Automated Check Processing via Optical Character Recognition and Database Retrieval
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Solution Overview
Problem
Current systems for processing payments, especially when received as paper checks, are resource-intensive, time-consuming, and prone to inaccuracy due to unclear payment amounts or destination accounts, requiring manual operator analysis and external information retrieval.
Innovation Solution
A database retrieval system that includes a scanner to convert checks into grayscale and black-and-white images, a processor using optical character recognition to extract relevant information, and a GUI for auto-populating account and amount fields, allowing for automated payment application based on stored customer data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual operator analysis is used to process paper checks, then payment processing can be performed, but the process becomes resource-intensive and time-consuming
Solution Approach 1:
The patent replaces manual operator analysis with an automated system consisting of a scanner that converts paper checks into images, optical character recognition software that extracts payment information, and a processor that applies payments to accounts. This substitution of mechanical/manual processes with automated technological systems directly resolves the contradiction by improving processing speed while reducing resource consumption.
Solution Approach 2:
The system enables self-service processing where the check processing system automatically extracts information from checks, identifies recipient accounts, and applies payments without requiring human operators. The automated retrieval of customer information from databases and automatic payment application demonstrates self-service functionality that eliminates manual intervention.
2Reliability
If manual operator analysis is used to determine payment destination, then payments can be processed, but accuracy decreases due to unclear payment amounts or destination accounts
Solution Approach 1:
The patent replaces manual operator judgment with automated optical character recognition and database retrieval systems. The OCR software accurately extracts payment amounts and destination account information from check images, while the processor automatically matches account numbers with customer records in databases, eliminating human error and improving accuracy without sacrificing speed.
Solution Approach 2:
The system incorporates feedback mechanisms where the processor retrieves customer information from databases based on extracted account numbers, verifies the information, and uses this feedback to confirm correct payment application. The system can identify and correct discrepancies between extracted information and database records, ensuring high accuracy.
3Productivity
If automated optical character recognition is used to extract information from checks, then processing speed increases, but the system complexity increases
Solution Approach 1:
The patent employs a multi-functional integrated system where a single processor coordinates multiple functions: controlling the scanner, managing optical character recognition, retrieving customer information from databases, and applying payments. This universal system handles the entire payment processing workflow, improving speed while managing complexity through integration rather than separate components.
Solution Approach 2:
The patent uses an intermediary database system that stores customer information and account details. The processor queries this intermediary database to verify extracted account numbers and retrieve additional customer information, acting as a mediator between the OCR extraction process and the final payment application, thereby simplifying the overall system architecture.
4Loss of energy
If automated payment processing system is implemented, then resource consumption decreases, but initial system setup and complexity increase
Solution Approach 1:
The patent implements preliminary action by pre-storing customer information, account details, and payment preferences in databases before actual payment processing occurs. When checks are processed, the system simply retrieves pre-prepared information rather than creating it in real-time, reducing processing complexity and resource consumption during operational phases.
Data Source
AI summary
A method for database retrieval is provided. The method may include receiving a history datastore. The method may include receiving a payment, i.e., a paper check. The method may include simultaneously scanning the check into a grayscale image and black and white image. The method may include reviewing each pixel on the black and white image alone and in combination with surrounding pixels to determine an arrangement of shaded pixels. When the arrangement of shaded pixels is determined to be above a predetermined threshold of similarity to a predefined set of characters, the method may determine a subset of characters and store the subset of characters in a memory. The method may include crawling the history datastore to determine information which corresponds to the subset of characters stored in memory and retrieving the corresponding information. The method may include showing the corresponding information and the payment on a GUI.