OCR Technology

Quick Guide on Evolution of Invoice Processing OCR Technology

Traditionally, invoices were printed on paper and until recently the processing was done manually.

What was the typical invoicing process?

A bill would be typed, printed, and sent by mail. Some were written and delivered by hand while the services were being provided. The invoice was made up of line items that each included a price and a description of the products or services sold. It included the total amount due as well as the payment due date.

The payment request would be sent along to a bookkeeper when the accounting department received the invoice. The payment request would subsequently be added to a sub-ledger for accounts payable.

Once the payment for the invoice was made, the details were entered into the company’s ledger. The paper invoice sheet was usually kept in a file for future reference or to tally the payments at the end of each month/quarter.

The story of conventional invoice processing comes to an end here. These procedures are effective for businesses with limited incoming bills, notwithstanding their inefficiency.

So, how can organizations with hundreds and thousands of bills make the invoicing process more efficient?

Using an invoice OCR software.

First, let’s understand the different types of data-capturing methods.

Most contemporary accountants believe that document digitization is a crucial step in processing paper invoices. There are three fundamental ways to capture data for invoices: manually entering the information, using an invoice OCR template, and using intelligent invoice OCR processing.

  • Manual data capture entails manually reading the invoice’s information and entering it into a database. This procedure is ineffective, time-consuming, and highly susceptible to human error.
  • The financial documents are “read,” and the data are extracted using invoice OCR technology. The established criteria used by template-based OCR are compatible with the format of the processed invoice. This way of capturing invoice data can be moderately reliable and accurate. The disadvantage of invoice OCR is that each type of invoice format requires its own template and set of
  • Robotic invoice OCR automation, not a technology stack component for intelligent document processing, greatly enhances integrated data processing. RPA bots can extend the capabilities of the intelligent process of automation by processing transactions, modifying the retrieved data, evoking responses, or interacting with third-party

What makes invoice OCR the preferred method for data capture?

OCR invoicing is extracting data from invoices, integrating it with a structured database, and training a template-based OCR model for a particular invoice style. Field-specific data can be removed from fixed template documents using this semi-automated data extraction method. Invoice OCR cannot extract “context-specific” information from records; however, Intelligent Document Processing can do so.

Here are some of the reasons why invoice OCR is the preferred method for data capture:

  • Boosting efficiency 

It takes much longer and more work to extract and enter data manually. However, invoice OCR helps to do it efficiently and quickly. They help with unstructured data and employ machine learning to keep learning new formats.

All of this has the potential to speed up and simplify the data collection process greatly. Additionally, with invoice OCR technology, quicker payment distribution can happen.

  • Decrease in manual expenses

Invoice OCR technology reduces the need for physical labor. As a result, workers can now concentrate their efforts on more worthwhile initiatives. They might only be needed to get involved if they need to validate any data that has been identified or approve payments that exceed a certain amount. They won’t be required to complete as many physically taxing, labor-intensive duties, though. As a result, they can concentrate on more essential responsibilities.

  • Cutting costs 

Using invoice OCR software might eliminate the need to recruit additional accounting personnel as it automates manual and repetitive tasks such as document verification and validation of data. Additionally, since they can use their time more efficiently, employees may concentrate on activities that create value and increase revenue for the company.

  • For increasing accuracy

Accuracy is also a significant advantage when managing financial data and payments. We are only human, after all, and manually entering data might be taxing. Errors may result from this. For example, errors can occur even due to copy-pasting mistakes when collecting data from multiple spreadsheets. When handling such sensitive and crucial information, there is terrible news. Not to mention that it can result in payments being processed incorrectly. Advanced invoice OCR software significantly lowers this chance of error, providing the accounts team with peace of mind.

What is the conclusion?

You may automate the collection and processing of invoice data by using an advanced invoice OCR engine and APIs. Intelligent extraction and validation with minimal configuration and straightforward integration. Using invoice OCR software can help you save the hours previously spent manually entering invoice data.

With more than 99% accuracy, you can extract data from thousands of invoices in real time. With advanced accounts payable automation, the invoice OCR system can help you spot duplicate invoices, typos, and potential fraud.

Christophe Rude
Christophe Rude
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