The Power of Automated Invoice Scanning: A Guide

In a world where businesses are constantly seeking to optimize their processes, the rise of automated technologies has been nothing short of revolutionary. One such technology that is gaining widespread adoption is invoice scanning. With the ability to extract key data from digitized or image-based invoices, these software solutions are helping businesses save time and money while increasing efficiency.

In this article, we’ll talk about invoice scanning, including how it works, automating it, its limitations, and best practices. We’ll also discuss methods to optimize the performance of this software and strategies to uphold the precision of data extraction.

What is Invoice Scanning?

Invoice scanning is simply involves converting invoices into a digital format. Scanned, or digitized, invoices are then processed using tools to automate data extraction. Invoices can be scanned through dedicated scanners, or mobile applications.

Instead of manually entering data, businesses can scan invoices to automatically capture details such as invoice numbers, dates, amounts, supplier information, and line items.

 Overview of How Automated Invoice Scanning Works

So how do automated invoice scanning softwares work? In a nutshell, these softwares evaluate invoices for certain pre-defined criteria and extracts the necessary data automatically.

Automated invoice scanning software are built on a combination of OCRtechnology and Natural Language Processing (NLP) algorithms.

OCR technology is capable of recognizing text from various types of images, including those with different fonts, sizes, and orientations. It can also identify text that is written by hand, making it suitable for human invoices. Once the text is identified, the software uses NLP algorithms to interpret it and extract the necessary data. NLP algorithms analyze the text for patterns and structures, which allow it to identify key pieces of information such as the invoice number, date, amount, and vendor details.

NLP algorithms are designed to work with natural human language, which means they can recognize and extract data from various languages. This makes automated invoice scanning software ideal for businesses that deal with international vendors and invoices in different languages.

The process looks like this:

1. Invoice Received: Companies might receive invoices through email, chat messages, or through a digital folder.
2. OCR Reading: This technology converts the text from an invoice into machine-readable and editable data which can they be queried.
3. Data Extraction: Specific fields from the invoice, like the vendor’s name, total amount, tax, etc., are identified and extracted into a structured format.
4. Data Validation: Users must verify the extracted information either manually or through pre-built validation rules. These automatic rules trigger an alert in case of errors.
5. Integration and Automation: Once the data is extracted, it can be directly fed into a target destination like an accounting system or enterprise resource planning (ERP) software. This entire workflow can be automated, reducing the need for manual data input for each file.

Benefits and Limitations of Automated Invoice Scanning 

Automated invoice scanning can be extremely helpful in quickly and accurately extracting data from invoices. It can greatly reduce human effort and the cost associated with manual data entry.

Faster and more accurate entry also results in quicker payments and improved relationships with vendors.

Automated scanning is also highly scalable as it can handle a higher number of documents without additional manual intervention.

Additionally, removing the need for manual data entry also removes the potential for errors in the process. Humans can make errors 18% to 40% of the time when they use spreadsheets.

However, there are some limitations to invoice scanning technology, which should be considered when evaluating whether it is suitable for your needs.

The accuracy of automated invoice scanning software relies heavily on the quality of the images being scanned. Data extraction may become unreliable or even impossible if the image quality is low or blurry due to poor lighting conditions. Additionally, automated data extraction software typically requires a significant upfront investment. There may be additional costs down the line due to maintenance and updates. Finally, it may take significant time to set up an automated invoice scanning system that works reliably with your existing systems and processes.

Types of Invoice Scanning Techniques

Template Matching

The software also employs Template Matching to accurately read fields such as supplier name, address, product descriptions, and more. This technique involves comparing the structure of an invoice to a predefined template to identify the location of specific fields. The software can then extract the data from those fields. This can improve accuracy by reducing the need for the software to analyze the entire invoice for every data point, which can be time-consuming and resource intensive.

Regex Recognition

Regex recognition is another technique used by the software, which enables it to recognize patterns in text strings using regular expressions. This technique allows the software to identify data even if it appears in different formats on different invoices. By identifying patterns and regularities in the text, the software can more accurately and efficiently extract the necessary data.

Machine Learning

Furthermore, some automated invoice scanning software also incorporate Machine Learning techniques. This enables them to learn from their mistakes over time and improve accuracy using deep learning algorithms. The software recognizes patterns and learns from past errors. It becomes more efficient and accurate at recognizing different types of invoices and extracting data over time.

Templateless Extraction

Templateless software use NLP to detect and extract items from invoices. These software are highly flexible – they can extract data from multiple sources, from emails to contracts, without pre-configuration. They are especially useful for a vast number of incoming files with different layouts. Using a template-based approach in such a situation would be time-consuming – requiring building a specific template for each file.

Optimizing Source Documents for Accurate Invoice Scanning 

To ensure accurate data extraction, businesses need to optimize the quality of the source documents before scanning. One of the most critical factors in successful invoice scanning is the quality of the source document. The image quality must be high enough to ensure reliable text recognition, and the document should be free from any damages or smudges that could impact the OCR process.

Here are some tips to improve the quality of the source documents:

• Use high-quality scanners that can capture clear and sharp images.
• Ensure that the document is straight and flat on the scanner bed to prevent distortion.
• Make sure that the document is not creased, folded, or damaged in any way.
• Improve lighting conditions to avoid shadows, glare, or low-contrast images.
• Remove any stickers, stamps, or marks on the document that could interfere with text recognition.

In addition to optimizing the quality of the source document, businesses should customize the software to meet their specific needs. This includes setting appropriate criteria for data extraction and regularly reviewing the accuracy of the extracted data.

Best Practices for Using Automated Invoice Scanning Software

When it comes to scanning invoices, there are some best practices you should follow to get the most out of your software. Here are a few tips to help you make the most of the data extraction experience:

• Understand your data requirements: Before kicking off your project, take time to assess your data needs and ensure that your software can support them.
• Use keywords: Using keywords will make it easier for the software to recognize and extract information from invoices correctly.
• Test it out: Make sure to test out the software on a number of sample invoices. Do this before deploying it for your entire organization or company. This will help make sure any problems are identified and addressed quickly. It will also minimize costly mistakes or delays down the line.
• Keep your software up to date: Ensure that your software is regularly updated with the latest features, security patches, and performance updates. This will ensure that it remains efficient and effective over time. This is especially important if you’re dealing with sensitive customer or financial data—so be sure to prioritize keeping your software secure!

Explore Astera's AI-powered Data Extraction Capabilities

Explore!

Using Automated Invoice Scanning Software to Detect Fraud

Automated invoice scanning software  can also be an essential component against fraud. Fraudulent invoices are a significant problem for businesses of all sizes and can lead to large financial losses. By automating the invoice scanning process, businesses can detect fraudulent activity faster and more accurately than ever before.

Automated invoice scanning can flag invoices that do not meet certain criteria. This includes those that deviate from the company’s standard invoice format or those that are received from unknown vendors. In addition, software can identify invoices that contain suspicious data, such as duplicate invoice numbers or inflated prices.

Businesses can also use automated invoice scanning software to monitor supplier performance and track payment trends. This can help identify patterns of fraud or other suspicious activity. For example, if a supplier suddenly begins submitting invoices that are significantly higher than usual or if payments are always made to the same bank account, it could be a sign of fraud.

Another benefit of using automated invoice scanning is that it can process large volumes of invoices quickly and accurately. Thus, reducing the risk of fraudulent activity going undetected. It can also free up staff time that would otherwise be spent manually reviewing invoices. Moreover, it allows employees to focus on higher-value tasks.

Conclusion 

In conclusion, Automated Invoice Scanning can significantly reduce the time and effort required for manual data entry. It also provides accurate data extraction and saving resources. It is crucial for companies to select appropriate software based on the volume and complexity of their invoices, while ensuring that data security measures are in place.

Astera Intelligent Document Processing solution offers template-based extraction model and templateless extraction to extract data from unstructured file sources. With its user-friendly interface, users can design templates without the need for coding skills. It also has OCR capabilities to extract data from scanned PDFs. Additionally, it offers a range of data integration and transformation features that streamline the data management process.

By leveraging the power of Astera IDP and following best practices, companies can optimize their invoice processing and allow them to reduce manual labor and take their business operations to the next level.

Automated Invoice Processing with Astera ReportMiner

View Demo