Electronic Receipt Data Structuring for Banking Integration

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Solution Overview

Problem

Current systems lack the ability to effectively integrate electronic receipt data with online banking applications, limiting customers' ability to manage and analyze their purchase transactions across multiple platforms.

Innovation Solution

A system that identifies, structures, and aggregates purchase transaction data from electronic communications, allowing it to be integrated with online banking applications, providing options for recurring purchases, automatic buying, and optimizing transactions based on best prices and user preferences.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If electronic receipt data is integrated with online banking applications, then financial management capability is improved, but system complexity increases

Engineering Contradiction:

Improvefinancial management capabilityVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent employs an intermediary processing layer that receives unstructured electronic receipt data, converts it to structured format, and then integrates it with the online banking application. This mediator handles the complexity of data parsing and transformation, shielding the core banking system from direct exposure to messy external data formats while enabling enhanced financial management capabilities.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system segments the integration process into distinct functional modules: data reception module, data conversion module, data aggregation module, and analysis module. Each module handles a specific aspect of the integration, making the overall complex system manageable and maintainable while providing comprehensive financial management functionality.

Inventive Principle:

Principle #1Segmentation

2Ease of operation

If unstructured purchase transaction data is converted to structured format, then data usability is improved, but processing time increases

Engineering Contradiction:

Improvedata usabilityVSAvoidprocessing time

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system performs preliminary conversion of unstructured receipt data to structured format at the time of data ingestion, rather than waiting until the data is needed for analysis. This advance processing, while requiring initial time investment, makes the data immediately usable for subsequent financial management operations without repeated processing delays.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The conversion process transforms data from unstructured text format to structured tabular format with standardized fields (date, merchant, category, amount, etc.). This parameter change in data structure enables efficient querying, filtering, and analysis while the processing is optimized to minimize time loss through automated parsing algorithms.

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If detailed product-level data is aggregated and analyzed, then budgeting accuracy is improved, but computational resources increase

Engineering Contradiction:

Improvebudgeting accuracyVSAvoidcomputational resources

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system extracts only the essential and relevant features from detailed product-level data for budgeting analysis, such as transaction amount, date, merchant category, and payment method. By taking out only the critical parameters needed for budgeting accuracy rather than processing all available product details, the system maintains precision while reducing computational resource consumption.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system applies partial analysis to transaction data by focusing computational resources on categories and time periods most relevant to the user's budgeting needs. Rather than analyzing every single transaction detail equally, it prioritizes processing high-impact data points that most influence budgeting accuracy, using excessive computational action only where necessary.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS9519928B2Product evaluation based on electronic receipt data

Publication Date: 2016.12.13 BANK OF AMERICA CORP

AI summary

Embodiments of the invention are directed to systems, methods and computer program products for providing product evaluation. An exemplary apparatus is configured to identify purchase transaction data associated with identified electronic communications between a merchant and a customer, the purchase transaction data includes product level data from a transaction, receive the identified purchase transaction data, the purchase transaction data is received in an unstructured format, convert the purchase transaction data from the unstructured format to a structured format, associate the structured purchase transaction data with the customer's online banking application, aggregate purchase transaction data related to one or more products purchased by the customer, determine one or more products are purchased on a recurring basis, and provide the customer with one or more options based at least partially on determining the one or more products are purchased on a recurring basis.