Real-Time Payment Risk Scoring via Hybrid In-Flight and Offline Models
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Solution Overview
Problem
Current payment card transaction systems face challenges in providing timely and comprehensive risk information, leading to significant losses due to fraud and false-positive declines, with existing solutions being account-and issuer-oriented, failing to detect cross-account fraud and credit risk effectively.
Innovation Solution
A real-time transaction processing system that generates and utilizes risk scores, reason codes, and condition codes to provide informed authorization decisions, incorporating a hybrid approach with in-flight and offline models for risk evaluation, and linkage detection to mitigate payment card risks across multiple accounts and issuers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time risk evaluation is implemented across multiple accounts and issuers, then fraud detection capability is improved, but system complexity increases
Solution Approach 1:
The system divides the risk evaluation function into separate modules: in-flight model component for real-time authorization requests, offline model component for batch processing, and linkage detection component for pattern recognition. This segmentation allows complex multi-account fraud detection to be achieved through coordinated simple components, resolving the contradiction between comprehensive fraud detection and system complexity.
Solution Approach 2:
The patent introduces a transaction monitoring system as an intermediary that collects data from multiple accounts and issuers, processes it through various model components, and generates risk scores. This intermediary layer enables comprehensive fraud detection across the payment ecosystem without requiring direct complex interactions between all system components, thus managing system complexity while improving reliability.
2Measurement precision
If comprehensive risk information is provided for all transactions, then authorization decision quality is improved, but processing time increases
Solution Approach 1:
The system performs preliminary risk assessment by generating risk scores, reason codes, and condition codes during the authorization process itself (in-flight processing). Historical data and patterns are pre-analyzed by the offline model component, so that when a transaction requires evaluation, the comprehensive risk information is already prepared or can be quickly generated, maintaining both decision quality and processing speed.
Solution Approach 2:
The patent implements a tiered approach where not all transactions receive the same level of analysis. The system provides comprehensive risk information only when necessary (e.g., when risk indicators are present or transactions meet certain criteria), while allowing low-risk transactions to proceed with standard processing. This partial action approach maintains authorization decision quality for problematic transactions without unnecessarily increasing processing time for all transactions.
3Reliability
If real-time risk scores and condition codes are generated for each transaction, then risk mitigation effectiveness is improved, but computational resources consumed increases
Solution Approach 1:
The system applies different levels of computational analysis to different transactions based on their risk characteristics. The in-flight model component generates risk scores using streamlined calculations for routine transactions, while the linkage detection component applies more intensive analysis only when patterns suggest potential fraud. This local quality approach ensures effective risk mitigation for problematic transactions while conserving computational resources for standard transactions.
Solution Approach 2:
The patent dynamically adjusts the complexity of risk evaluation based on transaction parameters such as amount, merchant type, location, and account history. When parameters indicate low risk, the system uses simplified evaluation with minimal computational resources. When parameters suggest potential risk, the system activates more comprehensive analysis including linkage detection across multiple accounts. This parameter-driven adaptation maintains risk mitigation effectiveness while optimizing computational resource usage.
Data Source
AI summary
A system for providing real-time risk mitigation for an authorization system. The system receives authorization requests from multiple merchants (or their respective acquirers) and processes such requests. Each processed request is then forwarded to its corresponding issuer for further authorization. Each processed request includes an authorization message. The authorization message can include a risk score, a number of reason codes, and a number of condition codes. The use of the risk score, reason codes and condition codes allows issuers to make better informed decisions with respect to providing authorizations.