How Does Form Extraction Add Value to Any Organization?

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Why is form extraction so important? Let’s try to make a list of paper form types, which contain valuable data for organizations.

  • Account opening forms (Banking, Insurance)
  • Customer satisfaction forms (Retail, HORECA, Services)
  • Job application forms (All industries)
  • Proof of delivery forms (Transportation, Courier)
  • Medical record forms (Health, Medicine)
  • Complaint forms (Public sector, Aviation)
  • Registration forms (Education, Travel)
  • Surveys (All industries)
  • Maintenance Forms (Logistics, Aviation, Automotive)

These are only a few examples of most frequently used form types. The list goes on.

Now, think that almost all of these forms are filled handwritten and you need to read, understand and classify every data. You can imagine how big amount of time it takes to complete the task manually. Moreover, you need to process data properly to make it ready for use. You can use a data entry layout or tool to speed up processing, nevertheless you would have to prepare a new layout and workflow for each new form type. Even for a single input field added to the existing forms.

AI Makes It Possible to Automate Form Extraction

We are lucky that there is a cost-efficient solution for this intimidating business problem. Automated form extraction (also called; form capture or form ICR) is combining ICR (intelligent character recognition) technology with AI and thereby extract any type of data easily from handwritten forms.

ICR is the muscle of automated form processing while AI is the brain. Without utilizing AI, extracting handwritten content would be less useful. Since you need to interpret, validate, classify and integrate extracted data, AI plays an essential role in automation of form processing. Another asset of AI is the capability of processing new form layouts, which are not recognized by the system previously. This feature reduces need for human intervention and minimizes errors.


How Does Form Automation Work?

onVision Intelligent Form Capture is a cloud-based solution and it can be used through API or by Web scan. After you scan the form or take a photo of it by your mobile device, you can upload it to the platform. We can also listen an e-mail inbox or watch a folder to collect forms. Once the document reaches to the platform, handwritten data is extracted in seconds and structured output is generated in XML or JSON format.

From there on it becomes possible to use data as you wish, according to business rules and workflows. You can also employ RPA solutions to optimize any process. Thus, your organization will not only save time and money, but also improve its way of doing business and customer/employer satisfaction.

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Invoice Processing Automation with OCR

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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.

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How to Design Automated Invoice Processing Framework?

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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. 

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Why Intelligent Automation Is the First Step of Digital Transformation?

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As the amount of data companies need to process in day-to-day operations becomes larger and larger, business processes get more sophisticated and intelligent automation needs gain urgency. There are many competencies that companies have to possess to keep pace with these requirements. Digital transformation is the overall framework which can be defined as the process of using digital resources to improve existing business models and culture or creating new ones.

Intelligent Automation as a Part of Digital Transformation

One of the main goals of digital transformation of an organization is to automate operations and processes. This not only about getting faster or more profitable, but also getting able to make better decisions and becoming more strategic.

Overall, we conclude that digital transformation is a more complex type of technology-enabled business transformation, which needs to address the strategic roles of new digital technologies and capabilities for successful digital innovation in the digital world (Yoo et al. 2010). We define it as the process through which companies converge multiple new digital technologies, enhanced with ubiquitous connectivity, with the intention of reaching superior performance and sustained competitive advantage, by transforming multiple business dimensions, including the business model, the customer experience (comprising digitally enabled products and services) and operations (comprising processes and decision-making), and simultaneously impacting people (including skills talent and culture) and networks (including the entire value system).

Digital Business Transformation and Strategy: What Do We Know So Far? by Mariam H. Ismail, Mohamed Khater, Mohamed Zaki

With this perspective in mind, we can understand why intelligent automation is such an important stage of digital transformation. It is so important because it is impossible to digitize processes and operations without utilizing intelligent automation tools. Companies need to free their employees from manual work as much as possible. So that employees can become more productive and focus on high value tasks instead of repetitive, time-consuming jobs.

Handling Data with Data Extraction

As we mentioned above, the amount of data companies need to handle is getting larger. It is not easy to process such a big amount of data, especially when it is generated through many types of documents. When data is arrived in various formats and mostly unstructured, we need a solution to extract, interpret and validate data. Data extraction tools are built to meet this demand and OCR technology has been enriched by AI assets.

Since it is possible to run intelligent automation only after proper data extraction from documents, it is critical to choose a well-developed data extraction solution.

What are the Stages of Intelligent Automation?

Although requirements and KPIs for intelligent automation differ from industry to industry, there are some common principles and methodologies to be used as a guideline.

  • Data Extraction: This is the first step towards successful automation. OCR and ICR engines working through AI based software, make it possible to extract data in various formats, from any type of document.
  • Data Processing: Once data is extracted and digitized, second step is processing it. Machine learning technologies come in help at this stage. Data validation and classifying is ensured with high accuracy.
  • Data Distribution & Automation: As a final step, structured and validated data should be distributed to relevant authorities and core systems. Integration to ERP or DMS software is undertaken at this stage and final automation tasks are completed.
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Invoice Processing Automation with RPA

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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.
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Intelligent Automation as A Way of Improving Employee Happiness

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Too many companies and business leaders believe that using automation technologies is one of the smartest ways of gaining competitive advantage and profit. They are completely right; however, they overlook the human component frequently. When you run business automation technologies (RPA, process automation, intelligent document processing, data extraction etc.) within your organization, obvious benefits occur: reducing costs, speeding up operations, minimizing human error, getting more control and transparency.

All these benefits create great business results yet they can help to achieve something else, which is equally important: employee upskilling and satisfaction. If a company is able to use automation technologies to bring out the best in people, then it will take advantage of a lasting transformation of organizational structure and corporate culture.

How Does Business Automation Help Employee Upskilling?

In a recent Deloitte survey of more than 11,000 business leaders, more than 60 percent of respondents said they actively redesign jobs around artificial intelligence (AI), robotics, and new business technologies.

Robots, machines and business automation software can execute repetitive tasks much faster and more precisely than humans. Nevertheless, there are many critical skills such as innovative thinking, creativity, ethical judgement, responsibility, intuition which can be performed by only your human workers. And when people find room and time to use their skills, it is shown that they feel much better and engaged to work.

According to a recent survey, daily stress level of employees is getting higher. Intelligent automation can also help employees to cope with stress. When people have proper tools to use, they feel more secure and comfortable in terms of finishing their jobs on time and with success. 89% of employees believe that automation helped them to be more efficient on work.

Where to Start Intelligent Automation From?

It is always better to start simple. First, define what you need and specify bottlenecks of your processes. Listen your workers and involve them in decision making. Afterwards you can start looking for alternative solutions. Try to go step by step, but never miss the big picture. If you need an invoice extraction tool, for instance, be sure that it can integrate to your existing ERP or is able to streamline with a proper intelligent document processing framework.

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Invoice Capture: Promising High ROI

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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.

 

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Why To Use Cognitive Data Capture For Invoice Processing

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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.

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What Is Automated Invoice Processing?

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.
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How Does Artificial Intelligence Turn OCR Into Intelligent Document Processing (IDP)

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Digital transformation has been around almost for two decades, however there is still lots to do to overcome devastating paper work and manual document processing.  Main reason which lays beneath the fact that document processing (invoice processing, banking and financial document processing, legal document processing etc.) couldn’t reach to a higher level of digitalization is the difficulty of transforming contents of custom and arbitrary documents to structured, standardized data.

According to a recent survey, 92% of business leaders agree that companies need to enable process automation technologies. OCR (optical character recognition) technology plays a vital role in this story. It is still the best method to turn print outs into consistent digital data, which can be processed by computers. And the good news is OCR technology is improving constantly. Nevertheless, companies need more complex, flexible and yet accurate solutions than OCR in order to fulfill their challenging document management and digitalization needs.

How Does Intelligent Document Processing Work? 

 

Think about all of these various types of documents, forms, e-mail attachments, PDFs, invoices, receipts, work orders, bank and insurance statements etc. Tones of valuable data are stored in these documents, yet it needs a great deal of time and effort to reach and use them meaningfully.

 

Intelligent document processing (IDP) can be defined as a bunch of solutions come together to transform unstructured data into usable data and finally to create smooth, productive and cost-effective work flows. Most of IDP tools can be easily integrated with enterprise solutions such as ERP, CRM and DMS.

Components of IDP framework are:

  • Data capture & classification: OCR, NLP
  • Data extraction & interpretation: Deep learning, machine learning
  • Data validation & automation: AI, RPA

What Are the Benefits of Intelligent Document Processing?

 

When you run an IDP platform your business gets into a total boost. Typical and obvious benefits of IDP are:

  • Time and cost savings
  • User friendly processes and efficiency
  • Data accuracy & security uplift
  • Higher satisfaction of employers and customers
  • High quality internal project management

These benefits can be designed for a high variety of use cases in a flexible manner. One of the best assets of IDP is this flexibility, which is built on different levels of technology. For example, a medium sized exportation company can limit the solution for scanning invoices and extract invoice data to transfer to concerning parties in seconds. Besides, a large international enterprise would run AI based intelligent document processing in a multi lingual environment. And also can track, interpret and create each business process through robotic process automation (RPA) integration.

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