Nearest Neighbor Bank Account Validation
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Solution Overview
Problem
Conventional bank account number validation procedures are complex, model-based, and require substantial memory and processor resources, constant retraining, and vast amounts of data to validate new bank account numbers, making them inefficient and resource-intensive.
Innovation Solution
A nearest neighbor-based bank account validation process that uses a small subset of valid bank account numbers associated with a routing number, validating new numbers based on proximity to existing ones without requiring model training or retraining, thus minimizing memory and processor usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If model-based validation procedures are used, then validation accuracy is improved, but memory and processor resources are substantially increased
Solution Approach 1:
The patent extracts only the essential validation logic from complex model-based procedures, retaining accuracy while removing unnecessary computational overhead. The system uses a streamlined validation approach that checks only critical account number formats and patterns rather than employing full machine learning models.
Solution Approach 2:
The system replaces expensive, resource-intensive model-based validation with a simpler, more economical validation method. The lightweight validation logic consumes minimal processor and memory resources while maintaining sufficient accuracy for bank account number verification.
2Reliability
If model-based validation procedures are used, then validation accuracy is improved, but device complexity is increased
Solution Approach 1:
The patent extracts and removes the complex model training and retraining components from the validation system, keeping only the essential validation rules. This simplifies the device architecture while preserving the core validation functionality.
Solution Approach 2:
Instead of using complex models to validate account numbers, the system inverts the approach by using simple, deterministic rules that check account number validity without requiring sophisticated computational models.
3Reliability
If model-based validation procedures are used, then validation accuracy is improved, but constant retraining is required
Solution Approach 1:
The system inverts the traditional approach by using static validation rules that do not require continuous learning and retraining. The validation logic remains consistent over time, eliminating the need for periodic model updates while maintaining validation accuracy.
Solution Approach 2:
The validation system is self-sufficient with predetermined rules that automatically validate account numbers without requiring external retraining data or computational resources. The system maintains its validation capability indefinitely without periodic maintenance.
4Reliability
If model-based validation procedures are used, then validation accuracy is improved, but processor resources are substantially increased
Solution Approach 1:
The system replaces expensive processor-intensive model execution with inexpensive, lightweight validation logic. The simplified validation procedure consumes minimal computational power while achieving sufficient accuracy for bank account number verification.
Solution Approach 2:
The patent removes the computationally expensive model inference step from the validation process, retaining only the essential validation checks that can be performed with minimal processor resources.
Data Source
AI summary
Systems and methods that may be configured to implement a nearest neighbor-based bank account validation process that may be used with electronic payments, transactions and or services.