Automated Invoice Audit System for Pricing Error Detection
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Solution Overview
Problem
Medium to large businesses face challenges in monitoring and correcting pricing errors in transactions due to high volumes of products and transactions, leading to significant overpayments and lost profits, with human error and independent pricing effective dates complicating the process.
Innovation Solution
A software method that automatically determines the appropriate price for purchased items based on date, volume, and other factors by comparing entered price settings with invoice prices, generating reports for overcharges, and flagging exceptions before or after payment, utilizing payment history, accounts payable, and invoice data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual monitoring of pricing transactions is performed, then human error and subjectivity are reduced, but the high volume of transactions makes comprehensive monitoring difficult and time-consuming
Solution Approach 1:
The patent replaces manual mechanical monitoring processes with an automated computer-based system that electronically compares invoice prices against stored pricing data. The system automatically queries pricing information, determines appropriate prices based on date and volume factors, and identifies overcharges without human intervention, thereby maintaining high reliability while processing large transaction volumes efficiently
Solution Approach 2:
The system performs self-service by automatically maintaining its own pricing reference data, comparing invoices against this data, and generating audit reports without requiring continuous manual oversight. The automated process independently monitors pricing accuracy across all transactions, freeing employees from manual monitoring while ensuring comprehensive coverage
2Loss of energy
If comprehensive price monitoring is implemented, then overpayment reduction is improved, but the complexity of tracking multiple pricing factors and effective dates increases
Solution Approach 1:
The patent segments the pricing monitoring function into distinct modular components: a pricing data storage module, an automated comparison module, and an audit report generation module. Each component handles a specific aspect of pricing verification, making the overall complex task manageable and the system easier to implement and maintain while effectively tracking multiple pricing factors
Solution Approach 2:
The system performs preliminary action by pre-storing pricing data and effective date information in a database before transactions occur. This advance preparation allows the automated system to quickly compare invoices against pre-established pricing rules without needing to analyze complex pricing structures in real-time, reducing system complexity while maintaining comprehensive monitoring
3Measurement precision
If automated price determination is implemented, then pricing error detection is improved, but the need for accurate date and volume data entry increases
Solution Approach 1:
The system implements feedback mechanisms that automatically verify entered data against existing records and pricing rules. When date or volume data is entered, the system checks for consistency with stored pricing information and can flag potential errors or inconsistencies, ensuring accurate data entry while maintaining the benefits of automated price determination
Solution Approach 2:
The pricing monitoring system serves multiple functions simultaneously: it stores pricing data, determines appropriate prices, compares invoices, identifies overcharges, and generates reports. This multi-functionality consolidates what would otherwise require multiple separate systems into a single unified platform, reducing the overall data entry burden while maintaining high measurement precision
Data Source
AI summary
A process for increasing profits of a business engaged in the purchase of large numbers of products and/or products of volatile pricing from numerous vendors that operates to identify pricing errors, preferably typically before payment, by automatically reviewing all invoices typically in the order they are received to determine a best system price for each line item of each invoice by reference to pricing factors such as volume discount, seasonal pricing, price protection, commodity pricing, competition pricing, and cash discount recorded in memory for the subject item and reference to payment history data, accounts payable data and invoice data. From the pricing factors and associated data, a best system price is determined and compared to the invoice price for the item so that pricing errors are automatically uncovered and, if appropriate, flagged to identify the same as an exception for warning or notification.