Contextual Payment Checkpoint for Amount Confirmation Accuracy

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Electronic payment systems often result in errors due to incorrect payment amounts or payees being selected, leading to costly and time-consuming rectifications for customers and financial institutions.

Innovation Solution

Introduce a checkpoint in the payment workflow using a generative artificial intelligence model (GAIM) to generate educational text strings that include the payment amount, allowing customers to reconsider and correct their payment details before confirmation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If a simple payment confirmation interface is used, then the ease of operation is improved, but the payment accuracy deteriorates due to errors in amount or payee selection

Engineering Contradiction:

Improveease of payment initiationVSAvoidpayment accuracy

Core Design Contradiction:

Ease of operationVSManufacturing precision

Solution Approach 1:

The system performs preliminary actions by generating an educational text string that includes the payment amount before the user confirms the payment. This allows the user to review and verify the payment details in advance, preventing errors in amount or payee selection while maintaining a simple interface.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system introduces feedback by displaying an educational text string that provides information about the payment amount to the user before confirmation. This feedback mechanism helps users verify their input and reduces errors without complicating the payment process.

Inventive Principle:

Principle #23Feedback

2Manufacturing precision

If additional verification steps are added to improve payment accuracy, then the payment accuracy is improved, but the device complexity increases

Engineering Contradiction:

Improvepayment accuracyVSAvoidworkflow complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The system uses an intermediary approach by introducing an educational text string as a mediator between the payment input and confirmation steps. This text string provides verification information without requiring additional complex verification steps, maintaining simplicity while improving accuracy.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Manufacturing precision

If a checkpoint with educational text string is introduced, then the payment accuracy is improved, but the loss of time increases due to additional processing

Engineering Contradiction:

Improvepayment accuracyVSAvoidtime for payment processing

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The educational text string is generated using a pre-trained GAIM model, which allows for quick generation of verification content. This preliminary preparation of the AI model enables fast generation of text strings during the payment process, minimizing additional processing time while maintaining accuracy improvement.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20260017662A1Contextual payment augmentation

Publication Date: 2026.01.15 WELLS FARGO BANK NA

AI summary

Augmenting an electronic payment by generating and interposing into the payment workflow a text string that includes a number corresponding to the payment amount. The text string can be an educational text string that is interposed before, or in conjunction with, a portion of the payment workflow that includes a request to confirm the payment. The interposed educational text string can be generated by a generative artificial intelligence model (GAIM). The GAIM can generate the interposed educational information based on the payment amount and one or more contextual factors about the payment.