Intelligent Document Processing: Benefits, Key Technologies, and Use Cases

Ashutosh Saitwal
Ashutosh Saitwal

Founder CEO - KlearStack AI

Table of Contents

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Documents are the crux of every business. From bills, emails, invoices, etc., every document is critically essential to keep track of important data. These days, organizations are using Intelligent Document Processing (IDP) to transform the way they deal with data. 

Manually organizing and maintaining these documents is laborious, time-consuming and tedious. As paperwork increases, you’ll need more employees to handle this which increases costs significantly. 

In order to manage document workflow, document processing is the most crucial step. Document processing involves converting physical documents (paperwork) into digital and editable data. 

As we have stepped in the 5th generation of computers, document processing has become intelligent and smarter. This generation of computers are capable of using artificial intelligence (AI), machine learning (ML) , natural language processing (NLP), etc. 

When AI is integrated in document processing, it leverages machine learning (ML), NLP and OCR (Optical Character Recognition) to automate extraction of data, classification and validation, minimizing human intervention significantly. This is known as Intelligent Document Processing (IDP). 

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What is Intelligent Document Processing (IDP)?


Intelligent Document Processing (IDP) automates the process of seamlessly identifying and organizing important information/data from unstructured and semi-structured documents. This makes it easier for your organization to manage and maintain documents by reducing the need to enter data manually and process it further.

Intelligent Document Processing takes the help of AI-based technologies like Machine Learning(ML) and Natural Language Processing(NLP), Optical Character Recognition (OCR) and Robotic Process Automation (RPA)  to extract, interpret and process data from various unstructured documents.

According to industry research, more than 80% of data within any organization is unstructured. These documents can be in various forms- emails, text, PDF or scanned documents, etc. This means that we need a robust tool to process these documents without any human involvement.

With Intelligent Document Processing, you can easily and automatically collect, classify and extract data across all types of documents.


Key Technologies of IDP


  1. Optical Character Recognition (OCR): This technology focuses on recognizing and scanning image-based or handwritten text into machine-readable text.It reads different types of documents, such as scanned paper documents, PDF files, or images, and converts it to editable and searchable data. Due to such capabilities, it has become a fundamental component of IDP.For instance, when you scan an invoice, OCR reads it as an image and then converts into text so that you can copy and edit it. If you have paper documents, it can scan the document and convert it into a digital file which can be easily copied and edited.
  2. Natural Language Processing (NLP): NLP plays a crucial role in IDP as it helps in understanding human language. It allows the software to analyze and interpret unorganized and unstructured information such as symbols, sentiments, etc. This data is usually seen in email texts, customer support tickets, or other textual formats.NLP helps IDP systems to understand the context and extract relevant information from documents.For instance, When you receive an email, NLP helps the IDP system recognize the key information within it, such as dates, names, and context.
  3. Machine Learning (ML) and Artificial Intelligence (AI): ML and AI technologies are used in IDP systems to enhance data extraction accuracy and automate document processing tasks. These technologies enable the software to continuously learn from data patterns and  adapt to new document formats. It continuously enhances the accuracy and efficiency of data extraction and processing.ML and AI are like the “learning assistants” of the IDP system. They continuously keep learning and adapting over time. Just like us, these learning assistants get better at a task through practice.  These technologies improve the IDP system’s accuracy in recognizing and extracting data from your documents over time.
  4. Data Extraction and Classification Algorithms: These algorithms are designed to identify and extract specific data points such as names, dates, or amounts. They also help in sorting out your documents by using predetermined categories.Think of these algorithms as “information detectives.” They scan documents and identify specific details like invoice amounts, due dates, or customer names. Additionally, they can categorize your documents into different groups, making it easier to organize and process them efficiently.
  5. Robotic Process Automation (RPA): RPA technology is often integrated with IDP solutions to automate repetitive tasks involved in document processing. It helps in streamlining workflows, and reduces the need for manual intervention. This helps in optimizing the overall operational efficiency within your organization.Think of RPA as a “virtual assistant.” It can automate repetitive tasks, such as sorting and routing documents, just like a human assistant would do. RPA ensures that the right documents are directed to the right departments, reducing the need for manual efforts.These technologies work together to enable IDP systems to efficiently process, interpret, and manage various types of documents. This makes it easier to work and saves time and effort in the long run as well.


Intelligent Document Processing Workflow


Before using an Intelligent Document Processing tool, you should be mindful of two key considerations.

1. Let us first figure out the kind of technology we would require to extract important data from the automated document processing. This depends upon the type and layout of the document, since:

  • Structured data would require less advanced tools and as it is mainly template-based. Its extraction can be easily automated using Robotic Process Automation (RPA).
  • The biggest challenge with unstructured documents is its extraction. It requires a more sophisticated technology. This is because unstructured documents prevent the use of regular expressions (Regex) or template matching techniques (they are usually template-less).

2. The next thing you should consider is how your data comes in. If you are a medium or large-sized organization, data is received in different formats such as paper documents, faxes, attachments of emails, scanned PDFs, etc.

Now that you understand key elements of integrating the IDP into their workflow, let’s find out how Intelligent Document Processing actually works.[/vc_column_text][vc_column_text]

How does Intelligent Document Processing work?


When organizations integrate Intelligent Document Processing into their workflow, the IDP system recognizes, classifies and extracts information and organizes that information with minimal involvement of employees. The process involves five key phases: 

1. Document Pre-processing

The initial phase of intelligent document recognition is document preprocessing. It takes help from OCR and machine learning to recognise raw data. In this stage, OCR enhances the image quality to ensure high-quality data gets processed.

2. Document Classification

This step involves the classification of your documents intelligently by identifying the type of the document such as invoices, bill of lading, purchase orders, pro forma invoices etc. This stage uses Computer Vision (CV), Natural Language Processing (NLP) and Machine Learning (ML) technology together.

3. Data Extraction

This is the most important step in the process of Intelligent Document Processing. It extracts valuable information from documents.

4. Validation

Validation of data is a crucial part of IDP. It helps you detect inaccuracies from the extracted data. Certain rules get integrated with the IDP uses so that any inaccuracy could be detected. If any issue is detected, it flags it for human review.

5. Integration

Once all the above procedures are completed, the final data can now be fed into your organization’s document repository or your cloud database. 

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Intelligent Document Processing Use Cases


Intelligent Document Processing can be implemented in various industries that regularly deal with unstructured data and documents. 

Here are some of the industries where IDP plays a significant role in improving productivity

1. Accounting

Accounting is one sector that generates a heavy amount of paperwork and physical documents such as:

  • Invoices
  • Bills
  • Contracts
  • Receipts, etc.

Maintaining and organizing all these documents would result in lesser efficiency and reduced productivity.

Using intelligent document processing (IDP) in the accounting sector can reduce the processing time, get rid of human errors and lower processing costs.

With accurate data processing, late payments are less likely. It also enables you to capitalize and build revenue.

2. Foreign Currency Reconciliations

Intelligent Document Processing (IDP) not only makes your reconciliation process easier, it also makes it faster. Moreover, this is done without compromising on accuracy.

IDP can smoothly and efficiently do repetitive tasks like transaction matching. This offers you the capability to focus on the open entries and exceptions that specifically need additional attention. This generates more quality time for your team to work on important activities.

3. Law and Legalities

Legal service providers deal with processing a plethora of documents every day. Some of the main documents include:

  • Archiving and auditing documents
  • Mergers
  • Acquisition-related documents
  • Property filings
  • Compliance regulation documents, etc.

Majority of these require complicated paperwork at each stage. Apart from this, you may find yourself referring to large amounts of information in the midst of working on a case.

The paperwork for your client/s is often handled by an associate manually and hence is prone to errors. Having an automated system that uses IDP to manage data and documentation maintains security and improves the quality of work. It also enables your associate to assist you and work on other prioritised tasks.

4. Healthcare and Medical Records

In the healthcare industry, maintaining records of patients is cardinal. As every minute is crucial and it is important to have easy access to information in cases of emergencies. 

As a doctor, if you need to access a particular file, it becomes a task to go through all the paperwork and find exactly what you’re looking for.

With the help of Intelligent Document Processing, all medical records can be extracted from various reports of patients’ medical history and only relevant information can be accessed when required.

5. Employee Reimbursement Claims and Fraud Detection

Company employees make fraudulent claims that charge a lot to the company. Manual reviews and audits can miss these false claims and expenses. Sometimes, multiple claims are made for the same bills.

These claims may be part of a mistake or intentional fraud. But ultimately, it could cost a lot of money for your company. 

Intelligent Document Processing helps in preventing employee expense frauds as it extracts the data from the employee expense documents. It goes through fraudulent entries and highlights the inconsistencies in the claims submitted by the employees.

This fast-tracks the disbursements and cuts out rejected claims. As a result, it helps your business save a significant amount of cash outflow that would otherwise be invested in manual efforts. 

6. Trade Finance

As global trade is projected to have high growth, trade finance continues to be a significant pillar of the bank’s business model. Although the revenue growth outlook is promising, organizations need to optimize their trade finance business to maximize profitability.

Trade finance is mainly paper-based and labor-intensive. Due to this nature, trade finance processes are highly focused on documentation and checking.

This usually results in a longer turnaround time, high handling, storage costs, and error rates due to manual document verification. It also presents more operational risks due to staff turnover. 

7. Supply Chain Management

According to Gartner, up to 50% of B2B businesses globally will be processed and paid without manual intervention. In supply chain companies, the main problem with invoice processing is the complexity of semi-structured documents. This is coupled with a lack of extensive Intelligent Document Processing capabilities. Intelligent Document Processing plays a huge role here. 

IDP can match data from varying systems and organize it in an understandable way. These solutions can make end-to-end processes simple. Such as:

  • Purchase-to-pay
  • Order-to-cash
  • Record-to-report, etc.

Improving processes and getting rid of tasks that do not add any significant value may offer extra savings. [/vc_column_text][vc_column_text]

Benefits of Intelligent Document Processing


1. Increased productivity

The main advantage of automation of business processes is that it improves overall productivity. This helps in:

  • Eliminating manual intervention
  • Capturing, converting, sorting, indexing data from a document with a single click, and directing it  to its destination
  • Supporting your organization to have an effective workflow

2. Optimized Savings

Companies that have adopted the intelligent document processing (IDP) technology into their workflow have observed a significant changes like:

  • Decrease in processing time
  • Decrease in labor costs by up to 50%
  • Reduced operational cost 

3. Reliability and Accuracy

Intelligent Document Processing helps in improving the quality of document processing. It also significantly decreases the margin of error, especially in fields where attention to detail is the most important. It helps in:

  • Reducing human error significantly
  • creasing employee productivity
  • Optimizing operational workflow

4. Simplified Compliance

Intelligent Document Processing is a secure technology. It: 

  • Maintains data privacy
  • Protects data from being misused or manipulated
  • Gets access only by authorized personnel

5. Scalability

The scalability of the Intelligent Document Processing is also excellent. As it: 

  • Applies to multiple applications in multiple areas
  • Easy to integrate
  • Serves as a platform for an integrated framework
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How to Choose the Right IDP Solution for your Business?


1. Assess Your Data Processing Needs

Data Format and Structure: 

Identify the formats in which your data is received or stored. Then, determine whether your data is structured (organized in a specific way) or unstructured (does not have a specific format).

Data Volume and Automation Requirements: 

Note the volume of data you receive and the frequency of its arrival. Define how much of this data you truly need to automate for efficient processing.

2. Identify Ideal Document Candidates for IDP

Once you know the areas that need IDP integration, identify which documents are most time-consuming to process manually These are prime prospects for IDP.

3. Asses and Compare IDP Software Options

Accuracy and Improvement Potential:

Check the accuracy of the IDP software as compared to human errors and find the potential for improvement over time.

Technology and Data Handling:

Determine whether the IDP technology is template-based or it can easily handle complicated and unstructured data. Confirm if the software can read and understand the various types of data and documents  used in your organization.

Technology and Data Handling:

Determine whether the IDP technology is template-based or it can easily handle complicated and unstructured data. Confirm if the software can read and understand the various data and document types used in your organization.

Integration and Scalability:

Check if the software readily integrates with your preferred business tools or if it can be customized to fit your requirements. Ensure that the IDP solution can handle your current data volume and can be scaled to accommodate future growth.

Pricing Comparison:

Compare quotes from different IDP vendors to gain a better understanding of pricing and determine the most cost-effective and optimal solution for your business.[/vc_column_text][vc_column_text]

Parameter KlearStack ABBYY Flexicapture Adobe Acrobat Pro DC ReadIris Kofax
Accuracy 99% 94% 97% 99% 98%
Pricing Starts from 10,000 to 100,000 Pages/Year.  Starts from $99/year Starts from $12.99/mo $844 Starts from $3,500 for 100,000 pages per year
Integration RPA, Quickbooks, API Alteryx, Bizagi, Pegasustems, Blue Prism, UiPath, SAP, m-Files, SharePoint, Laserfiche Salesforce, Zoho CRM, and Microsoft Dynamics 365. Arabic/Hebrew Scripts, Asian CJK OCR, Desktop OCR, Excel OCR, Farsi/Persian/Iranian, IRIS Third-party AI solutions and open source ML tools such as Python, Webservices, .NET, SOAP and REST

Are you ready to transform the way you handle documents? Klearstack is here to guide you on your path to document processing excellence. 

KlearStack is an intelligent document processing (IDP) solution and one of the best software for accounts payable. KlearStack leverages OCR technology to scan documents such as credit notes, invoices, etc. 

The tool is built on advanced technologies such as artificial intelligence (AI) and machine learning (ML). With these technologies’ help, the tools extract the data from the document with 99% accuracy without human intervention. It is easy to integrate with RAP, QuickBooks, and APIs. 

It eliminates manual data entry, making the accounts payable process efficient. It supports 15+ document types. Its model is so advanced that even if you give it a completely new document, it processes it significantly more accurately than other solutions.

Why Should You Choose KlearStack?

  1. Achieve 99% Accuracy 
  2. 90% Cost Cut Down
  3. 20x lower Set-Up Cost
  4. Time-Saving
  5. Reduced Errors
  6. No Human Intervention

Save time and labor costs by adopting to KlearStack! 

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