Fraud Detection System Using Consumer Authentication Data
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Solution Overview
Problem
Current transaction risk assessment systems are inadequate for real-time fraud detection in card not present transactions, as they rely on data from transaction authorization requests and fail to utilize additional information that could indicate fraudulent activity, leading to delayed detection and increased processing resources and potential losses.
Innovation Solution
A system that processes consumer authentication data from card not present transactions to generate fraud detection rules, providing an early warning to issuers about potentially fraudulent transactions by analyzing characteristics of previous transactions, allowing for real-time evaluation and prevention of fraudulent activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional transaction risk assessment systems are used, then transaction processing can proceed, but fraud detection is delayed and processing resources are increased
Solution Approach 1:
The system performs fraud assessment before transaction authorization by analyzing authentication data from the authentication process. This preliminary fraud evaluation occurs prior to the authorization request, enabling early detection of fraudulent transactions and preventing unnecessary processing of high-risk transactions.
Solution Approach 2:
The fraud detection system is separated from the traditional authorization system. It independently analyzes authentication data and generates fraud assessments that are then integrated with authorization decisions. This segmentation allows fraud detection to operate in parallel with authentication, improving detection timing without interfering with the core authorization process.
2Reliability
If traditional transaction risk assessment systems are used, then transaction processing continues, but data processing resources are increased and losses occur
Solution Approach 1:
The system performs fraud assessment before transaction authorization by analyzing authentication data from the authentication process. This preliminary fraud evaluation occurs prior to the authorization request, enabling early detection of fraudulent transactions and preventing unnecessary processing of high-risk transactions.
Solution Approach 2:
The system extracts and analyzes only the authentication data from the authentication process, separating this fraud-relevant information from the complete transaction data. By focusing analysis on specific authentication characteristics rather than processing all transaction data, the system reduces computational resources required while maintaining effective fraud detection.
3Productivity
If fraud detection is performed later in processing, then standard authorization流程 is maintained, but potential losses increase
Solution Approach 1:
The system performs fraud assessment before transaction authorization by analyzing authentication data from the authentication process. This preliminary fraud evaluation occurs prior to the authorization request, enabling early detection of fraudulent transactions and preventing unnecessary processing of high-risk transactions.
Solution Approach 2:
The system takes preliminary anti-action by identifying and flagging fraudulent transactions before they can cause financial loss. By detecting fraud patterns in authentication data early in the process, the system prevents fraudulent transactions from proceeding to authorization and settlement, thereby protecting against potential losses.
Data Source
AI summary
A system, apparatus, and method for reducing fraud in payment or other transactions by providing issuers with a warning that a transaction being processed for authorization is potentially fraudulent. In some embodiments, the present invention processes data obtained from a consumer authentication process that is used in card not present (CNP) transactions to determine characteristics or indicia of fraud from previous transactions. The characteristics or indicia of fraud can be used to generate a set of fraud detection rules or another form of fraud assessment model. A proposed transaction can then be evaluated for potential fraud using the fraud assessment model.


