Automated Invoice Processing System with Validation and Spend Evaluation
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Solution Overview
Problem
Current electronic invoicing systems face challenges due to divergent accounts receivables and payables systems, requiring extensive customization and resulting in the prevalence of manual data entry from paper or electronic invoices, hindering widespread adoption.
Innovation Solution
An automated invoice processing system that includes a document workflow system and an invoice hub for receiving, validating, and evaluating invoices through imaging, OCR, and data field validation, with a spend management database for substantive evaluation and secure session management for configuration and data exchange.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If electronic invoicing systems are implemented with standardized protocols (EDI, XML), then automation and efficiency are improved, but extensive customization is required for each vendor-customer interface, increasing system complexity
Solution Approach 1:
The patent implements a universal interface framework that enables the system to handle multiple invoice formats (EDI, XML, PDF, images) through a single standardized interface. The interface layer provides format-agnostic data extraction and validation capabilities, allowing the core processing system to remain unchanged while supporting diverse input formats, thus reducing customization requirements for each vendor-customer interface
Solution Approach 2:
The patent introduces an intermediary interface layer that mediates between diverse invoice formats and the core processing system. This interface layer includes standardized data mapping, validation rules, and conversion capabilities that translate various invoice formats into a unified internal representation, eliminating the need for extensive custom integration for each vendor-customer pair
2Adaptability or versatility
If manual data entry is used for invoice processing, then system compatibility is maintained, but processing time and labor costs increase significantly
Solution Approach 1:
The patent implements automated data extraction and validation capabilities that enable the system to process invoices autonomously without manual intervention. The system automatically extracts data from various invoice formats, validates it against predefined rules, and integrates it with accounting systems, replacing manual data entry while maintaining compatibility through standardized interfaces
Solution Approach 2:
The patent replaces the mechanical process of manual data entry with automated optical character recognition (OCR) and data extraction technologies. The system uses software-based methods to capture, validate, and process invoice data, substituting human operators with automated processing mechanisms that significantly reduce processing time while maintaining accuracy
3Measurement precision
If comprehensive validation and evaluation rules are implemented, then data accuracy is improved, but processing complexity and computational requirements increase
Solution Approach 1:
The patent segments the validation and evaluation process into distinct modular components, each responsible for specific validation rules or evaluation criteria. This modular architecture allows validation rules to be organized into separate, reusable modules that can be independently configured and maintained, reducing overall system complexity while maintaining comprehensive validation capabilities
Solution Approach 2:
The patent implements configurable validation parameters and thresholds that can be adjusted based on specific business requirements. The system allows dynamic modification of validation rules, data formats, and evaluation criteria without requiring changes to the core processing logic, enabling high accuracy while maintaining processing simplicity through parameter-based configuration
Data Source
AI summary
An invoice processing system includes a document system and an invoice hub. The document system receives a document image (either a paper invoice or an image file). A character recognition system generates a data file representation of the invoice data from the document image. A data field value validation engine determines, for each data field, a rule associated with each data field. The rule is applied to the data field value to distinguish between a valid field value and suspect data value. A correction center: i) displays a portion of the document image comprising the suspect field value; ii) receives user input of a replacement value to replace the suspect field value as the data field value. The invoice hub receives the data file which includes all validated data field values and stores the invoice data in a transaction database. A spend management evaluation module performs an evaluation function of a selected one of a plurality of evaluation parameter sets to generate a resulting value. Based on the resulting value, the spend management module may determine an evaluation field value in accordance with the defined action associated with the resulting value. The evaluation field value is then associated with the at least one record of invoice data.