LLM-Based Financial Transaction System with Pre-Authorization
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Solution Overview
Problem
Current electronic financial transaction systems face challenges in real-time surcharge calculation and payment security, particularly with ACH transactions, which can be delayed and result in unpredictable fees for consumers, and lack the ability to securely process tips at restaurants.
Innovation Solution
A multimodal financial transaction system utilizing a Large Language Model (LLM) operating system with integrated payment processing modules for various payment methods and a Generative AI module for interactive communication, along with fraud prevention mechanisms, to analyze multimodal data and facilitate secure, real-time transactions across diverse channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ACH transactions are used for electronic payments, then payment processing is enabled, but transaction finalization is delayed taking days to process
Solution Approach 1:
The system performs pre-authorization charges on credit cards before ACH transactions are initiated. This preliminary action secures the payment in advance, allowing the merchant to have confidence in the transaction while the ACH process completes in the background, effectively reducing the perceived processing time delay.
Solution Approach 2:
The system introduces a credit card pre-authorization mechanism as an intermediary between the merchant and the ACH transaction. This intermediary provides immediate payment assurance while the slower ACH transaction processes in the background, resolving the time delay issue without compromising the reliability of ACH processing.
2Measurement precision
If real-time surcharge calculation is implemented, then consumer fee transparency is improved, but system complexity increases
Solution Approach 1:
The system automatically calculates and applies the appropriate surcharges based on pre-configured payment method rules. The processing system self-determines the correct fee structure without requiring manual intervention or complex user-side calculations, maintaining precision while managing complexity through automated rule-based processing.
Solution Approach 2:
The system pre-configures surcharge rules and payment method hierarchies before transactions occur. By establishing these rules in advance, the system can perform accurate real-time surcharge calculations without complex on-the-fly decision-making, reducing processing complexity while maintaining measurement precision.
3Adaptability or versatility
If multiple payment processing modules are integrated, then payment versatility is improved, but device complexity increases
Solution Approach 1:
The system implements a universal payment processing architecture where a single integrated platform handles multiple payment methods (credit card, debit card, ACH, mobile payments) through standardized modules. This multi-functional design allows diverse payment processing capabilities while managing complexity through unified architectural patterns and shared infrastructure.
Solution Approach 2:
The payment processing system is divided into separate, modular components for different payment methods. Each module (credit card processing, ACH processing, mobile payment processing) operates independently but interfaces through a common framework, allowing versatility across payment types while reducing overall system complexity through clear separation of concerns.
4Reliability
If pre-authorization charges are applied, then payment security is improved, but consumer responsibility for fees increases
Solution Approach 1:
The system provides clear feedback to consumers about pre-authorization charges and subsequent ACH transaction status. By communicating the relationship between the pre-authorization and the final ACH processing, the system helps consumers understand when fees are applied and when they are waived, reducing unexpected fee burdens while maintaining security.
Solution Approach 2:
The pre-authorization charge acts as a cushion that covers potential failures of the ACH transaction. If the ACH transaction fails, the pre-authorized amount is already in place to cover the loss. This beforehand cushioning protects both the merchant and consumer while managing fee expectations through transparent communication about when and why charges are applied.
Data Source
AI summary
A method for conducting multimodal financial transactions is disclosed. The method includes a. analyzing a context window using a Large Language Model (LLM) based operating system to identify multimodal triggers; b. selecting an appropriate payment processing module from a plurality of modules, each associated with different payment methods, based on the identified multimodal triggers; c. initiating a financial transaction utilizing the selected payment processing module; and d. facilitating diverse channels of input and output between the LLM-based operating system and a user through a plurality of modalities.