Stale Interaction Notification System for Fraud Risk Assessment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Historical fraud detection methods are inadequate due to reliance on incomplete information and limited notifications, failing to provide comprehensive risk assessments and relevant information to entities involved in interactions.
Innovation Solution
A system and method for determining address risk scores using machine learning models to predict fraud based on historical data and generating notifications for stale interactions and safety alerts, incorporating push notifications and other communication methods to inform entities of potential fraud and safety concerns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive information is used for risk determination, then risk score accuracy is improved, but information collection complexity increases
Solution Approach 1:
The system collects comprehensive information about users (address, device identifiers, interaction history) in advance and stores it in databases before risk assessment is needed. This preliminary data collection and organization enables accurate risk scoring without adding complexity at the moment of interaction.
Solution Approach 2:
The patent introduces intermediary components including address risk models, device risk models, and interaction risk models that process raw data and transform it into meaningful risk scores. These intermediary models act as mediators between comprehensive data collection and final risk determination, simplifying the overall system architecture.
2Device complexity
If simple notifications are used for interactions, then notification system complexity is reduced, but information completeness deteriorates
Solution Approach 1:
The notification system dynamically adapts its complexity based on interaction risk levels. For low-risk interactions, simple confirmations are used. For high-risk or stale interactions, the system automatically generates comprehensive notifications including fraud warnings, safety alerts, and detailed interaction information, optimizing both simplicity and completeness.
Solution Approach 2:
The patent changes notification parameters (content, timing, delivery method) based on interaction characteristics such as risk score, interaction type, and user preferences. This parameter-based adaptation allows the system to provide complete information when needed while maintaining simplicity for routine interactions.
Data Source
AI summary
A method of transmitting a stale notification using one or more processors, comprising: receiving data about an interaction involving a user device, the data including a predefined period of time based on a complexity of the interaction; detecting no user inputs for the predefined period of time; and transmitting a notification to the user device indicating that the interaction is stale.