OCR Basics and Tools: How to Streamline Your Invoice Data Extraction

As finance leaders today face increasing capital costs and higher staff turnover rates, efficient financial operations are more important than ever. This is one reason why Accounts Payable (AP) automation is on the rise, revolutionizing how businesses handle their finances.

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In the following sections, we’ll explore one of the biggest headaches of the AP workflow: extracting invoice data. Today’s blog shares different technologies that finance teams use to automate and streamline this important first step of the AP process.

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Automating Invoice Data Extraction: A Necessary Step in Any Digital AP Workflow

Extracting and entering invoice data is one of the largest pain points when it comes to manual AP systems. This task, often falling to AP staff, involves meticulously sifting through invoices and keying in data by hand—a process that's not only time-consuming but also prone to costly errors. This laborious task can lead to delays, increase costs, and frustrate staff.

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But it doesn’t have to be so bad. Businesses have traditionally turned to Optical Character Recognition (OCR) technology to tackle the challenge of manual invoice data extraction. But now, newer technologies like the integration of Artificial Intelligence with OCR (AI/OCR) and the emergence of natural language processing via Generative AI have opened the door to faster, smoother invoice data extraction.

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These advanced technologies provide more accuracy, learning, and adaptability in processing invoice data than ever before, reducing the burden on AP staff and significantly expediting what has been a key bottleneck in AP processes for teams around the globe.

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Invoice Data Extraction Technology: Pros and Cons of Common Approaches

Today’s invoice data capture methods range from manual approaches to cutting-edge AI technologies. In this section, we'll share the pros and cons of the most common invoice data extraction methods: the manual approach, Optical Character Recognition (OCR), Artificial Intelligence with OCR (AI/OCR), and Generative AI Models so you can determine which is best for your business.

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1. Manual Approach

Many teams today still extract invoice data by hand. This involves physically going through each invoice, line by line, to identify and record pertinent information.

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Pros:

This allows complete control over the extraction process.
It doesn't require any specialized software or technical knowledge.

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Cons:

It's time-consuming.
It's prone to human error.
It doesn't scale well with larger volumes of invoices, making it less suitable for large businesses.

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2. Optical Character Recognition (OCR) + Template and Rule-Based Extraction

OCR, or Optical Character Recognition, is a technology that converts scanned images or handwritten text into machine-encoded text. Traditional OCR systems are rule-based and rely on pattern recognition to identify and extract data from invoices.

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Pros:

OCR is efficient at extracting structured data from standard invoices with consistent layout and formatting.
It reduces the time your team has to spend on manual data entry.

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Cons:

OCR struggles with variations in layout, handwriting, and non-standard invoices as it cannot understand any data context.
It typically requires manual intervention from humans to correct errors. That means that all OCR providers need some form of human intervention to assist the extraction process and resolve errors if and when they arise.

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3. OCR with Machine Learning

OCR and machine learning combine traditional OCR with machine learning and artificial intelligence to improve its data extraction capabilities. AI/OCR systems are trained on labeled data and can learn to recognize and extract data from your invoices with higher accuracy than OCR alone.

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Pros:

AI/OCR can better adapt to variations in invoice formats, layouts, and fonts, making itmore versatile than traditional OCR.
It can handle semi-structured and even some unstructured invoices, thanks to its ability to understand context and relationships between different data fields.

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Cons:

AI/OCR systems need to be trained on labeled data, requiring additional time.
Models must be fully retrained to extract additional data points.

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4. Natural Language Processing via Generative AI

Natural Language Processing via Generative AI is another technology that you can couple with your AI/OCR solution. This approach can improve your overall data extraction and validation process.

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Natural Language Processing models fall under this category and can be used to extract specific entities from text, such as dates, currency amounts, vendor names, invoice numbers, and product descriptions.

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Pros:

These models can cross-reference extracted data with contextual information or company-specific rules to ensure accuracy.
Gen AI models are pre-trained on gargantuan datasets and can successfully be applied to new problems with little to no retraining. Providing even greater flexibility in processing the variety of invoice formats encountered by most companies.
Can be tweaked to extract additional data points without full retraining.

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In practice, a complete invoice data extraction solution often combines elements of each of the above approaches. For example, an AI/OCR system may be used to extract the majority of structured data from invoices, while generative AI models assist in context analysis and verification. Even OCR can still be useful in situations where the layout and formatting of invoices are highly consistent.

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Benefits of Automating Invoice Data Extraction

There are significant benefits to automating your invoice data extraction within your AP process, including:

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Time Savings

Automating your invoice data extraction drastically cuts down the time you have to spend on manual data entry and processing. This new efficiency allows your AP team to concentrate on more strategic tasks like vendor relationship management and financial analysis.

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Accuracy and Reliability

Automation greatly minimizes the risk of human errors during manual data entry, resulting in more accurate and reliable financial records.

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Faster Processing

Automation helps your finance team process and approve invoices more quickly, leading to more early payment discounts and better cash flow management. In turn, this speed can also improve your supplier relationships.

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Cost Reduction

Automating your invoice capture can lower the risk of late payment fees and penalties by minimizing human errors, saving your organization money in the long run.

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Scalability

Automated systems easily handle increased invoice volumes as your company grows, no additional staff required.

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Reduced Data Entry Fatigue

Automation reduces the repetitive and monotonous nature of invoice processing, enhancing job satisfaction and employee retention across your finance department.

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Beyond OCR: The Importance of Comprehensive AP Automation with Centime

In the journey towards achieving an efficient accounts payable process, automating invoice data capture is a crucial first step. However, it's essential to understand that this is just one part of a modern, digital AP workflow.

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While a top-tier OCR or extraction solution may remove the burden of manual keying and structure your data efficiently, true AP automation goes well beyond this. If you automate just one aspect of your AP process, you’re likely shifting the bottleneck further down your workflow.

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A best-in-class AP automation solution doesn’t stop at invoice data extraction. It also streamlines your invoice approval workflows, manages internal AP workflows for both PO and non-PO invoices, and facilitates seamless payments. This end-to-end solution will optimize every step in your AP process, eliminating manual tasks across the board instead of just in one area.

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Conclusion

The benefits of automating your invoice data extraction are clear. It's an investment that can save time, reduce costs, improve accuracy, and increase productivity.

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By harnessing these cutting-edge tools, businesses are not only addressing the challenges of manual invoice processing but also paving the way for more streamlined, accurate, and efficient financial operations.

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Want to learn more about the power of streamlining invoice capture and other key components of AP automation? Click the banner below to check out our recent webinar, The Innovative CFO’s Agenda: Driving Efficiency with AP Automation.

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*Centime is not a bank and is not authorized by any federal or state agency to engage directly in core banking activities.
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*All banking products and services available through Centime are provided by FNBO and are governed by the applicable agreements and related disclosures provided to you by FNBO. Member FDIC.
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‍*While Centime facilitates traditional banking activities (such as the acceptance of deposits or extensions of credit), these services are actually provided by our banking partner, FNBO.
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*Centime may provide support services to FNBO, as permitted by applicable law, to facilitate the delivery of its bank products and services.

**Deposit placement through ICS is subject to the terms, conditions, and disclosures in the applicable agreements. Although deposits are placed in increments that do not exceed the FDIC standard maximum deposit insurance amount (“SMDIA”) at any one destination bank, a depositor’s balances at the institution that places deposits may exceed the SMDIA (e.g., before settlement for deposits or after settlement for withdrawals) or be uninsured (if the placing institution is not an insured bank). The depositor must make any necessary arrangements to protect such balances consistent with applicable law and must determine whether placement through ICS satisfies any restrictions on its deposits. A list identifying IntraFi network bank

OCR Basics and Tools: How to Streamline Your Invoice Data Extraction

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