SBO Identification Network Host System for Transaction Data Categorization
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Solution Overview
Problem
Current data analytics systems face challenges in accurately identifying and categorizing transaction data, particularly when cardholders use business-oriented transaction cards for consumer transactions or vice versa, leading to confusion and obscuration of real-world entities and individuals, which hampers data analysis and credit risk assessment.
Innovation Solution
A SBO identification network host system that includes a decisioning engine to compute a Small Business Owner (SBO) score and assign an SBO tag based on a methodology using data elements such as demographics, transaction history, and credit reports, enabling the identification of SBOs and facilitating cross-selling opportunities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional transaction card systems are used without SBO identification, then cardholders can use cards for both consumer and business transactions, but accurate identification and categorization of transaction data becomes confused and frustrated
Solution Approach 1:
The patent segments cardholders into distinct categories (SBOs and non-SBOs) based on multiple data elements including transaction patterns, demographics, and credit information. This segmentation enables precise identification and categorization of transaction data by assigning specific tags to individual cardholders, thereby resolving the confusion in data classification without requiring complex manual intervention.
Solution Approach 2:
The system changes the parameter of cardholder identification from a binary consumer/business card distinction to a multi-dimensional profile based on transaction patterns, demographic data, credit inquiries, and spending behavior. This parameter transformation enables more accurate identification of SBOs even when they use consumer-oriented cards, improving measurement precision while maintaining system manageability.
2Adaptability or versatility
If business-oriented transaction cards are used for consumer transactions or vice versa, then cardholders have flexibility in card usage, but the identity and categorization of real-world entities behind transactions becomes obscured
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring transaction patterns, credit inquiries, and spending behavior to dynamically update SBO probability scores and tags. This feedback loop ensures that even when cardholders use cards flexibly across different transaction types, the system maintains accurate entity identity classification by adapting to changing behavioral patterns and re-categorizing cardholders as needed.
Solution Approach 2:
The patent introduces an intermediary SBO identification system that sits between the transaction card and the underlying entity. This intermediary layer analyzes multiple data sources including transaction history, credit reports, and demographic information to infer the true nature of the cardholder, thereby preserving entity identity clarity even when the card type does not directly indicate business or consumer usage.
3Measurement precision
If multiple data elements are analyzed to compute SBO scores, then identification accuracy improves, but data processing complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing key data elements such as credit inquiry counts, transaction pattern classifications, and demographic profiles before SBO score computation is needed. This preliminary processing organizes raw data into structured formats that can be quickly evaluated during SBO score calculation, thereby improving identification accuracy while reducing the computational complexity during the actual scoring process.
Data Source
AI summary
Systems and methods of improving the operation of a transaction network and transaction network devices is disclosed. A SBO identification network host may comprise various modules and engines as discussed herein wherein the probability that a cardholder is a small business owner may be evaluated for establishing proper usage of differentiated transaction instruments according to their proper purposes, marketing and cross-marketing of differentiated transaction instruments, and provision of value-added services. For instance, a probable SBO may be identified, whereby the SBO identification network network may tailor the handling of the transactions, such as by denying them, whereby the transaction network may actively deter misuse of transaction products, or tailor the handling of electronically delivered advertisements, such as by targeting them, whereby the SBO identification network more properly functions according to approved parameters.