What is IDP? What are Key Benefits of Intelligent Document Processing (IDP)?

Did you know that even in today’s digital age, most business information is still trapped in paper documents? The good news is that Intelligent Document Processing (IDP is changing the game.

Businesses handle an immense volume of documents daily, which significantly impact productivity, costs, and efficiency. Reports indicate that 95% of corporate information exists on paper, making paper-based documents a significant part of corporate memory (InfoRouter). Paper-intensive processes like manual data entry are time-consuming, labor-intensive, and prone to human errors, especially with large volumes of data. Intelligent Document Processing (IDP) has changed the game with its ability to process structured, semi-structured, and unstructured documents automatically and accurately. Organizations that handle bulk document processing can now benefit from services that integrate IDP to automate high-volume document handling, reduce errors, enhance compliance, and deliver faster, more accurate results.

What is Intelligent Document Processing and How Does it Work?

IDP combines artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) to automate the extraction, classification, and analysis of data from documents.

Traditional document processing relies on manual labor, rigid templates, and basic Optical Character Recognition (OCR) technology, which are prone to errors and lead to compliance issues, delayed payments, or client dissatisfaction. However, with digitization, documents appear in a vast range of types, structured, unstructured and semi-structured formats, and applications, extending far beyond simple text. Modern formats include PDFs, HTML, emails, and proprietary database formats, each with unique properties, and are challenging to handle manually.

IDP makes the difference by automating document-intensive processes.

Microsoft defines IDP as a “workflow automation technology that scans, reads, extracts, categorizes, and organizes meaningful information into accessible formats from large streams of data”.

Using complex deep-learning AI technology, IDP automates and increases the speed and accuracy of data processing, and makes it more cost-effective and less error-prone.

Here’s a step-by-step breakdown of how AI improves document processing accuracy:

1. Pre-processing: Documents often arrive in different formats and quality levels. IDP systems clean and prepare them using techniques like noise reduction, binarization, and de-skewing to enhance readability and ensure accurate data extraction.
2. Image Processing: Next, IDP uses computer vision to understand the document’s structure and identify key elements such as text, tables, graphs, and images. Technologies like OCR and ICR (Intelligent Character Recognition) are then applied to convert text from images into machine-readable data.
3. Classification and Data Extraction: Using machine learning (ML) and natural language processing (NLP), IDP automatically identifies, separates, and classifies different types of documents and their contents. It then extracts key information—such as names, dates, or invoice amounts—using pre-trained models, pattern matching, or Regular Expressions (RegEx). Automated data extraction ensures only relevant, structured data is captured for further use.
4. Data Validation: Once data is extracted, it’s verified against external databases and predefined rules to ensure accuracy and completeness. If any discrepancies arise, a Human-in-the-Loop (HITL) mechanism allows humans to review and correct the data. This feedback helps the system learn continuously and improve its accuracy over time.
5. Integration: Finally, the validated data is seamlessly integrated into enterprise systems such as ERP, CRM, or document management platforms. This allows for automated workflows, faster decision-making, and smoother business operations. IDP acts as a crucial enabler for business intelligence (BI) and analytics by feeding accurate, structured, and contextual data into those systems.

How Does Intelligent Document Processing (IDP) Benefit Businesses?

Intelligent Document Processing (IDP) has transformed the way businesses handle documents by automating labor-intensive, time-consuming tasks. Employees no longer need to focus on repetitive manual work to ensure quality, as AI-powered OCR integrated with machine learning handles most of the processing.

Continuous data feedback loops help the system learn and improve accuracy, reducing the need for human intervention. When human validation is required, the AI intelligently highlights only the points needing review, allowing faster and more precise verification.

Streamlines Workflows

End-to-end process automation is one of the key advantages of IDP, driving process efficiency and supporting hyperautomation. For example, records managers can manage documents contactlessly at the end of their retention lifecycle, while mailroom clerks benefit from automated sorting and forwarding of incoming correspondence.

By combining machine learning and rules-based logic, IDP automates document capture, conversion, sorting, indexing, and routing—eliminating manual effort and streamlining workflows. The result is faster, more accurate data entry, quicker access to critical information, reduced resource use, and a truly digital workforce.

Improves Process Efficiency

IDP boosts office efficiency by automating repetitive, document-heavy tasks that traditionally consumed valuable employee time. By automatically extracting, classifying, and routing information from invoices, forms, emails, and contracts, it eliminates the need for manual data entry and reduces turnaround time from hours to minutes. Digitized and indexed documents can be easily searched and retrieved, improving decision-making speed and collaboration across teams.

With AI-driven OCR and machine learning, IDP ensures precise data capture, while automated validation continually enhances accuracy, minimizing rework and compliance risks. IDP also connects with existing systems like ERP, CRM, and document management platforms, ensuring smooth data flow across departments and reducing bottlenecks in approval cycles.

Enhances Data Quality and Usability

It is estimated that on an average, about 80 percent of an organization’s data is “dark data” – meaning it is locked in emails, text, PDFs and scanned documents. By utilizing RPA and AI-based tools, IDP unlocks the value of dark data by transforming it into high-quality, structured data that is primed for analysis. By combining the data derived from paper documents with the huge amount of digital data (already available), a comprehensive data landscape can be established, significantly enhancing data evaluation and analytics possibilities.

Boosts Compliance and Security

Data entry, document sorting, and information validation are among the most repetitive tasks that cost a company both time and money. IDP automates these mundane but essential processes, simplifying compliance even with complex regulations.

Data privacy is an important concern for organizations. IDP’s impressive accuracy rate makes it the ideal solution for handling documents with high compliance requirements or those that include sensitive information such as personally identifiable information (PII) or health records. The technology stores data or information in a secure location where only authorized individuals can access it. This prevents data manipulation or misuse, and optimizes regulatory reporting.

Cost Savings

By minimizing the human effort involved in document processing, IDP helps reduce staffing costs. Additionally, storing data digitally cuts down on expenses related to printing, shipping, and physical storage. With automated data processing, organizations can complete a large volume of work in a short time—significantly lowering overall operational costs.

Scalability and Consistency

Intelligent automation solutions allow organizations to handle increasing document volumes without adding staff, maintaining consistent quality and performance even during workload spikes.

Improves Customer Experience

Customer experience and satisfaction play a crucial role in a business’s success. Consider the example of a mortgage loan application — borrowers typically need to complete and submit extensive paperwork to the bank or lender. Without automation, mortgage companies must manually sort files, verify applicant data, enter details into backend systems, and cross-check records for missing or incorrect information.

With IDP, all these repetitive tasks can be automated. Employees can quickly access and search customer data across multiple input channels, enabling faster loan processing and issue resolution. Document automation not only reduces document processing time but also improves response speed, accuracy, and overall customer satisfaction—leading to higher retention rates.

IDP is driving digital transformation in document management across various industries:

• Contract Management: Accelerates document analysis and risk assessment.
• Financial Services: Enhances loan and invoice processing efficiency.
• Human Resources: Streamlines résumé screening and onboarding processes.
• Healthcare: Improves records management and compliance monitoring.
• Government: Facilitates efficient records management and compliance monitoring.
• Education: Automates administrative tasks and document processing.

These applications not only boost operational efficiency but also ensure data consistency and compliance across sectors.

Real-World Example: How RPA-Driven IDP Transformed Loan Processing Efficiency

A leading global bank faced challenges with its manual mortgage loan processing system. Each application required staff to review hundreds of pages of documents—such as pay slips, identity proofs, and bank statements—and enter key information into multiple backend systems. This process was not only slow and labor-intensive but also prone to errors, extending loan approvals to nearly 7–10 days.

To overcome these inefficiencies, the bank deployed an Intelligent Document Processing (IDP) solution integrated with Robotic Process Automation (RPA). The system combined OCR for text extraction, machine learning (ML) for document classification, and natural language processing (NLP) for understanding unstructured data. Once validated, RPA bots automatically transferred accurate data into the bank’s core loan management system, triggering further actions in the workflow.

Results achieved:

• Reduced loan processing time from 10 days to less than 24 hours
• Improved data accuracy to over 98%
• Cut manual effort by 80%
• Enhanced compliance through automated audit trails
• Delivered a faster, smoother customer experience

By integrating RPA with IDP, the bank achieved end-to-end process automation, significantly improving operational efficiency and customer satisfaction while freeing staff to focus on higher-value tasks.

The global IDP market was valued at USD 2.30 billion in 2024 and is projected to reach USD 12.35 billion by 2030, according to Grand View Research. For organizations managing large volumes of structured, semi-structured, or unstructured data, investing in solutions that incorporate intelligent document processing is a smart choice. Automating manual document workflows with IDP can efficiency, accuracy, scalability, and compliance in document-heavy business processes.