Delegate Notification Scheme for Fraud Intervention Timing
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Solution Overview
Problem
Vulnerable individuals, such as the elderly, are often targeted in fraudulent transactions and lack the time to seek input from trusted advisors due to high-stress situations designed to encourage impulsive decisions.
Innovation Solution
A delegate notification scheme is implemented that triggers notifications to trusted advisors based on predefined alert events, using fraud models to determine the need for intervention and prioritize message transmission to delegates, allowing them to approve, reject, or flag transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a delegate notification scheme is implemented to engage trusted advisors in fraudulent transaction prevention, then the reliability of transaction decisions is improved, but the device complexity and processing time increase
Solution Approach 1:
The system segments the fraud prevention process by creating separate modules: a fraud model that analyzes transaction data independently, a notification system that contacts delegates separately, and a response processing component. This segmentation allows each component to specialize in one function, improving overall reliability while managing complexity through modular design.
Solution Approach 2:
The system performs preliminary fraud analysis using machine learning models before transactions are completed. By pre-assessing fraud risk and proactively notifying delegates of potential issues, the system prevents fraudulent transactions before they cause harm, rather than reacting after the fact.
2Measurement precision
If fraud models and trigger events are used to determine when to notify delegates, then the precision of intervention timing is improved, but the loss of time for vulnerable users to complete transactions increases
Solution Approach 1:
The system changes parameters dynamically by adjusting notification thresholds and delegate engagement levels based on fraud risk scores. For low-risk transactions, the system uses higher thresholds and minimal notification, while for high-risk transactions, it lowers thresholds and engages delegates more aggressively, optimizing the balance between precision and speed.
Solution Approach 2:
The system applies partial notification based on fraud risk levels. For transactions with moderate risk, only specific trigger events trigger delegate notifications, while for high-risk transactions, multiple triggers and higher-level delegates are engaged. This partial action approach prevents unnecessary delays for low-risk transactions while maintaining precision for high-risk ones.
3Reliability
If multiple delegates are notified simultaneously for high-priority transactions, then the reliability of fraud prevention is improved, but the loss of time for obtaining delegate responses increases
Solution Approach 1:
The system dynamically adjusts the notification strategy based on transaction priority and fraud risk. For high-priority transactions, multiple delegates are notified simultaneously to ensure comprehensive review. For lower-priority transactions, the system uses sequential notification or single-delegate approaches. This dynamic adaptation optimizes reliability for critical cases while minimizing time loss for routine transactions.
Solution Approach 2:
The system implements feedback loops where delegate responses and transaction outcomes are continuously monitored. This feedback informs future notification decisions, allowing the system to learn which notification patterns yield the best fraud prevention results with minimal time loss, progressively optimizing the balance between reliability and speed.
Data Source
AI summary
Systems and methods may generally include creating a notification scheme for alerting delegates for a user. An example method includes creating a data store including one or more delegates associated with one or more intervention alert trigger events. Transaction data may be received and based on the transaction data and the trigger events, one or more triggered events may be determined. Based on the triggered events(s), notification messages may be transmitted to one or more particular delegates and response message(s) may be received. In some examples, priority data may be received setting how individual delegates receives notifications or setting how notification messages are transmitted to multiple delegates associated with the same triggered event.