Receipt Image Amount Extraction for Expense Validation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current reimbursement processes for expenses, such as those incurred by employees, are often manual, time-consuming, and prone to errors, and poorly suited for detecting fraud, especially when dealing with retrospective submissions of receipts.
Innovation Solution
A method and system that involves receiving and processing receipt images using a computing device, which renders the images on a display screen, allows for input confirmation of submission totals, and transmits these totals to an expense management system, incorporating features like character recognition for adjusting amounts and categorization of expenses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual reimbursement processing is used, then flexibility in handling individual cases is maintained, but time consumption and error rates increase significantly
Solution Approach 1:
The system enables self-service through automated receipt processing where the system independently extracts amounts, categorizes expenses, and validates submissions without requiring manual intervention for routine tasks, thereby increasing productivity while maintaining operational simplicity
Solution Approach 2:
Manual mechanical processing of receipts is replaced with an automated image processing system that uses optical character recognition and digital validation mechanisms to extract and verify expense information, eliminating manual data entry and reducing errors
2Reliability
If retrospective reimbursement processing is used, then flexibility in submitting expenses after incurred is maintained, but fraud detection capability deteriorates
Solution Approach 1:
The system performs preliminary validation of expense policies and amount verification before reimbursement is processed, enabling fraud detection to occur in advance rather than retrospectively, thereby maintaining timely submission while improving detection accuracy
Solution Approach 2:
The system provides immediate feedback on expense submissions by automatically validating amounts against policy thresholds and flagging potential anomalies, enabling real-time fraud detection while maintaining the flexibility of retrospective submission timing
3Measurement precision
If automated amount extraction is implemented, then processing accuracy is improved, but system complexity and initial setup requirements increase
Solution Approach 1:
The system creates a digital copy of the receipt image and processes this copy through automated optical character recognition, separating the complex processing tasks from the original physical receipt and enabling accurate amount extraction without increasing operational complexity
Solution Approach 2:
An intermediary processing layer is introduced between the receipt image and the final reimbursement decision, where automated systems extract and validate amounts, thereby improving accuracy while the intermediary layer manages the complexity of image processing
4Productivity
If manual verification of expense amounts is performed, then flexibility in adjusting individual expenses is maintained, but time consumption increases
Solution Approach 1:
The system performs self-service validation by automatically comparing extracted amounts against predefined expense policies and thresholds, eliminating the need for manual verification while maintaining the ability to adjust individual expenses through automated rule-based decisions
Solution Approach 2:
The system changes the verification parameter from manual review to automated digital validation, where amounts are automatically compared against policy parameters, thereby increasing validation speed while reducing manual intervention requirements
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach streamlines the reimbursement process by reducing manual errors, enhancing the detection of potential fraud, and improving the efficiency of expense management by automating the processing and validation of expense submissions.
Implementation Method 1
performing character recognition on the receipt image to determine the total amount
Data Source
AI summary
A device, system and method for processing images that include amounts is provided. A receipt image is received at a controller of a computing device. The receipt image is rendered, at a display screen, the receipt image comprising a total amount region including a total amount of expenses in the receipt image. A total amount field, including a submission total amount associated with the total amount, is rendered at the display screen adjacent the receipt image. A link between the total amount region and the total amount field is rendered at the display screen, at the total amount region of the receipt image. Input is received confirming the submission total amount, via an actuatable option rendered at the display screen in association with the total amount field. The submission total amount is transmitted, via a communication interface, to an expense management system.