Intelligent Document Processing is a workflow automation technology that scans, reads, categorizes, and extracts meaningful information into accessible formats from large streams of data.
Organizations are dealing with huge data on a daily basis. Thus, it makes them difficult to manage and extract which data is useful and which one is not!
Managing such data can be a cost-effective as well as time-consuming process. This is where Intelligent Document Processing comes into the picture. This technology can process various types of documents including PDF, word documents, spreadsheets, and more. The main goal of IDP is to extract meaningful data from the documents without human intervention.
How does Intelligent Document Processing Work?
Here are a few steps to intelligent document processing;
Intelligent document processing (IDP) employs a variety of methods to extract and understand data from documents before converting it into a usable format:
Document classification: IDP uses intelligent document recognition technology to categorize documents based on their existing kinds.
Document processing: IDP can flip, rotate, and clean documents in preparation for processing.
Data extraction: IDP employs machine learning (ML) models to extract information from documents.
Data validation: It compares extracted data to internal and external data to ensure its accuracy.
Data integration: Document processing using automation connects data into tools and applications like as BPM, RPA, and CRM.
IDP generates output files in standardized formats such as JSON or XML.
What are the advantages of Intelligent Document processing?
Every industry wants to do more while also wanting to save time with minimal resources. At the same time. Businesses are also focusing on boosting customer experiences and employee productivity, as key to improving ROI and retention.
Direct cost reductions.
Reduce expenses by significantly lowering the price of processing big amounts of data.
Increased straight-through processing (STP).
Reduce the need for knowledge workers to process documents manually.
Scale.
The volume of digital documents is always increasing; IDP provides a scalable solution for processing massive data volumes quickly and accurately.
Process efficiency.
Enables complete automation of document-centric procedures.
Accuracy increases.
AI can result in fast and large increases in data accuracy.
IDP Applications in various Industries
Banking & Finance
Automate loan applications, digitize paper records and extract information from financial documents like invoices and bank statements.
Healthcare
Digitize patient information, process insurance claims, and extract data from medical forms to increase billing accuracy and speed.
Insurance
Automate claim processing, extract data from insurance documents and enhance fraud detection.
Manufacturing
Automate document-intensive activities including supply chain management, invoicing processing, and quality control.
Accounting & Finance
Automate invoice processing, cost management, and financial report analysis to speed up tax filing and auditing.
Human Resources
Streamline employee onboarding procedures, manage resumes and job applications, and extract information from HR forms.
OCR vs. Intelligent Document Processing (IDP)
While both OCR (Optical Character Recognition) and IDP (Intelligent Document Processing) involve extracting data from documents, they serve different purposes and offer varying levels of sophistication.
OCR (Optical Character Recognition)
Purpose: Converts images of text into machine-readable text.
Functionality: Recognizes characters and symbols in images and transforms them into editable text.
Limitations: Primarily focused on basic text recognition. Struggles with complex layouts, handwriting, and non-text elements.
IDP (Intelligent Document Processing)
Purpose: Automatically extracts data from documents and understands their context.
Functionality: Combines OCR with advanced AI techniques like natural language processing (NLP) and machine learning to:
Understand document structure: Identify headers, footers, tables, and other elements.
Extract relevant data: Accurately extract specific information, such as names, dates, and amounts.
Validate and enrich data: Verify extracted data against predefined rules and databases.
Integrate with downstream systems: Automatically route documents and data to appropriate systems.
Advantages: Higher accuracy, ability to handle complex documents, and seamless integration with other processes.
In summary, OCR is a foundational technology for extracting text from images, while IDP builds upon OCR to provide a more comprehensive and intelligent solution for automating document-based processes. IDP offers significant advantages in terms of accuracy, efficiency, and integration capabilities.
If you’re looking for best agency for document processing using automation, contact Werq Labs!