When using invoice OCR software to automate the business processes of the AP department, you expect certain functions to be performed. Collecting invoices from different sources, extracting data from invoices with high accuracy, reading existing and new invoice templates, full integration with ERP and accounting systems.

An invoice OCR software with these features greatly reduces the loss of time and human error caused by manual data entry, and significantly simplifies the audit and control processes.

However, OCR technology alone cannot provide the wonderful benefits we have outlined above. Considering the variety of data contained in invoices (whether in paper or digital format such as PDF, etc.) and the flexibility of the way this data is presented, OCR absolutely needs machine learning support for complete invoice automation.

Contact us if you need free consultancy about accounts payable automation. 

Invoice OCR and Machine Learning

The point where machine learning comes into play is that invoice templates can change frequently. Invoices from different countries or different suppliers, or even a new line item or table added to the same supplier’s invoice, render the rule-based invoice OCR system inoperable. For this reason, there is a need for a software that can interpret such different invoice samples by itself and that can perform data extraction without human intervention. A software with this feature should have a strong machine learning infrastructure. Only in this way can the invoice OCR system be fully automated.

For example, let’s consider an invoice that was previously processed with the invoice OCR system. Things will get complicated when the supplier that sent this invoice changes the stock system and switches to a new system in product coding. A new data field added to the product table cannot be processed by an invoice OCR system that is not supported by machine learning, even if all other fields of the invoice remain the same. However, an OCR software using machine learning can make sense of such new data types and can process even an invoice that it has never encountered before, thanks to its comparative analysis skill.

Cloud Access Is Indispensable for Invoice OCR Systems

Invoice OCR software is expected to fulfill some conditions in terms of user experience and access possibilities, as well as technical features. The first of these is that the software is cloud-based. Software running on cloud technology allows employees to work independently of time and space.

This feature also simplifies user management and eliminates installation/hardware costs. Another advantage is that the number of invoices you process does not matter in cloud-based invoice OCR systems, such as onVision Invoice Extraction.

Integration with ERP

The last stage of AP automation is, of course, the transfer of data to the ERP or accounting system at the point where invoice processing is finished. This process should also be performed automatically by the invoice OCR software. In order to fulfill this task, the OCR software you will use must have various and smoothly working connectors. Integration protocols developed for ERP systems such as SAP, MS Dynamics will enable a seamless integration without interrupting your workflow even for a day.

Paper invoices still occupy a huge place in day-to-day business operations. Accounts payable team needs to collect, process and distribute invoices properly to manage payments. When performed manually each step of invoice processing takes a lot of time and usually cause delays and bottlenecks. There is an effective solution of this frequent problem: invoice processing automation through invoice OCR.

How to use OCR for Invoice Automation?

 

The starting point of digitizing a paper invoice and thereby automating invoice processing, is scanning or visualizing printed or handwritten texts. OCR (optical character recognition) helps us to turn data of paper invoices (or PDFs) into digital units. However, if there are handwritten contents, special characters, non-uniform or distorted parts then OCR won’t suffice to advance. In this case, ICR (intelligent character recognition) is the proper tool to use.

There are critical points at this stage. It is not always easy to handle unstructured data. First obstacle is new invoice types. If you use a rule-based OCR, it can’t extract data from layouts which are not included to system previously. In such a case, human intervention becomes necessary. It is clear that we can’t call it an automated invoice processing, if we need human supervision every time a new layout is arrived.

Machine Learning Supports OCR

 

To solve this problem, onVision utilizes deep learning. Our invoice extraction tool uses a powerful machine learning algorithm to adapt itself to unfamiliar invoice formats. System is always ready to learn by itself and interpret any type of document to understand relevant data fields, line items etc.

Another significant difficulty with OCR technology is accuracy rates. Even the most advanced OCR engines struggle to offer an accuracy rate over 80%. Shadowy or noisy texts can only be extracted properly by the help of higher technology. That’s why we strengthen invoice OCR with machine learning.

Once we have a digitized data set, we are ready to process invoices. Following the first step, artificial intelligence has to interpret data and classify it according to business rules. After validation is realized, AI parses data and JSON output can be easily processed on API or server. Hence, we can easily integrate with any ERP or DMS software.

Language support and cloud access for invoice OCR

onVision Invoice Extraction support 119 languages for printed invoices and can also extract data from handwritten invoices in almost every language using Latin alphabet. Cloud based platform offers a great flexibility and speed. User management and accessibility becomes so easy that AP team can work from anywhere, any time. You can use onVision by buying credits and pay as much as you use.

Automated invoice processing is extracting data from incoming invoices and transferring it to any ERP or financial system within seconds. To achieve this task, companies need a well-designed framework which works seamlessly.

Processing invoices and payments is a complex and a very time-consuming process with hundreds and thousands of invoices arriving in various formats (e-mail attachments, PDFs, paper based etc.). If accounts payable team is working manually to process invoices, errors and delays occur unavoidably.  For this reason, using an invoice automation software creates great benefits for companies.

How to Automate Invoice Processing?

Invoice processing as a business function, may seem relatively simple job with a low priority. It is not the case though. First of all, invoice processing has a multi-channel workflow and it sits in the middle of three critical processes: operations, production and finance. How can a company manage its supplier chain without running a fast, productive and error-free accounts payable operation? How is it possible to keep production lines (or services) working without managing your supply chain properly?

With its important role, invoice processing workflow needs to be improved. To do this, invoice automation solutions have been developed for the last decade. Let’s dive in details and see how to automate invoice processing.

Invoice Automation Basics

There are four main steps of invoice automaton.

  • Digitizing physical invoices (scanning)
  • Extracting data from invoices (invoice OCR). Powerful OCR and ICR engines let us to extract data from files in various formats such as PDF, jpg, TIFF.
  • Interpreting and analyzing the invoice content. AI and machine learning technologies come to help at this stage. Pre-trained invoice automation solutions are able to understand unstructured or nonuniform contents and classify them. No human intervention is needed.
  • Integration to core systems such as SAP, MS Dynamics, Oracle etc. (connectors and APIs)

An intelligent invoice automation software can handle these four steps seamlessly and help your company to save time, money and valuable other resources.

Invoice OCR or Cognitive Data Capture?

OCR (optical character recognition) is the technology which makes automated invoice processing possible.  When you scan a physical invoice or take a photo of it, OCR turns optical characters into digital data. ICR (intelligent character recognition) is the advanced version of OCR. It can even turn handwritten texts into digitally usable data.

However, invoice OCR does not suffice to fully automate invoice processing. It is mainly because, OCR software without an AI component can only extract data from pre-defined templates. When you add a new vendor to system, rule based OCR software is incapable of extracting data from new invoice layout since it doesn’t know how to process fields, line items, shapes etc.

Cognitive data capture, on the contrary, uses artificial intelligence to read invoices. Two key features of cognitive data capture are; ability of AI to learn by itself and ability to understand patterns and layouts which are not seen by it before.

Thanks to these two key features, cognitive data capture doesn’t require human supervision or continuous controlling. So that it really automates invoice processing and saves huge volumes of manpower. You can learn details about onVision Invoice Extraction solution here. 

While application areas of RPA (robotic process automation) are expanding steadily, one of the fastest growing area is back-office jobs and accounts payable (AP) operations. Companies who need to process high volumes of invoices periodically, suffer from complications of manual invoice processing.

Invoice processing is a key joint stage of many business operations. AP department needs to extract data from various invoice types and formats (PDF, printed etc.) and transfer these data into their own core system only after they verify the content. If this stage takes long to step further and discrepancies occur frequently, which is unavoidable during manual work, financial workflows start to tremble and fall.

How Can RPA Help to Optimize Account Payable Operations?

 

There are three main steps of AP automation through RPA:

  • Monitoring incoming invoices: via e-mail attachments, folders, servers
  • Invoice capture: extracting data with high accuracy (see onVision’s product)
  • Validation/approval: evaluation of invoice content by AI

You can see details of these steps, and most frequent use cases in Simplilearn’s video below.

 

 

Outcomes of Invoice Processing Automation

  • Among many benefits of automating invoice processing, we should emphasize key ones.
  • Shorter cycle time for AP operations and due to it better financial planning and internal harmony.
  • Compliance and audition requirements can be met easily, because RPA handles repetitive tasks which are prone to error with high precision.
  • Companies streamline financial part of vendor management process and it leads to several improvements from production to customer satisfaction.

There are two underlying reasons why invoice capture has become an essential tool for companies in recent years.  First and foremost, invoice capture contains two powerful and effective technologies, which serve companies to easily automate processes. These are Optical Character Recognition (OCR) and machine learning. The other reason is that by automating one of the most time consuming and critical processes, invoice capture promises high ROI rate.

Invoice Capture Combines OCR and Machine Learning

Invoice capture (also called invoice extraction or invoice OCR) means extracting data from invoices so that invoice processing can be automated. It is significant to automate data extraction and invoice processing because there are tones of different invoice formats and these formats involve many unstructured and nonuniform data types.

invoice capture detail

Using OCR (and also ICR) to recognize invoice content and machine learning to understand the context of that content and validate each data and item makes the difference. In this sense, invoice capture goes beyond OCR. OCR by itself is incapable of automating invoice extraction, because it needs templates and rules to work properly. This means that every time OCR meets a new format, a different line item, complex tables or a low-quality invoice a human operator’s supervision is necessary.

How to Choose Invoice Extraction Solution?

We can classify invoice extraction solutions under 3 groups:

  • Template based solutions. (OCR level)
  • Pre-trained machine learning solutions. (OCR + machine learning)
  • Continuous training AI solutions. (OCR + machine learning + AI)

The last group is your best choice to fully automate invoice processing, for the reason that these solutions are; format/document agnostic, can learn by themselves, have very high data confidence ratings.

You can learn more about continuously trained onVision Invoice Extraction solution. 

High ROI of Invoice Capture

Companies processing 300-500 invoices/month and whose invoice processing is not automated yet can reach to a $1500-2000 cost saving amount per month. *

*This calculation is based on various variables and therefore may differ from company to company. We took APQC benchmark report data as an average.

 

One of the most promising areas for digitization of business is cognitive data capture. Among many applications of cognitive data capture, invoice processing is getting ahead because of fast and effective results that companies get.

In every company, accounts payable department spends most of its time to process invoice data. Invoice processing consists of a series of steps, which must be followed and executed strictly. Data collection, validation, approvals, payment terms and synchronization of all these steps with an ERP or accounting software can easily lead to bottlenecks in any organization.

Instead of putting that much load onto your accounts payable team, you can start using a solution that uses cognitive data capture in order to automate invoice processing.

What is cognitive data capture?

 

Cognitive data capture performs two main functions: Data extraction and data validation/correction. Automation of these two steps are vital for invoice processing, because there are various invoice formats with respect to metadata and you often encounter with several unstructured and non-uniformed data.

As the first step, onVision Invoice Extraction product uses a mixation of OCR and ICR to recognize contents of invoice and extract data with a high level of accuracy. Following this step, machine learning procedure begin to show off its abilities. Each line item of the invoice is analyzed and interpreted by AI. Based on confidince score rating and spatial referencing method, data validation/correction is finalized.

 

5 Benefits of Using Cognitive Data Capture for Invoice Processing

  • Traditional OCR tools can solve some basic problems of invoice processing, nevertheless OCR needs rules and templates to work properly. This means that a human operator needs to define rules and templates for each new invoice format. On the contrary, cognitive data capture is document-agnostic and can learn and operate by itself without any supervision.
  • Automation of invoice processing through cognitive data capturing reduces costs (time, money, energy) and enhances efficiency of the relevant business process.
  • Increased level of control and transperancy is another significant benefit. You can easily prevent fraud, duplicates or any possible malicious attempt, by using cognitive data capture for invoice processing.
  • When you automate invoice processing by cognitive data capture, it works as a catalyst for other enterprise software solutions and business processes. Supply chain management, customer relations will benefit and your ERP system will perform much better.
  • Digitization level of a company depends on the ratio of its paperless and touch-free processes. If you aim at increasing digitization level of company, cognitive data capture is your best servant.

Learn about onVision Invoice Extraction product.

Invoice processing handled by accounts payable department in a company is one of the most time-consuming business functions, which also needs to be performed with high accuracy. Since invoice processing consists of consecutive steps such as; data entry, approvals, transferring to financial system, recording & archiving, payment etc. many companies prefer to automate invoice processing in order to save time and streamline their workflows.

Transforming Invoice Processing

Let’s think about steps of traditional/manual invoice processing and see how to transform these time consuming, repeating steps into a digitalized business process.

  1. The first step of invoice processing is the reception of invoices, which come in a variety of formats. Accounts payable (AP) team needs to handle data entry for all of these different invoice types. In contrary, automated invoice processing is able to extract every type of invoice data in a blink of an eye.

 

  1. Following data entry, invoices are supposed to be distributed for review and approval. If you use paper documents or even Excel sheets or PDFs throughout this step, it is very likely to come up with delays and errors. Automated invoice processing prevents these undesired outcomes by submitting invoice data automatically to your ERP or accounting software.

 

  1. Payment and audition as final stages are also performed effortlessly in automated invoice processing. AP team can anytime reach invoice data easily and quickly, and it is possible to integrate invoice automation with almost every enterprise software solution.

 

 Benefits Of Automated Invoice Processing 

 

  • When you use invoice automation tools, you add more control to and speed up your accounts payable operations. Starting from data entry, human errors will diminish drastically and you will save up to 90% of the time spending for traditional invoice processing.
  • Another significant benefit of invoice automation is increased level of transparency and auditability.
  • One of the most overlooked benefit of invoice automation is increasing data quality and the enhanced ability of acquiring insights.
  • Last but not least, employer productivity and satisfaction will get on top by invoice automation.