Payment Transaction Classification Model for Real-Time Authorization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing payment systems require real-time authorization from consumers, which can be time-consuming and inconvenient, especially for recurring transactions or transactions conducted in person.
Innovation Solution
A system and method for real-time automatic authorization of payment transactions that uses a payment transaction classification model generated from transaction data and biometric data, allowing for independent authorization without consumer input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time consumer authorization is required for payment transactions, then transaction security is improved, but transaction processing time increases
Solution Approach 1:
The system performs preliminary actions by collecting biometric data and transaction history data before the actual payment transaction occurs. A payment transaction classification model is trained in advance using this historical data, enabling the system to predict and authorize transactions automatically without requiring real-time consumer input, thus resolving the contradiction between security and processing time
Solution Approach 2:
The system enables self-service authorization by using the consumer's own biometric data and transaction patterns to automatically determine whether to authorize a payment. The classification model serves itself by learning from historical data and making authorization decisions independently, eliminating the need for manual consumer authorization while maintaining security
2Measurement precision
If manual consumer authorization is required for each payment transaction, then authorization accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The system replaces the mechanical process of manual consumer authorization with an automated electronic classification model. The model uses biometric data and transaction history to automatically determine authorization, substituting the manual mechanical process with an electronic system that maintains accuracy while dramatically improving ease of operation
Solution Approach 2:
The system changes the parameters used for authorization from manual consumer input to automated biometric and transactional parameters. By using biometric data (such as blood sugar levels) and transaction history as input parameters for the classification model, the system maintains authorization accuracy while eliminating the operational burden on consumers
3Ease of operation
If pre-authorization is used for recurring payments, then transaction convenience is improved, but flexibility deteriorates
Solution Approach 1:
The system introduces dynamics by continuously monitoring biometric data and transaction patterns to adaptively adjust authorization decisions. Rather than using static pre-authorization rules, the classification model dynamically evaluates each transaction based on current biometric state and historical patterns, providing both convenience and flexibility to cancel or modify transactions as needed
Data Source
AI summary
Provided is a computer-implemented method for real-time automatic authorization of a payment transaction that is independent of an authorization input from a consumer. The method may include receiving first data associated with a consumer, generating a payment transaction classification model based on the first data associated with the consumer, receiving second data associated with the consumer, determining whether to process a payment transaction in real-time between the consumer and a merchant independent of an authorization input received from the consumer using the payment transaction classification model and the second data associated with the consumer, and processing a payment transaction between the consumer and the merchant based on determining to process the payment transaction in real-time between the consumer and the merchant.