In this article, we will explore how processing invoices using optical character recognition (OCR) works and its benefits. Read on to learn more.
Invoice OCR (Optical Character Recognition) processing uses technology to convert invoice documents—such as scanned paper invoices, PDFs, or images—into editable and searchable data. This process automates the extraction of key information, enabling efficient data entry and integration into financial systems.
Example: Using OCR, Coca-Cola can extract and validate data from a supplier's invoice for 500 units of Coca-Cola Classic (Product ID: CCC500), including invoice number 12345, date 07/15/2023, and amount $10,000, directly into their SAP system.
Use our 10 step OCR invoice processing to save time on your invoice documents. Simply follow the steps below.
Invoices are received from vendors via various channels such as email, mail, or electronic data interchange (EDI). The invoices are then scanned or imported into the OCR system.
Example: An invoice for 50 units of iPhone 12 is received via email and uploaded into the OCR system for processing.
The OCR system preprocesses the scanned images to enhance their quality. This involves steps like deskewing, noise reduction, and adjusting brightness and contrast.
Example: The scanned image of an invoice for 200 units of Samsung S23 is enhanced to ensure all text is clear and legible.
Using OCR technology, the system extracts text from the enhanced images. It identifies key data fields such as invoice number, date, vendor name, line items, and totals.
Example: The OCR system extracts details like the invoice number 78910, date, vendor Tungsten Corp, and items including 30 units of USB flash drive.
The extracted data is validated against predefined rules and existing data to ensure accuracy and completeness. Any discrepancies or errors are flagged for review.
Example: The system checks the extracted invoice number 78910 and matches it with the vendor details in the database to confirm authenticity.
Flagged errors and discrepancies are reviewed and corrected manually or through automated corrections. This ensures that the data is accurate before further processing.
Example: A discrepancy in the quantity of product iPhone 13 is corrected from 50 to 55 units based on the vendor's purchase order.
The validated and corrected data is then integrated into the company’s accounting or ERP system. This allows for seamless updating of financial records and inventory management.
Example: The validated data for an invoice with 20 units of Airpods is imported into the SAP system, updating the accounts payable and inventory records.
The processed invoices are digitally archived for future reference and compliance purposes. This ensures that all invoice records are easily retrievable when needed.
Example: The invoice for 100 units of Lenovo IdeaPad stored in the company’s digital archive, tagged with metadata for easy search and retrieval.
The system generates reports based on the processed invoice data. These reports help in financial analysis, auditing, and monitoring vendor performance.
Example: A report is generated showing all invoices processed in the month for vendor Tungsten Corp, including details like invoice numbers and total amounts.
Invoices that cannot be processed automatically due to various issues are flagged for manual intervention. These exceptions are handled by trained personnel to ensure no invoice is left unprocessed.
Example: An invoice for 70 units of bluetooth keyboard with unclear line items is flagged and sent to the accounts payable team for manual review.
The OCR system continuously learns and improves from the feedback provided during manual corrections and validations. This enhances its accuracy and efficiency over time.
Example: The OCR system learns from repeated corrections of product codes like JKL456, improving its recognition accuracy for future invoices.
TechWave Innovations is a leading tech company specializing in consumer electronics. It aims to enhance its market strategy using our OCR invoicing process. Here’s how they implemented our simple 10 step process:
Sales data is collected from multiple sources like online sales platforms, retail stores, and distributors. For example, data for 50 units of TechWave SmartWatch Infinity sold via the online store is captured and uploaded into the system for analysis.
The collected data undergoes preprocessing to ensure quality and consistency. For instance, sales data for 200 units of TechWave Smartphone Titan is cleaned to remove duplicates and correct any errors, ensuring all records are accurate and standardized.
Advanced extraction techniques are used to identify key metrics such as sales volume, revenue, and customer demographics. The system extracts details like a total revenue of $50,000 from the sale of 30 units of TechWave Smart Speaker Echo.
The extracted data is validated against predefined rules and historical records. The system checks the sales volume of 789 units and matches it with inventory records to confirm accuracy.
Flagged errors and discrepancies are reviewed and corrected. For example, a discrepancy in the sales quantity of TechWave Tablet Nova is corrected from 50 to 55 units based on the sales team's records.
Validated data is integrated into the company’s business intelligence or ERP system. The validated data for 20 units of TechWave Home Security Pro is imported into the SAP system, updating accounts receivable and inventory records.
Processed sales data is digitally archived for future reference and compliance. The sales record for 100 units of TechWave Laptop Vertex is stored in the company’s digital archive, tagged with metadata for easy retrieval.
Reports are generated based on the processed sales data to aid in financial analysis and auditing. A report showing all sales processed in the month for TechWave SmartWatch Infinity includes details like sales volumes and total revenue.
Sales data that cannot be processed automatically due to issues are flagged for manual intervention. A sales record for 70 units of TechWave Bluetooth Keyboard with unclear line items is flagged and sent to the sales team for review.
The system continuously learns from manual corrections and validations to improve accuracy and efficiency. The system learns from repeated corrections of product codes like TWK456, enhancing recognition accuracy for future sales data.
Here are some of the most common benefits of using OCR to process your invoices:
Using OCR to process invoices automates the extraction of data from invoices, drastically reducing the time needed compared to manual entry. This enables faster processing and quicker turnaround times.
Manual data entry is susceptible to human errors, which can lead to costly mistakes. OCR technology improves accuracy by automatically capturing data with high precision.
By minimizing manual labor and reducing errors, companies can save on administrative costs. The automation of invoice processing also reduces the need for paper storage and handling.
OCR systems convert invoice data into digital formats, making it easily searchable and accessible. This facilitates better data management and quick retrieval of information when needed.
Automated invoice processing ensures consistent data capture and storage, aiding in compliance with regulatory requirements. It also simplifies the generation of financial reports and audits.
Faster and more accurate invoice processing leads to timely payments, which can improve relationships with vendors. This can result in better terms and potential discounts for early payments.
We hope that you now have a better understanding of what invoice processing using OCR is, its benefits and how to implement our 10 step process. If you enjoyed this article, you might also like our article on OCR for invoice processing and AI invoice processing.