Intelligent Document Processing: The Complete Guide

Key Article Takeaways

Intelligent Document Processing (IDP) follows workflow to transform unstructured documents into usable business data. Each stage plays a role in capturing, classifying, and validating information while ensuring accuracy.

Here are the key stages of the workflow:

1. Document Ingestion

   The IDP platform captures documents in multiple formats like PDFs, scans, or electronic files. OCR then converts image-based documents into machine-readable text for further processing.

2. Classification

   Documents are automatically sorted by type, such as invoices, receipts, or contracts. This ensures the right extraction rules and workflows are applied to each document.

3. Data Extraction

   Key information like names, addresses, invoice numbers, and amounts is captured. Machine learning improves accuracy over time, even with different layouts or formats.
   

4. Validation

   Extracted data is verified against business rules or external systems. For example, invoice totals can be matched with purchase orders for accuracy.

5. Integration

   Validated data is converted into a structured format and sent to business systems or databases. This enables seamless processing, reporting, or archival.

6. Exception Handling & Human Review

   When the IDP system encounters low-confidence or unclear data, it flags them as exceptions. This ensures accuracy while creating a feedback loop that strengthens the system.

7. Continuous Learning & Improvement

   The IDP system uses machine learning to adapt and improve over time. By learning from human feedback, tracking accuracy, and handling new document types, it becomes more reliable with every cycle.

Intelligent Document Processing (IDP) can be applied to various use cases across industries where there is a need to process and extract information from unstructured documents.

Here are some common use cases and real-world scenarios and the outcomes IDP enables:

1. Invoice Processing

   Intelligent document processing tools can automate the extraction of relevant data from invoices, such as vendor information, invoice numbers, line items, and amounts. It can validate the extracted data against purchase orders or contracts, enabling efficient accounts payable processes.

   • Scenario: A finance team struggles with thousands of vendors invoices each month, leading to payment delays and late fees.
   • Outcome: With IDP, invoices are automatically extracted, validated against purchase orders, and processed in minutes. Companies report 60–80% faster cycle times and up to 40% cost savings in accounts payable.

2. Customer Onboarding

   Intelligent document processing solutions automate the extraction of customer information from documents like application forms, identification documents, and financial statements. This speeds up the onboarding process, reduces manual errors, and improves customer experience.

   • Scenario: A bank faces long onboarding times due to manual KYC document checks and form validation.
   • Outcome: IDP automates the extraction of data from ID proofs, forms, and financial statements, reducing onboarding from 7 days to under 24 hours, improving customer satisfaction and compliance accuracy

3. Loan Application Processing

   Intelligent document processing platform can extract data from loan applications, including applicant details, financial statements, and supporting documents. This enables faster and more accurate loan application review and decision-making.

   • Scenario: Lenders face backlogs as employees manually review applicant details, financials, and supporting documents.
   • Outcome: IDP extracts and validates income proofs, credit history, and ID documents, cutting processing time by 70% and improving loan approval accuracy by 30%.

   

4. Claims Processing

   IDP can automate the extraction of data from insurance claims forms, medical records, and supporting documents. This accelerates the claims processing cycle and improves accuracy in determining coverage and payouts.

   • Scenario: Insurers handle a backlog of claim forms, medical records, and supporting documents, delaying payouts.
   • Outcome: IDP automates data extraction and validation from claim forms and medical records, reducing claim settlement time by up to 50% and improving fraud detection through cross-checking.

5. Human Resources (HR) Processes

   Intelligent document processing solutions can automate HR processes by extracting data from resumes, employee onboarding forms, performance evaluations, and other HR documents. This streamlines HR workflows, improves data accuracy, and enhances employee experience.

   • Scenario: HR teams spend hours manually processing resumes, offer letters, and employee onboarding forms.
   • Outcome: IDP automates resume parsing and form validation, enabling HR to screen 10x more applications per week and cut onboarding document processing time by 65%.

6. Healthcare Records Processing

   IDP can also extract relevant information from medical records, lab reports, and patient forms. This assists in accurate medical coding, billing, and streamlines healthcare record management.

   • Scenario: Hospitals face delays in coding and billing due to manual review of patient records and lab reports.
   • Outcome: IDP extracts patient data, diagnoses, and billing codes with 95% accuracy, reducing claim denials and enabling faster revenue cycles for providers.

When selecting an intelligent document processing (IDP) solution, it’s crucial to consider various factors to ensure it aligns with your organization’s specific needs.
Choosing the right IDP solution requires careful consideration of several factors.

1. Start by understanding your organization’s data its formats (emails, scans, paper, etc.), whether it’s structured or unstructured, and the volume and frequency that require automation.
2. Identify datasets that consume the most manual effort. Documents like invoices, contracts, or forms that take significant processing time are the best candidates for IDP.
3. Next, compare different IDP software options. Here are a few factors to keep in mind while choosing and comparing IDP solutions
   1. Consider factors such as the expected accuracy level compared to manual error rates and the potential for improvement.
   2. Determine if the IDP technology is template-based or capable of handling complex data formats that lack a prescribed structure.
   3. Verify if the software can effectively read and understand the types of data and documents your organization deals with.
   4. Assess the ease of integration with your preferred business tools and whether customization is possible.
   5. Evaluate the scalability of the software to handle your expected data volume and future growth.
   6. Consider the implementation timeline and the level of support provided by the vendor. Lastly, compare quotes from different providers to gain insights into pricing.

AutomationEdge DocEdge is more than just an OCR tool—it’s a complete enterprise IDP platform with built-in RPA and automation. It supports both cloud and on-premise deployments, making it ideal for industries with strict compliance needs. With pre-built use cases for invoices, KYC, HR documents, healthcare claims, and contracts, businesses can get started quickly.

Unlike API-only solutions, DocEdge offers seamless integration with ITSM, CRM, and BPM systems, along with enterprise-grade security and compliance. Its user-friendly console, custom model training, and dedicated support make it a scalable, reliable choice for intelligent document processing.

Intelligent Document Processing (IDP) Platform Comparison

Frequently Asked Questions