Account Number Cleansing for Payment Routing
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Solution Overview
Problem
Existing electronic payment systems face high rates of account mask failures due to incorrect customer input of account numbers, leading to suboptimal remittance routing and eBill activation rejections, despite existing solutions failing to effectively address these issues.
Innovation Solution
A system and method that transforms customer-entered account number data into multiple forms for specific processing needs, incorporating account cleansing capabilities, global trim rules, and automated redirections to improve match rates and routing efficiency, while allowing administrators to manage and maintain account cleansing rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If customers manually enter account numbers without automated validation, then the system maintains simplicity, but account mask failure rates increase significantly
Solution Approach 1:
The system performs preliminary account number cleansing and validation by comparing entered account numbers against stored account masks before processing remittances. This pre-validation step identifies and corrects formatting errors, leading/trailing spaces, and other input issues before they cause mask failures, thereby improving reliability without requiring complex customer actions
Solution Approach 2:
The system provides feedback to customers when account number entry errors are detected by comparing against account masks. Error messages guide customers to correct their input, and the system may attempt re-validation automatically. This feedback loop improves the success rate of account mask matching while maintaining ease of operation through clear error communication
2Reliability
If the system implements multiple account cleansing rules and validation steps, then account mask failure rates decrease, but system complexity increases
Solution Approach 1:
The account validation process is segmented into distinct steps: initial input validation, comparison against account masks, identification of specific error types (formatting issues, leading/trailing spaces, incorrect length), and targeted correction. Each segment handles a specific aspect of validation, making the overall complex process more manageable and maintainable while achieving high success rates
Solution Approach 2:
The system introduces an intermediary account mask database that stores reference account number patterns for different merchants. This intermediary layer acts as a mediator between customer input and the remittance processing system, providing a buffer that absorbs validation complexity while presenting a simple interface to customers and downstream systems
3Productivity
If the system routes remittances without validating account numbers first, then processing speed is maintained, but remittances may be routed incorrectly
Solution Approach 1:
The system performs preliminary account number validation and merchant identification before remittance routing by comparing account numbers against stored masks. This pre-processing step ensures correct routing determination without adding significant delay, as the validation occurs in parallel with remittance preparation and uses efficient string matching algorithms
Solution Approach 2:
For account numbers that pass initial validation checks or match obvious patterns, the system skips detailed mask comparison steps and proceeds directly to routing. This selective validation approach maintains high processing speed for clear cases while applying thorough validation only when needed, balancing productivity and routing accuracy
Data Source
AI summary
A technique is provided that transforms account number data received from the consumer into one or more forms based on use by specific processes. Further provided is a technique for establishing payees using these account numbers such that remittances can be routed via the most cost effective means, e.g. which remittance processor is determined and/or which processor among internal processors within an enterprise is determined, and such that, when available, electronic bills can be successfully requested for on-line presentation. The technique to transform account number data can be applied by systems in industries other than banking and for account numbers from sources other than a customer.