(IDP) Intelligent Document Processing


Intelligent document processing is the next generation of automation, which enable systems to capture, extract, and process data from a variety of document formats automatically to enable end-to-end business process automation.

What is Intelligent Document Processing?

Intelligent Data Processing (IDP), also known as intelligent data capture, is the process of intelligently capturing specific information and streamlining document processing tasks. IDP solutions transform unstructured, semi-structured information into usable data and works with both paper and electronic documents. By capturing data intelligently, it’s easy for organizations to manage information faster and more efficiently with digital document format.

IDP is a specific form of Intelligent Process Automation, where technologies such as Machine Learning, Natural Language Processing or Intelligent Character Recognition are added to the processing of documents to eliminate tasks within a process that would normally rely on human intelligence.

This is especially relevant for businesses that are receiving a high volume of semi-structured and unstructured documents such as invoices, sales orders and customer inquiries which usually can’t be fully processed using rules-based automation software.

How Does Intelligent Document Processing Work?

The IDP platform is based on a huge, pre-built database of labeled data points. It uses artificial intelligence technology, also known as transfer learning, to create a system trained on one task to be used for a related task. Transfer learning removes the need for the system to be trained on thousands of documents to achieve high accuracy.

After receiving various of types of documents from different devices, an Intelligent Data Processing system will recognize, classify, and extract important information and then direct it to the selected document workflows for review.

There are three key techniques that are applied to an IDP system: Document Classification, Data Extraction, and Data Release.

  • Document Classification: this classifies the type of document first, then defines the beginning and the end of the document. Both electronic and paper documents can be used with OCR (Optical Character Recognition) technology.
  • Data Extraction: After classifying the document, it’s time to extract valuable data from the document which will be entered into the required database or stored appropriately for future use once the information is collected.
  • Data Release: The last step is to export the data and images automatically to the required business workflows which can be used immediately for organizations to provide efficient services to its customers.

How Is Intelligent Document Processing used in Document Processing Automation?

IDP solutions enable businesses to optimize their processing of documents through utilizing DPA technologies to deliver end-to-end solutions which are more efficient, reduce manual tasks and costs.

In addition to this, IDP solutions collaborates with human operators, enabling the system to continually learn in a process called ‘human in the loop’ and thus, it can process content regardless of the format it’s received in.

The human in the loop enables the system to scale for business growth and adapt to changing content, which enables continuous process optimization.

Why Intelligent Document Processing Important?

Business data is crucial to every organization’s workflow because it facilitates the daily progress of business processes in the organization.

While 80% of business data is unstructured, it’s crucial for businesses to convert these documents into a digital format and properly categorize the extracted information.

For organizations that want to maintain control of its data and achieve higher goals, the deployment of technology like IDP into their business processes can help boost productivity, enhance customer experience, and provide more significant insights.

Intelligent Document Processing Technology Use Cases

Intelligent Document Processing technology can be used to extract and organize data across many different industries and business functions. Banking and insurance industries can greatly benefit from IDP solutions.

Banking and Finance:

  • Mortgage Underwriting: Applying IDP to mortgage underwriting automates the process, by reading the documents and extracting relevant data for input into the bank’s credit evaluation system.
  • Know Your Customer Process Automation: As part of the client onboarding process, these laws require banks to try to verify the identity of customers, as well as the risks involved in any business relationship with them.

Insurance:

  • Life Insurance Underwriting: IDP can help dramatically improve the process by taking humans out of the equation, by creating models to quickly categorize and extract data from reams of documents.
  • Claims Processing: IDP can be used to automate the classification and annotation of new claims, and route them to the appropriate SME for processing. It can also help extract important information from documents, including unstructured content such as images and hand-written notes from insurance adjusters.

Other articles related to this topic