Fraud Management System Using Transaction Grouping for Cost Optimization
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Solution Overview
Problem
Current fraud screening systems face challenges in efficiently managing fraud strategies, as they struggle to accurately assess and minimize the total costs of fraud, which include false negatives, false positives, and other related costs, leading to uncertainty and resource inefficiencies, especially for large merchants in the travel industry.
Innovation Solution
A computer-implemented fraud management system that monitors and predicts the efficiency of fraud screening strategies by calculating the expected total costs of fraud, grouping transactions, and sampling fraud screenings to optimize calculations, allowing for real-time adjustments and recommendations on rule modifications to minimize costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fraud screening calculations are performed for each requested transaction individually, then measurement precision of fraud costs is improved, but response time deteriorates
Solution Approach 1:
The patent segments transactions into groups based on transaction information characteristics, and performs fraud cost calculations at the group level rather than for each individual transaction. This segmentation maintains measurement precision by ensuring homogeneous transactions within groups while dramatically reducing computational overhead and response time.
Solution Approach 2:
The system performs preliminary grouping of transactions based on their characteristics before conducting fraud cost calculations. By pre-organizing transactions into homogeneous groups, the system prepares the data structure in advance, enabling efficient batch processing and reducing the time required for actual fraud cost assessment.
2Adaptability or versatility
If fraud screening rules are adjusted ad-hoc based on disparate data, then adaptability to different fraud patterns is improved, but device complexity increases
Solution Approach 1:
The patent transforms the complex, disparate fraud data into a unified parameter framework centered on expected total costs of fraud. By changing the representation parameters from multiple disparate metrics to a consolidated cost-based parameter, the system achieves adaptability to different fraud patterns while reducing system complexity through standardized evaluation.
Solution Approach 2:
The system implements feedback mechanisms that monitor fraud screening performance and automatically adjust strategies based on observed outcomes. This feedback loop enables continuous adaptation to emerging fraud patterns while maintaining manageable system complexity through automated adjustment rather than manual rule configuration.
3Measurement precision
If total costs of fraud are calculated for every transaction, then measurement precision is improved, but productivity deteriorates
Solution Approach 1:
The patent divides the transaction stream into segments or groups based on similarity in transaction characteristics. By calculating expected total costs of fraud at the segment level rather than for each individual transaction, the system maintains measurement precision for fraud assessment while significantly improving processing throughput through reduced computational operations.
Solution Approach 2:
The system performs fraud cost calculations selectively at the group level rather than exhaustively for every single transaction. This partial action approach applies fraud cost assessment to representative samples within groups, providing sufficient measurement precision for decision-making while avoiding the excessive computational burden of individual transaction analysis.
Data Source
AI summary
The present invention relates to a computer-implemented fraud method and system for managing fraud screening in response to a requested transaction. The fraud management system checks the efficiency of the fraud screening strategy and predicts the efficiency of new fraud screening strategies based on the total cost of fraud. This calculation is facilitated, because transactions are divided into groups, and the total cost of fraud may be calculated for a representative element of the group, and not for each transaction in the group. Furthermore, if the fraud screening is based on rules that apply an acceptance flow to predetermined conditions, the fraud management can choose the best acceptance flow for these predetermined conditions by minimizing the total cost of fraud. Finally, the fraud management can also flag inefficient rules thanks to an indicator related to the total cost of fraud to highlight rules whose predetermined conditions should be changed.