Transaction Data Enrichment via Browser Click Context
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Solution Overview
Problem
Transaction data often lacks sufficient contextual information about merchants, making it difficult for customers to identify transactions and potentially leading to fraud and increased customer service inquiries.
Innovation Solution
A system that enhances transaction data by incorporating click or browsing data, using a dynamic graphical user interface to match merchant transaction data with merchant browsing data by analyzing timestamps, user identification data, and URL information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional transaction data is used, then the system remains simple and easy to process, but the merchant identification accuracy is insufficient and customers cannot recognize transactions
Solution Approach 1:
The patent combines traditional transaction data with additional contextual data elements including merchant category code, merchant location, and browsing behavior data into a unified enhanced transaction data structure. This merging allows the system to maintain processing simplicity while significantly improving merchant identification accuracy by leveraging multiple data sources that work together to provide comprehensive merchant information.
Solution Approach 2:
The system performs preliminary actions by pre-processing and enriching transaction data with contextual information before the actual identification process. Merchant category codes, locations, and browsing patterns are prepared and associated with transactions in advance, enabling accurate merchant recognition without adding complexity during the critical identification moment.
2Loss of information
If more contextual data is added to transaction records, then customer ability to recognize transactions improves, but the amount of data processing and storage requirements increase
Solution Approach 1:
The patent applies local quality by selectively adding contextual data elements only where they provide the most value for merchant identification. Rather than uniformly expanding all transaction records, the system enhances data locally at key points such as adding merchant category codes and location information only to transactions where these elements improve recognition, thereby minimizing unnecessary data volume while maximizing information utility.
Solution Approach 2:
The enhanced transaction data structure is designed with multi-functionality, where added contextual elements serve multiple purposes: merchant identification, fraud detection, customer recognition, and analytics. This universal approach allows the same data enhancement to address multiple needs simultaneously, reducing the net increase in data volume required compared to separate systems for each function.
3Reliability
If click data is used to enhance transaction data, then fraud detection capability improves, but the complexity of matching and verifying data increases
Solution Approach 1:
The patent segments the data matching process into distinct, manageable stages: first matching transaction data with browsing data, then verifying against merchant category codes and locations. This segmentation breaks down the complex fraud detection task into smaller, more manageable comparisons, reducing the perceived complexity while maintaining comprehensive fraud detection capability through systematic verification at each stage.
Data Source
AI summary
A system may receive, via a web browser plugin on a user device, a first timestamp associated with first click data at a website associated with a merchant, a referring uniform resource location (URL), a current URL, and first user identification data. The system may also receive transaction data including a second timestamp, second user identification data, and a first merchant name associated with a transaction with the merchant. The system may determine whether the first timestamp is within a predetermined period of the second timestamp and determine whether the first user identification data corresponds with the second user identification data. When the system determines that the first timestamp is within the predetermined period of the second timestamp and the first user identification data corresponds with the second user identification data, the system may store the referring URL and the current URL with the first merchant name in a database.