Are you still manually processing your invoices?

Are you still manually processing your invoice

Invoice processing is critical to the Accounts Payable (AP) department of any business operation. Still, many businesses are stuck with traditional, slow, and inefficient invoice management solutions. If you look at AP processing today, there are a lot of companies processing their invoices manually within their accounting team or with the help of a legacy OCR engine with not-so-good results.

Today, when the world is offering AI-based solutions with advanced capabilities of machine learning and deep learning, what is limiting businesses from evolving? What are the pros and cons of manual processing? What are the first steps toward invoice process automation or Intelligent Invoice Processing? Let us try to find answers to some of these questions.

Exponential Processing

Time is one criteria used to assess any service today. The faster you deliver results, the more successful you are. Take the case of bank payments. Traditionally, bank payments and transfers were done through checks and paper-based documents, and it used to take a few hours or days to reflect the payment in the debtor’s or creditor’s account. Today, with electronic settlements, payments are just a matter of a few seconds. So, what difference have these instant payment transfer technologies brought to the world? Among the many benefits are transaction speed, increased security without the need to carry cash, efficient real-time record keeping, and customer convenience where transactions can be performed remotely from home.

Similarly, when you process invoices manually, the number of human resources you have to employ is high with the expected errors and duplication of efforts. Just imagine the time you have to spend to go through the invoice, understand the fields or data, and then manually process and feed the documents or data into your AP system.

Data Points

There are always a few data points or fields within invoices that are critical and their accuracy is essential. In manual processing, it is a daunting and time-consuming task to manage as you will have to implement multiple reviews and checkpoints and invest more resources for those fields.

For example, an invoice number or total payment is expected to be a critical data point as compared to say a description field. In this case, you have to invest additional resources to ensure 100% accuracy in extracting the invoice number or total payment amount.

IDP solutions offer incredibly high accuracy. Even though 100% accuracy for all data points right off the bat may be ambitious, it makes a huge difference for most businesses if their critical data points are 100% accurate in a few months from initiation.

For example, it may work for you if your invoice number and the total amount are extracted accurately but your description is extracted with 80% accuracy. With IDP solutions, you can define a confidence score for each data point based on the priority or criticality.


When you talk about invoice extraction, there are many fields with varying importance that you want to extract. The fields may include information such as line items or complex tabular data, which are more complex than other information such as key-value pairs or field or header-level data. It becomes even more complex when documents are distorted or line items are merged or spread across pages. This results in delays and errors and to manage these inefficiencies, you may have to employ more checks, which eventually boils down to more resources and cost.

IDP makes invoice processing a seamless experience even when handling complex information, such as table extraction. Today, most of the leading IDP solutions are enabled with proprietary ML algorithms to extract multiple tables with high accuracy within a few seconds, which is usually a fraction of the time required during manual processing.

As compared to an automated system, manual extraction is error-prone as humans are involved in gathering information. One overextended human has the potential to cause irreversible damage, and unlike intelligent machines, humans do get tired.

For example, during manual data entry, an input value for the amount 1200.50 may be entered as 120.05. Similar human errors are high in manual processing, especially with omissions and spelling. Moreover, ensuring the accuracy of critical data points, such as invoice number or total amount, requires an even greater investment in manual efforts.

Automated IDP systems pick exact values from documents, minimizing spelling and omission errors. Moreover, IDP systems are driven by AI technologies and machine learning algorithms and they learn faster from corrections. A feedback loop mechanism is usually available in leading IDP solutions to ensure that the system is constantly trained and matured to provide you high accuracy, as good as 90% or more within a few months of operation.

In the long run, manual processing requires more skilled humans, processing accuracy is not that good, and more importantly, the processing time remains high. Effectively, this makes your invoice processing not only less competitive but also an expensive option. Moreover, if you have invoices in multiple languages, you may need to employ expensive language experts.

When you invest in automation, and specifically in IDP, you cut down on a lot of inefficiencies and ensure that you have an efficient and cost-effective solution for the future. Additionally, most of the IDP solutions support multi-language processing. Infrrd for Invoice can process invoices in more than 20 languages.

Oversight Detection

Another common issue is some vendors may mistakenly raise a duplicate invoice. For example, a vendor raises an invoice on the 1st day of a month, and as a reminder, raises the same invoice on the 10th of the same month. They may not raise it as a duplicate, but just as another invoice. It is a cumbersome process to detect duplicates when invoices are manually processed unless a specific mechanism is there in your CRM, which again requires additional resources. There is also a possibility that the duplicate invoices go undetected and two payments are made for the same invoice.

Unlike manual invoice processing, detection of duplicate invoices is a simple task for IDP solutions. It can be either taken care of by setting up a simple business rule, which is available in and accessible from the user interface of most of the leading IDP solutions, or IDP vendors may be able to configure an automated detection feature for duplicate invoices.

Cost-Benefit Analysis

An important aspect of IDP is that it can perform a cost-benefit analysis to help you prioritize key invoices. Let us consider an example of a tax recovery scenario where your primary responsibility is to help your customers recover tax, such as value-added tax (VAT), and claim 10% of the recovered amount. There may be a huge number of invoices that may be available for you to process. However, you need to choose those invoices that provide you with cost benefits. Let us say if the VAT amount is a negligible one in an invoice, for example 100 dollars, it is not worth your time to process this invoice to gain the 10 dollars at the end of the day. Similarly, there are several such areas in invoice management where it may not be worth investing the human effort. With IDP, you can detect whether an invoice is worth your effort, saving you a great deal of resources and cost.

What is the right invoice processing solution for me?

Regardless of which solution you pursue, you should choose an IDP partner who addresses maximum challenges in manual processing. If you are not yet there in the world of automation, it’s time you think about initiating your IDP journey to stay competitive and be part of the rapidly-evolving AI space. And, if you have already started your IDP journey, ensure that your IDP partner offers a mature solution , which is exposed to a lot of variations but still has exponential speed and high accuracy in document processing.

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Infrrd has been offering AI as a Service since inception. Their focus is on developing faster Enterprise AI platform using AI, ML & NLP-