Transaction Classification at Point of Sale Using Class Code Manager
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Solution Overview
Problem
Managing and organizing payment transaction records across different merchants and payment processors is challenging due to varying names, categories, and descriptions, leading to inefficiencies in record-keeping and analysis.
Innovation Solution
A computerized method and system that collects transaction class codes at the point-of-sale (POS) interface, using a class code manager to prompt users for class codes during transactions, and employs machine learning to generate suggested class codes, enhancing accuracy and reducing resource usage by integrating class code collection with the transaction initiation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If transaction records are kept without standardized class codes, then merchants and payment processors can use their own names and categories, but transaction organization and analysis become challenging and inefficient
Solution Approach 1:
The patent introduces a standardized transaction class code as an intermediary element between the diverse merchant/payment processor naming systems and the user's account organization needs. The class code manager assigns standardized codes (e.g., 101 for groceries, 102 for dining) that mediate the translation from various merchant names into a unified classification system, enabling efficient organization without constraining merchant naming flexibility
Solution Approach 2:
The system transforms the unstructured parameter of merchant names and categories into structured transaction class codes. By changing the parameter representation from free-text names to standardized numerical or alphanumeric codes, the system enables efficient sorting, filtering, and analysis of transactions while maintaining the ability to accommodate diverse merchant identities
2Measurement precision
If class code collection is integrated into the POS interface during transaction initiation, then classification accuracy improves, but the transaction process requires additional user input
Solution Approach 1:
The system performs preliminary classification by presenting suggested transaction class codes to the user during the transaction initiation process at the POS interface. Rather than requiring post-transaction classification, the system proactively prompts users to select or confirm a class code at the point of sale, ensuring accurate classification is established before the transaction is finalized
Solution Approach 2:
The class code manager enables users to self-assign transaction class codes through the POS interface. Users can review suggested codes based on merchant information and independently select the appropriate classification, reducing the need for manual intervention or post-processing while maintaining high classification accuracy
3Measurement precision
If machine learning is used to generate suggested class codes, then classification accuracy improves, but computation costs increase
Solution Approach 1:
Instead of using machine learning to definitively classify every transaction, the system applies partial action by generating only suggested class codes that are presented to users for confirmation. The ML model provides probabilistic suggestions rather than deterministic classifications, reducing computation resources while maintaining improved accuracy through user verification
Solution Approach 2:
The machine learning model serves as an intermediary that generates suggested class codes rather than making final classification decisions. The ML suggestions act as a bridge between raw transaction data and user confirmation, providing high-quality recommendations that reduce the computational burden of exhaustive analysis while maintaining accuracy through selective user validation
Data Source
AI summary
The disclosure herein describes collecting transaction class codes of transactions at a POS interface and organizing those transactions based on the class codes. A class code manager receives a notification that a transaction associated with an account has been initiated. The class code manager sends a prompt to collect a transaction class code of the transaction. In some examples, the transaction class code is a code from a plurality of transaction class codes associated with the account. A transaction class code is received in response to the prompt and the received transaction class code is associated with the transaction. A transaction record of the transaction is recorded by the class code manager, including the associated transaction class code and transaction data of the transaction. The recorded class codes of transactions are used to organize and analyze transaction data. Further, suggested class codes are generated using machine learning in some examples.