Intelligent Document Processing (IDP) : Everything You Need To Know


How much staff time does your operation spend processing documents? Most companies devote extensive human resources to this task:

  • One major logistics company required more than a dozen employees to review and verify documents varying from bills of lading to letters of credit.
  • A leading specialty healthcare company had over 10 workers evaluating patient data and moving it between disconnected systems.
  • A top insurance company operated a sizable team of case managers to process service requests, each of which took more than four hours to identify, classify, and assign to representatives.

These highly varied companies had one thing in common: Their back-office workload was limiting productivity and, ultimately, growth. And the solution for each was the same: hyperautomation, anchored by a digital technology called Intelligent Document Processing (IDP). The Nividous hyperautomation platform leveraged its native IDP capabilities to help these companies reduce manual work by 80 to 90%, with other benefits ranging from error-reduction rates of 80% to turnaround-time improvements of 60% to 95%.

The value of automated data processing from very different business documents is clear across verticals. That explains why the IDP market is expected to grow at a compound annual growth rate of nearly 37% through 2026, reaching a global value of $3.7 billion that year. With such quick adoption, the question isn’t whether your company can benefit from this technology-it’s whether you can compete without it. This is an introduction to the new era of enterprise data processing, which, as anyone who struggles with back-office efficiency can tell you, begins with documents.

Intelligent document processing is a technology that uses Optical Character Recognition (OCR) and Artificial Intelligence (AI) to convert unstructured or semi-structured data into structured formats for analysis and/or further automation. That’s the technical definition of IDP. In the rest of this comprehensive guide, we’ll explain what these terms mean, how IDP can help your business compete, and why automated document processing technology is a cornerstone of end-to-end digital process automation. But it might be helpful to start with a concrete example of IDP at work.

IDP for Invoice Processing and Accounting Process Automation​

Intelligent automation can greatly improve accounts payable processes, and IDP plays an important role in this effort. Invoices come in many forms, from a standardized Quickbooks export to a few informal lines in an email. When you work with dozens or hundreds of vendors-and each one formats its invoices differently-it takes a lot of dedicated staff time just to move data from vendor forms into an ERP, accounting software, or both. Without AI, digital automation solutions can only work with structured data, and without AI, only humans can perform that structuring.

Luckily, AI is here, and it’s a hallmark of IDP. In the above example, IDP bots identify, extract, and organize relevant data from all those invoices, freeing the human workforce for more creative tasks-as they do in Nividous’ accounts payable automation solutions. The resulting structured data can be imported into an ERP or accounting software. Better yet, deploy Robotic Process Automation (RPA) bots to automate the whole process-something we’ll discuss in more detail later in this article.

The point is: IDP extracts relevant data from any record, regardless of layout-a capability that extends far beyond the accounting sphere. Because of its layout-agnostic ability to capture just the information you need from any type of document-from emails to images to PDFs-IDP saves billions of hours of work every year, with game-changing improvements to efficiency, accuracy, and capacity for innovation. But to begin to understand this form of intelligent data processing, you need to know the difference between structured, semi-structured, and unstructured data.

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