Recurring Transaction Management via Named Entity Classification

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Solution Overview

Problem

The management of recurring transactions is challenging due to the lack of a standard protocol or format in transaction data, leading to noisy data and intense computing resources required for analysis, especially in organizations with numerous subscription-based transactions.

Innovation Solution

A system that classifies named entities and determines recurring transactions by processing unstructured data to reduce processing resources, using a computing server to identify and predict upcoming transactions, and provide transaction recommendations to optimize resource usage.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If complex rules are applied to analyze unstructured transaction data to identify recurring transactions, then measurement precision is improved, but use of energy increases and productivity decreases

Engineering Contradiction:

Improveaccuracy of recurring transaction detectionVSAvoidcomputing resources consumed

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary actions by pre-processing transaction data to extract and store key features such as merchant names, transaction amounts, and timestamps in a structured format before analysis. This pre-extraction of relevant information reduces the complexity of subsequent pattern matching and reduces computing resources needed during actual recurring transaction detection

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary layer that transforms unstructured transaction data into a standardized structured format with extracted features. This intermediary representation serves as a bridge between raw data and analysis algorithms, enabling more efficient processing while maintaining measurement precision through consistent data normalization

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If complex rules are applied to analyze unstructured transaction data to identify recurring transactions, then measurement precision is improved, but productivity decreases

Engineering Contradiction:

Improveaccuracy of recurring transaction detectionVSAvoidtransaction processing speed

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The analysis process is segmented into distinct stages: data extraction, feature normalization, pattern matching, and validation. Each stage processes only relevant information with optimized algorithms appropriate to that specific task, improving overall processing speed while maintaining accuracy through specialized handling at each step

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Transaction data is pre-processed to extract and normalize key features before the main analysis routine. This preliminary structuring of data including standardizing merchant names and categorizing transaction types enables faster pattern matching and reduces the computational burden during peak processing times

Inventive Principle:

Principle #10Preliminary action

3Device complexity

If unstructured transaction data is processed without classification to detect recurring transactions, then device complexity is reduced, but loss of information increases

Engineering Contradiction:

Improveprocessing system simplicityVSAvoidtransaction data structure information

Core Design Contradiction:

Device complexityVSLoss of information

Solution Approach 1:

The system extracts key information elements from unstructured transaction data including merchant identifiers, transaction amounts, dates, and categories. By separating and storing these critical features in a structured format, the system preserves essential information while simplifying the overall processing architecture through focused data representation

Inventive Principle:

Principle #2Taking out (Extraction)

4Measurement precision

If comprehensive analysis of all transactions is performed to identify recurring patterns, then measurement precision is improved, but loss of time increases

Engineering Contradiction:

Improveaccuracy of subscription transaction identificationVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs partial analysis by focusing computational resources on transactions that exhibit characteristics of recurring patterns based on initial filtering criteria. Rather than analyzing every transaction equally, the system applies targeted analysis to suspicious or likely recurring transactions, achieving sufficient precision while reducing overall processing time

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS20240428325A1User interface for recurring transaction management

Publication Date: 2024.12.26 RAMP BUSINESS CORP

AI summary

A system for detects and manages recurring transactions incurred by members of a client organization. The system includes a computing server that is configured to classify named entities into a category of transacting named entities. For example, the computing server classifies a list of named entities that offer subscription services and hence, create recurring transactions with the client organization. The computing server receives transaction data and determines that a target transacting named entity extracted from the received data belongs to the category (e.g., there is a named entity in the received transaction data that has sold a service to the client organization more than once). The computing server may then determine the presence and frequency of a subscription transaction series in the received transaction data, and cause a predicted a timing of an upcoming transaction in the subscription transaction series to be displayed in a graphical user interface (GUI).