Mobile Invoice Image Processing for Automated Payment Settlement
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Solution Overview
Problem
Current methods for settling invoices are insecure and inefficient, as they require manual entry of payment information and are susceptible to fraud, with payors often forgetting to pay on time, leading to late fees.
Innovation Solution
A system and method using a mobile device to capture and process images of invoices, extracting network location and payment information to automatically settle invoices through a bill-pay website, reducing the need for manual data entry and minimizing fraud risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual entry of payment information is used, then the system is simple to operate, but the process is time-consuming and error-prone
Solution Approach 1:
The system enables self-service by automatically extracting payment information from invoice images and populating payment forms without human intervention. The mobile device captures the invoice, the system processes the image to extract details, and automatically submits the payment, allowing the invoice settlement process to serve itself.
Solution Approach 2:
The patent replaces manual mechanical data entry with automated image processing and data extraction systems. Instead of manually typing payment information, the system uses optical character recognition and form-filling algorithms to automatically extract and input data, substituting human manual operations with automated computational processes.
2Ease of operation
If email hyperlinks are used for bill-pay websites, then access is convenient, but fraud risk increases
Solution Approach 1:
The system introduces an intermediary verification process between the invoice and the bill-pay website. Instead of directly clicking email hyperlinks, the mobile device captures the invoice image, extracts the URL through image processing, and verifies the information through multiple data points before establishing connection, acting as a security intermediary that blocks fraudulent links.
Solution Approach 2:
The system performs preliminary verification actions before accessing the bill-pay website. By extracting and validating the URL from the invoice image itself, and cross-checking with other invoice data, the system preemptively prevents access to fraudulent websites before any payment information could be compromised.
3Loss of time
If payment information is stored manually, then quick access is possible, but late fees occur due to forgetting
Solution Approach 1:
The system performs preliminary extraction and storage of payment information directly from the invoice image at the time of capture. By automatically extracting due dates, payment amounts, and biller information from the invoice itself and storing it in structured format, the system prepares all necessary data in advance, eliminating the need for manual record-keeping and ensuring timely payment reminders.
4Measurement precision
If automated image processing is implemented, then data extraction accuracy improves, but processing complexity increases
Solution Approach 1:
The image processing system is segmented into distinct functional modules: image capture, pre-processing, text extraction, data validation, and form population. Each module handles a specific aspect of the processing pipeline, allowing complex image processing to be broken down into manageable, specialized components that work together to achieve high extraction accuracy.
Data Source
AI summary
Provided herein is a computer-implemented method for settling an outstanding invoice issued by a payee, including the steps of capturing a digital image of an invoice issued by a payee to a payor, processing the digital image to identify invoice data and a network location associated with the payee, automatically establishing communication with the network location identified in the digital image, and automatically inputting payment information into one or more fields of the webpage at the network location.