Dynamic Fraud Detection System for Stored-Value Cards
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Solution Overview
Problem
Existing systems lack effective methods to dynamically detect and prevent consumer fraud, particularly in digital transactions using stored-value cards, which are vulnerable to unauthorized use and fraudulent activities by internet bots (BOTs).
Innovation Solution
A system comprising a non-transitory memory, a processor, and an application that communicates with a data store to analyze requests associated with stored-value cards. The system determines if the requesting party is approved to use the card based on risk scores, banned lists, and artifact analysis, allowing or denying transactions accordingly and updating profiles and lists dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fraud checks are performed prior to selling goods, then fraud prevention is improved, but transaction processing time increases
Solution Approach 1:
The system performs preliminary fraud detection actions by analyzing artifacts and risk scores before the transaction is completed. The fraud check is conducted in advance using stored profile data and risk assessments, allowing the system to determine approval status prior to final transaction processing.
Solution Approach 2:
The system uses feedback from previous transactions and artifact analysis to dynamically update risk scores and profiles. This feedback mechanism allows the system to learn from past behavior and adjust fraud detection thresholds, improving accuracy while reducing unnecessary delays in transaction processing.
2Measurement precision
If dynamic profile updates are performed, then fraud detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system implements dynamic profile updates where risk scores and fraud indicators are continuously adjusted based on new transaction data and artifact analysis. This dynamic approach allows the system to adapt to changing fraud patterns while maintaining a manageable structure through automated updates.
Solution Approach 2:
The system performs self-service updates by automatically analyzing transaction artifacts, updating profiles, and adjusting risk scores without requiring manual intervention. This automation reduces the operational complexity of maintaining accurate fraud detection systems while improving detection accuracy through continuous self-optimization.
3Speed
If risk scores are analyzed in real-time, then fraud detection speed is improved, but computational resources increase
Solution Approach 1:
The system performs preliminary risk score calculations and artifact analyses before real-time transaction processing. By pre-computing risk assessments and storing profile data, the system reduces the computational burden during real-time transactions while maintaining fast fraud detection speeds.
Solution Approach 2:
The system applies partial fraud detection actions based on risk thresholds, focusing computational resources only on transactions that require detailed analysis. Low-risk transactions undergo simplified processing while high-risk transactions receive comprehensive analysis, optimizing the balance between detection speed and computational resource usage.
Data Source
AI summary
Systems and methods discussed herein relate to a system for detecting and preventing fraudulent transactions through collecting requests for website access, stored-card trades and sales, and transactions using physical or electronically issued credit, debit, stored-value, and other cards. The fraud detection system not only flags individual transactions, but is also configured to dynamically track and update banned/watch lists associated with request artifacts and cards in order to catch and prevent individual actors as well as BOTs, at least by adjusting the thresholds used to evaluate risk scores and what is placed on the banned/watch lists based upon requests received as well as information from financial institutions, merchants, government agencies, and watchdog groups. The system is also configured to provide information to those groups.