Automated Invoice Classification System for Non-PO Invoices
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Solution Overview
Problem
Medium-sized and large organizations face challenges in accurately classifying and routing invoices without associated purchase orders, often resulting in manual coding errors, inaccurate financial statements, and poor decision-making due to the complexity of their unique charts of accounts.
Innovation Solution
The Invoice Classification and Approval System is a server-based software process that automates the classification of invoices by applying general ledger account coding rules based on invoice data and uses machine learning to learn correct coding and routing rules, while also electronically routing invoices for approval to the appropriate approvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual coding of invoices is performed by approvers, then flexibility in handling diverse invoice types is maintained, but coding accuracy deteriorates due to lack of accounting knowledge and complexity of chart of accounts
Solution Approach 1:
The patent introduces an automated invoice classification system that acts as an intermediary between invoice approvers and the chart of accounts. The system automatically classifies invoices by analyzing invoice data, vendor information, and historical coding patterns, then presents suggested classifications to approvers. This intermediary system handles the complexity of account code selection, validation of code combinations, and routing decisions, while approvers maintain oversight and can override suggestions. The system learns from manual corrections to improve future automated classifications.
2Measurement precision
If automated classification system is implemented, then coding accuracy improves through consistent application of rules, but system complexity increases due to need to manage coding rules and machine learning models
Solution Approach 1:
The patent implements a self-learning classification system that automatically improves its performance over time without requiring manual intervention to update coding rules. The system monitors manual corrections made by approvers and uses machine learning to learn from these corrections, automatically updating its classification logic. The system also validates account code combinations against the organization's chart of accounts structure, automatically identifying and correcting invalid combinations. This self-service capability reduces the long-term complexity burden on the organization.
Solution Approach 2:
The system performs preliminary classification and validation of invoices before they reach human approvers. It pre-validates account code combinations against the chart of accounts, pre-routes invoices to appropriate approvers based on classification, and pre-presents suggested classifications to approvers. This preliminary action reduces the workload on approvers and ensures that most routine invoices are processed with high accuracy before human review.
3Device complexity
If manual coding is used, then system simplicity is maintained, but time consumption increases as approvers spend valuable time identifying correct coding
Solution Approach 1:
The patent replaces the manual mechanical process of invoice coding with an automated electronic classification system. The system electronically analyzes invoice data, vendor information, and historical patterns to automatically determine appropriate account codes and routing. This electronic substitution eliminates the time-consuming manual search through chart of accounts and eliminates errors from manual entry, while requiring minimal changes to the existing invoice workflow.
4Ease of operation
If invoice approvers code invoices without training, then operational ease is maintained, but coding consistency deteriorates as different managers code differently
Solution Approach 1:
The patent implements a feedback mechanism where the automated classification system learns from manual corrections made by approvers. When an approver overrides the system's suggested classification, the system records this correction and uses it to improve future automated classifications. The system also provides feedback to approvers by showing them why a particular classification was suggested, helping them understand the classification logic without requiring formal training. This feedback loop ensures coding consistency across different managers while maintaining operational ease.
Data Source
AI summary
A method and system for managing and automating the classification of non-purchase order invoices for organizations. A centralized server applies rules to properly apply general ledger account coding for invoices based on data contained in the invoice. The server then electronically routes the invoice for approval to the appropriate approvers in the organization. In the absence of rules, the system applies machine learning to learn the correct rules, to be applied the next time said invoice is received and processed.