Automated Transaction Review System Consolidating Customer Data
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Solution Overview
Problem
The manual review of transactions for fraud detection is a time-consuming and tedious process, prone to human error due to the need for manual gathering and organization of customer information from various sources, which can lead to inefficient decision-making in accepting or declining transactions.
Innovation Solution
A request processing system generates a consolidated view of customer information, including personal and transaction history data, to provide a streamlined review process, allowing automated verification and scoring to determine the likelihood of transaction authenticity, thereby facilitating quick and accurate decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual review process is used to verify customer information and transaction history, then accuracy of fraud detection can be maintained through human judgment, but the time required for review increases significantly and productivity decreases
Solution Approach 1:
The patent introduces an automated review system that acts as an intermediary between the transaction data and the reviewer. This system automatically gathers customer information, retrieves transaction history, consolidates data from multiple sources, and presents it in a structured format. The intermediary handles the tedious data collection and organization tasks, allowing the reviewer to focus on analysis and decision-making, thereby improving both speed and accuracy.
Solution Approach 2:
The system performs preliminary actions by automatically collecting and organizing all necessary customer information and transaction history before the reviewer begins their analysis. This pre-processing includes retrieving data from multiple external sources, verifying customer identity information, and consolidating transaction patterns. By completing these preparatory tasks automatically, the system reduces the time reviewers need to spend on data gathering while ensuring comprehensive information is available for accurate fraud detection.
2Loss of information
If manual gathering of information from various sources is performed, then complete customer profile can be obtained, but the complexity of the review process increases and human error increases
Solution Approach 1:
The patent merges multiple information sources and data types into a single consolidated customer profile. The system automatically retrieves customer information from internal databases and external sources, combines transaction history data, device fingerprint information, and identity verification data. This consolidation presents a unified view of the customer, ensuring completeness of information while reducing the complexity of manually navigating multiple sources. The merged data structure eliminates the need for reviewers to separately access and cross-reference multiple systems.
3Reliability
If comprehensive customer information and transaction history are reviewed, then fraud detection accuracy improves, but the time required for information gathering and organization increases
Solution Approach 1:
The review system performs self-service by automatically gathering, verifying, and organizing customer information and transaction history without requiring manual intervention for data collection. The system autonomously queries internal databases and external sources, retrieves customer profiles, verifies identity information, and consolidates transaction patterns. This automation eliminates the time-consuming manual data gathering process while ensuring comprehensive information is collected for accurate fraud detection, as the system systematically covers all necessary data sources.
Data Source
AI summary
Techniques for reviewing transaction information are provided. A reviewer computer can review transactions that are marked for review by a resource provider. The reviewer computer can review the transaction based on user information obtained from third party servers. The reviewer computer can also review the transaction based on historical transaction information obtained from a history database. The reviewer computer can aggregated the user information and the historical transaction information in order to generated a consolidated view.