Commercial Leakage Platform Using AI Contract-Invoice Comparison
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Solution Overview
Problem
Existing systems struggle to efficiently manage and enforce complex commercial terms across numerous contracts and invoices, leading to commercial leakage, particularly with low-value invoices often going unnoticed, resulting in unrealized discounts and significant financial losses.
Innovation Solution
A computer-implemented system that standardizes commercial terms from contracts and invoices using artificial intelligence, enabling automated comparison and detection of discrepancies, with feedback loops for human professionals to refine the process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review of contracts and invoices is performed, then accuracy in detecting commercial leakage is improved, but productivity and resource efficiency deteriorate due to intensive manual effort
Solution Approach 1:
The patent replaces manual mechanical review processes with an automated computer-based system that uses optical character recognition (OCR), natural language processing (NLP), and machine learning algorithms to extract, standardize, and compare commercial terms from contracts and invoices, thereby maintaining high detection accuracy while dramatically improving productivity
Solution Approach 2:
The patent introduces a computer processor as an intermediary that acts as a bridge between raw contract/invoice documents and the detection analysis, using standardized data formats and comparison algorithms to mediate the detection process, thereby reducing direct human intervention while preserving accuracy
2Measurement precision
If comprehensive line-item comparison of contracts and invoices is performed, then detection precision of commercial leakage is improved, but device complexity and operational difficulty worsen due to unique variations in each contract and invoice
Solution Approach 1:
The patent transforms the complexity of diverse contract and invoice formats into manageable parameters by extracting specific commercial terms (price, quantity, discounts, payment terms) and standardizing them into a common data structure, allowing precise comparison without being overwhelmed by format variations
Solution Approach 2:
The patent segments the complex comparison task into distinct modules: data extraction from documents, standardization of commercial terms, comparison logic execution, and discrepancy identification. This modular approach reduces system complexity while maintaining comprehensive detection capability
3Productivity
If low-value invoices are excluded from review, then productivity is improved by reducing manual effort, but commercial leakage worsens due to unrealized discounts and financial losses
Solution Approach 1:
The patent enables the system to automatically review and flag even low-value invoices for potential commercial leakage without requiring proportional manual review effort, using automated algorithms to identify discrepancies such as missed discounts or pricing errors that would otherwise be overlooked
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously learns from identified discrepancies and improves its detection algorithms, ensuring that even small-value invoices are systematically reviewed and that patterns of commercial leakage are progressively eliminated
Data Source
AI summary
The invention relates to computer-implemented systems and methods for identifying and further preventing commercial or contract leakage across multiple different procurement relationships. This may involve ingesting a contract extracting commercial terms, such as price, rates, etc. Invoices may be similarly ingested and commercial terms may be extracted on a line item basis. An embodiment of the present invention may identify various types of commercial leakage, such as rate/price discrepancies, full/partial duplication, unrealized discounts, unrealized rebates, disallowance of charges (travel expenses), etc.