Receipt OCR Item-Level Transaction Data With Corporate Entity Mapping
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Solution Overview
Problem
Consumers lack access to detailed transaction item-level data, as financial institutions and merchant systems often only provide summary-level information, making it difficult to track spending accurately and make informed purchasing decisions based on corporate entities associated with products.
Innovation Solution
A system that utilizes an account server to request line item data from merchants and processes receipt images using image analysis techniques to extract detailed transaction information, including product names, corporate entities, and additional details such as warranty and return policies, which are then stored and displayed to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If summary-level transaction information is provided by financial institutions and merchant systems, then system complexity is reduced and data processing is simplified, but consumers cannot access detailed item-level data needed for informed purchasing decisions
Solution Approach 1:
The patent introduces an intermediary system (financial institution's processing system) that mediates between merchant systems and consumer devices. This intermediary aggregates detailed item-level transaction data from multiple merchants and makes it accessible to consumers through mobile devices, thereby reducing the information loss without requiring consumers to directly interface with complex merchant systems.
Solution Approach 2:
The system creates digital copies of transaction receipts and item-level data that can be viewed on consumer mobile devices. Instead of requiring consumers to access original merchant systems, the patent generates and transmits copies of transaction information including itemized details, corporate entities, and product categories, enabling informed decision-making without increasing system complexity.
2Loss of information
If detailed item-level data including corporate entity information is collected and stored, then consumers can make informed purchasing decisions, but data storage requirements and processing loads increase
Solution Approach 1:
The patent extracts and isolates specific high-value information elements (item-level data, corporate entities, product categories) from complete transaction records. By selectively extracting only the essential information needed for informed purchasing decisions rather than storing and transmitting entire transaction datasets, the system reduces data storage requirements while preventing information loss.
Solution Approach 2:
The transaction data is segmented into hierarchical levels: transaction-level summaries, item-level details, corporate entity information, and product category data. This segmentation allows the system to store and process only the necessary granularity of information at each level, reducing overall data storage requirements while ensuring consumers access the specific detailed information they need.
3Loss of information
If consumers access detailed transaction histories through mobile devices, then spending transparency is enhanced, but network data transmission requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and formatting transaction data on the financial institution's server before transmission to consumer devices. Item-level data, corporate entity information, and product categories are aggregated, validated, and structured in advance, reducing the need for subsequent data processing and minimizing network transmission requirements when consumers access their transaction histories.
Data Source
AI summary
Systems, methods, apparatuses, and computer-readable media are provided for determining individual item-level details associated with a transaction. A plurality of purchase transactions associated with different merchants may be displayed via a user interface. Responsive to a user selection of a first transaction, of the plurality of transactions, a camera may capture an image of at least a portion of a user receipt associated with the first transaction. The image of the user receipt may be analyzed using one or more optical character recognition (OCR) algorithms to convert the image of the user receipt into textual data. One or more character strings associated with line item-level details may be extracted from the textual data associated with the first transaction. Additional information associated with the line item details may be determined and the line item details and the additional information may be displayed via a user interface.