Variable Risk Engine for Online Transaction Fraud Detection
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Solution Overview
Problem
Current risk assessment systems are inadequate in providing real-time and time-delayed risk analysis, especially in online transactions, as they fail to accommodate varying session types and transaction complexities, leading to inefficiencies in fraud detection and identity verification.
Innovation Solution
A variable risk engine system that performs both real-time and time-delayed risk assessments, allowing for flexible risk analysis based on predetermined time limits and test prioritization, adaptable to different transaction types and security levels, ensuring continuous risk evaluation throughout the transaction lifecycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time risk analysis is performed for all transactions, then fraud detection capability is improved, but processing time and system complexity increase
Solution Approach 1:
The risk analysis system is segmented into multiple categories (real-time, near-real-time, delayed, and batch processing) based on transaction risk profiles and time sensitivity. This allows different transactions to be processed at appropriate speeds, improving overall system efficiency while maintaining fraud detection capability for high-risk transactions.
Solution Approach 2:
The system dynamically adjusts the amount and type of risk analysis performed based on transaction characteristics, user behavior patterns, and risk indicators. High-risk transactions receive comprehensive real-time analysis, while low-risk transactions undergo minimal or delayed analysis, optimizing processing time while maintaining security.
2Measurement precision
If comprehensive risk analysis is performed, then risk assessment accuracy is improved, but system complexity and resource consumption increase
Solution Approach 1:
Different levels of risk analysis are applied to different transactions based on their specific characteristics and risk profiles. Not all transactions receive the same comprehensive analysis; instead, the system applies appropriate analysis depth locally to each transaction type, reducing overall system complexity while maintaining accuracy where needed.
Solution Approach 2:
The system changes parameters such as analysis depth, processing time, and data collection intensity based on transaction risk indicators. This allows the system to maintain high assessment accuracy for suspicious transactions while using fewer resources for routine transactions, effectively managing system complexity.
3Reliability
If real-time risk analysis is set to high amount, then security level is improved, but transaction processing speed decreases
Solution Approach 1:
The system performs partial risk analysis in real-time for most transactions, reserving comprehensive analysis for cases where risk indicators suggest it is necessary. This partial action approach maintains security levels by catching obvious fraud while preserving transaction processing speed for legitimate users.
4Adaptability or versatility
If multiple risk assessment categories are implemented, then adaptability to different transaction types is improved, but system complexity increases
Solution Approach 1:
The risk analysis system is designed as a universal multi-functional platform that can handle different transaction types, time sensitivity levels, and risk profiles through a single integrated architecture. This universality allows the system to adapt to various transaction scenarios without requiring separate specialized systems, effectively managing complexity while maintaining versatility.
Data Source
AI summary
The invention provides systems and methods for risk assessment using a variable risk engine. A method for risk assessment may comprise setting an amount of real-time risk analysis for an online transaction, performing the amount of real-time risk analysis based on the set amount, and performing an amount of time-delayed risk analysis. In some embodiments, the amount of real-time risk analysis may depend on a predetermined period of time for completion of the real-time risk analysis. In other embodiments, the amount of real-time risk analysis may depend on selected tests to be completed during the real-time risk analysis.