POS Merchant Data Enrichment for Clear Transaction Records
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Solution Overview
Problem
Merchant business names and associated data received from point-of-sale payment processors are often confusing and unintelligible, making it difficult for issuers' customers, service center agents, and data analysts to understand where money is spent.
Innovation Solution
A system and method that includes data normalization, enrichment, and output of transaction records by a computer program, utilizing techniques such as string distance matching, decision trees with natural language processing, and a rules engine to identify and enhance merchant information in transaction data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If raw merchant data is used directly from point-of-sale processors, then data processing is simple and fast, but the merchant information is confusing and unintelligible
Solution Approach 1:
The system performs preliminary data normalization on merchant fields before identification and enrichment processes. This includes standardizing formats, removing duplicates, and preparing data structures in advance, which reduces processing complexity during subsequent operations while ensuring information clarity.
Solution Approach 2:
The patent introduces an intermediary enrichment process that acts as a mediator between raw merchant data and final presentation. This intermediary layer adds contextual information, standardizes formats, and bridges the gap between raw data and intelligible information without requiring complete restructuring of the underlying system.
2Loss of information
If data normalization and enrichment processes are applied to merchant fields, then merchant information clarity is improved, but processing time and computational resources increase
Solution Approach 1:
The system applies partial normalization and enrichment only to the specific merchant fields that require clarification, rather than processing entire transaction records. This selective approach applies data normalization techniques to relevant portions of the data, reducing overall processing time while still improving merchant information clarity where needed.
Solution Approach 2:
The patent changes data parameters by transforming merchant field formats from raw processor formats to standardized, human-readable formats. This includes modifying string representations, standardizing address formats, and converting numerical codes into descriptive information, which improves clarity without requiring complete reprocessing of all transaction data.
3Measurement precision
If multiple identification methods are used to identify merchants, then identification accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the merchant identification process into distinct methodological components, each handling specific aspects of identification. Rather than using a single complex algorithm, the system divides identification into multiple targeted approaches that can be applied independently to different data scenarios, improving accuracy while managing complexity through modular design.
Data Source
AI summary
Systems and methods for s enhancing point of sale information are disclosed. In one embodiment, a method may include: (1) receiving, by a computer program, raw transaction data for a transaction, the transaction data comprising merchant fields, wherein the raw transaction data comprises payment card data for a payment card that was received at a point-of-sale device during a transaction between a customer and a merchant; (2) performing, by the computer program, data normalization on the merchant fields; (3) identifying, by the computer program, the merchant for the transaction based on one or more of the merchant fields; (4) enriching, by the computer program, a transaction record for the transaction with information for the merchant; and (5) outputting, by the computer program, the transaction record.