Automated Payment Detection in Communication Apps
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Solution Overview
Problem
There is a need for an automated process to facilitate digital payments between individuals, as manual reimbursement processes often result in forgotten payments, leading to inefficiencies in transaction handling.
Innovation Solution
A system that monitors communication applications on user devices to identify payment-related activities, determines the parties involved, and automatically processes payments or invoices based on user approval, utilizing natural language processing and machine learning to analyze communications and user patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual reimbursement processes are used, then people can conduct transactions with friends and peers, but payments are often forgotten leading to inefficiencies
Solution Approach 1:
The system performs preliminary actions by monitoring communications and automatically identifying payment obligations before the user forgets. The system proactively detects payment scenarios from chat applications, identifies parties involved, and prepares payment processing in advance, preventing the common problem of forgotten reimbursements.
Solution Approach 2:
The system enables self-service by automatically monitoring user communications, identifying payment scenarios, determining involved parties, and processing payments without requiring manual user intervention. The system serves itself by using the user's own communication data to trigger and complete payment transactions autonomously.
2Productivity
If automated payment determination is implemented, then payment processing efficiency is enhanced, but the system requires monitoring and analyzing communication applications
Solution Approach 1:
The system achieves multi-functionality by integrating multiple capabilities into a single platform: monitoring communication applications, analyzing text for payment scenarios, identifying parties involved, calculating payment amounts, and processing transactions. This universal approach handles diverse communication formats (chat messages, emails, social media) through a unified analysis framework.
Solution Approach 2:
The system introduces an intermediary layer between communication applications and payment processing. This mediator monitors communications without requiring direct integration with each application, analyzes the content to identify payment scenarios, and then triggers appropriate payment actions, thereby simplifying the overall system architecture.
3Ease of operation
If the system automatically identifies parties involved in payments, then manual information input is reduced, but natural language processing and machine learning are required
Solution Approach 1:
The system replaces manual mechanical processes (user typing and inputting party information) with automated intelligent processing. Natural language processing algorithms analyze communication text to automatically extract party identities, while machine learning models determine payment scenarios and amounts, substituting human cognitive effort with computational intelligence.
Data Source
AI summary
A computer system monitors one or more communication applications on a device of a user. The computer system identifies a communication that corresponds to a payment from a plurality of communications on the one or more communication applications. In response to the identifying the communication that corresponds to the payment, the computer system automatically identifying one or more other users associated with the payment without prompting the user for information.