex fraud detection rule sets, then fraud detection capability is improved, but device complexity and computational resources required increase
Solution Approach 1:
The patent segments the fraud detection system by dividing rule sets into multiple categories (e.g., geographic rules, merchant rules, time-based rules) and organizing them in a hierarchical structure. This segmentation allows the processing center to manage complex rules in manageable segments rather than as a monolithic system, reducing operational complexity while maintaining comprehensive fraud detection coverage.
2Measurement precision
If processing centers deploy custom fraud detection rules for individual users, then fraud detection precision is improved, but computational power and resources required increase
Solution Approach 1:
The patent implements local quality by tailoring fraud detection rules to individual user characteristics, transaction patterns, and risk profiles. Each user receives customized rule sets based on their specific behavior patterns rather than applying uniform rules to all users. This approach improves detection precision for each user while allowing the system to allocate computational resources efficiently by focusing intensive processing only where needed.
Solution Approach 2:
The system applies partial action by selectively applying subsets of fraud detection rules based on transaction context and user risk profile. Rather than evaluating all possible rules for every transaction, the system dynamically determines which rules are relevant and applies only those, reducing computational overhead while maintaining detection precision for high-risk scenarios.
3Adaptability or versatility
If processing centers update fraud detection rules in real-time, then adaptability to new fraud patterns is improved, but computational resources and processing time increase
Solution Approach 1:
The patent implements preliminary action by pre-compiling and organizing fraud detection rules into categorized structures before they are needed for transaction processing. Rule sets are pre-processed, validated, and organized in hierarchical categories (geographic, merchant, time-based, etc.) so that during real-time transaction processing, the system can quickly retrieve and apply relevant rules without performing complex compilation or validation operations, thus maintaining both adaptability and processing efficiency.
4Measurement precision
If processing centers manage personalized rules for each user, then fraud detection accuracy is improved, but operational complexity and resource management increase
Solution Approach 1:
The patent implements universality by creating a multi-functional rule management system that handles multiple types of fraud detection rules (geographic, merchant, time-based, user-specific) through a unified framework. This universal system can manage diverse rule sets using common operations for creation, modification, retrieval, and deactivation, reducing operational complexity despite the diversity and personalization of individual user rule sets.
Data Source
AI summary
Detection of fraud in financial transactions is facilitated. A financial transaction is initiated by a user, and based on the financial transaction, information is obtained by an electronic device of the user. Using the information, the electronic device evaluates a set of rules personalized for the user; the set of rules to be used to determine whether the financial transaction is to be approved for the user. The electronic device provides an initial indication, based on the evaluating, of whether the financial transaction is to be approved.