Intelligent Document Processing

The Beginner’s Guide to Intelligent Document Processing (IDP)

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The Beginner’s Guide to Intelligent Document Processing (IDP)

The world’s data storehouse is expected to reach 175 zettabytes by 2025. Most of the data will be unstructured, such as photographs, emails, and documents, necessitating intelligent document processing (IDP) software to arrange the data into actionable insights. IDP helps mine vast amounts of data which would otherwise be costly and time-consuming. 

Throughout this intelligent document processing guide, we’ll see how IDP optimizes an organization’s data, removes redundant tasks, and improves productivity by supporting employees in their jobs. 

This guide also includes how the technology works, and the real-world applications it provides for organizations today.

So, let’s jump right into it:-

What is Intelligent Document Processing (IDP)?

Intelligent document processing is a workflow automation technology that converts semi-structured and unstructured information into accessible formats from large streams of data. IDP scans, reads, extracts, categorizes, and organizes data from a variety of sources and formats. 

Unstructured data is challenging to store or index because it lacks a predefined pattern or structure. As a result, the ambiguous structure presents users with a slew of data extraction issues. Fortunately, a dependable, intelligent document processing system can automate data processing, simplifying information extraction.

Primarily, IDP extracts valuable information from large sets without manual intervention or human input. 

IDP solutions are used in a variety of applications in modern enterprises such as: 

• Client support

• Contract management 

• Data extraction 

• Document processing

The technologies behind Intelligent Document Processing

Artificial intelligence and optical character recognition (OCR), which includes various subdisciplines of AI, like computer vision (CV) and natural language processing, are the technical foundations that underpin IDP (NLP). 

Let’s understand the technologies powering intelligent document processing. 

1. Optical character recognition (OCR)

OCR translates typed, printed, and handwritten text into a computer-readable format. Although OCR solutions are intelligent, they only interpret what they “see” and hence are limited to discerning the meaning of the texts. As a result, OCR depends on artificial intelligence to extract insights from data.

2. Computer vision

Computer vision (CV) is a subfield of artificial intelligence that deals with comprehending and extracting information from digital pictures. In contrast to OCR, which focuses on text recognition, CV evaluates a document’s layout to detect and remove specific data fields from non-textual features such as tables or graphs.

3. Natural language processing (NLP)

NLP is a subset of AI that extracts meaning from unstructured data. Instead of employees searching through support requests for hours to uncover common issues, NLP allows businesses to examine the data in seconds. Commonly, businesses use NLP and OCR to increase the accuracy of document processing by 99% or more. 

4. Artificial intelligence (AI)

After being trained on massive amounts of historical data, AI models may make their own decisions and predictions. As a result, the models learn to “understand” image data, as well as process information from unstructured documents and analyze the importance of textual data in the same way humans do.

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A comprehensive guide on Intelligent Document Processing use-cases

Whether a business wants to digitize customer data, process invoices, and payment receipts, or extract specific information from unstructured data, IDP software can carry out the functionalities within seconds, across industries. 

The use uses of intelligent document processing include: 

1. Accounting

Intelligent document processing helps the finance and accounting departments understand unstructured and semi-structured data by converting it into searchable data using technologies like NLP, ML, OCR, and computer vision. 

For starters, the accounting department receives orders in many formats: emails, purchase orders, PDF or word-based invoices, and even remittances. Integrating the IDP software with ERP allows for automated document processing including data extraction, indexing, and validation. 

Manually creating invoices, especially at a high volume, is a tedious and erroneous job prone to delays. Using IDP, invoices can be batch-created with templates based on company data. What’s more, advanced intelligent document processing software notifies admins in case of errors. 

Reliable data processing reduces the danger of late payments allowing businesses to capitalize and grow their income.

2. Banking

A widely implemented use case of IDP is in the banking industry. For example, bank statement processing automation digitizes bank statements with more than 99% accuracy. It extracts data from bank statements for detailed analysis, AI-based data validation reduces human effort and the time spent on document processing, and reconciles statements, analyzes credit profiles, and verifies tax reporting within 30-60 seconds over thousands of documents with automated transaction categorization.

For example, a payment company uses Docsumo’s APIs for automating data capture from bank statements and identity cards during customer onboarding. As a result, the data entry time is reduced significantly with improved customer experience.

Another intelligent document processing application for the banking sector: is approving more loans and mortgages with automated bank statement processing. AI-based IDP can detect changes in header/column/table positions and even subtle alterations in bank statements for bank statement analysis. 

3. Human resources 

Document processing for the HR department simplifies complex human resource administrative workflows by eliminating manual data entry tasks so that the team can focus on more valuable work. 

Intelligent document processing ingests unstructured data like employee onboarding documents, employee codes, payroll documents, and external contractor invoices with OCR and machine learning technology.  

4. Insurance

IDP for the insurance industry leads to faster claim processing and improves fraud detection while reducing operational costs. 

Typically insurance companies need to process a large number of unstructured and semi-structured documents. They deal with enormous volumes of unstructured data, such as email input from regional offices. These emails contain information about an insured individual that must be reviewed, validated, processed, and then sent to the company’s CRM software. 

Intelligent document processing software processes the claim documents, categorizes them, and extracts the information into the correct format, helping insurers improve the accuracy and efficiency of the archiving process by more than 99%. With pre-trained APIs, users can classify documents, extract key points, and validate data to make smarter underwriting decisions. 

5. Logistics

IDP for logistics helps classify, extract, and analyze unstructured data from all kinds of transport documents at scale. 

  • For example, IDP can automatically extract data from shipping papers, which is used to track shipments and inventory levels. 
  • IDP can also prepare bills of lading and conduct customs declarations, allowing products to traverse borders more quickly. And these are just a few instances of IDP’s supply chain capabilities.

The automated document processing software improves data extraction efficiency by 10X as the smart AI can learn with every new transport document time. In addition to this, Docsumo’s pre-trained API extracts data from complex documents like cargo insurance certificates within seconds.

6. Legal

Legal service providers face various issues each day: 

  • Archiving and auditing documents
  • Mergers and acquisition-related papers
  • Property filings
  • Adhering to compliance rules
  • Ensuring client response times

The majority of these require extensive documentation at each level. It is critical to put a system to manage these papers while keeping their importance and sensitive nature in mind.

Additionally, attorneys frequently refer to massive amounts of material when working on a case. The documentation for their client/s is commonly done manually by an associate, making it prone to inaccuracies and mistakes.

Here’s how intelligent document processing for legal services benefits law firms: 

  • Document storage and access - Firstly, IDP extracts key elements from lengthy legal documents, appends the key data points as metadata in digitized versions, and stores them over the cloud for fast search and retrieval. 
  • Fine-grade security - Stores sensitive legal documents and information with end-to-end encryption. Role-based access rights ensure that the sensitive data is secure. 
  • Fraud detection - IDP extracts data from physical documents and brings them on the same level as other digital data. Advanced automated document processing software can also flag fraudulent or erroneous documents that don’t match the specific data sets. 

How does intelligent document processing work

IDP is widely used across industries to automate document processing, extract specific information from a variety of sources, and extract insights for decision makers. Here’s how intelligent document processing works: 

Step 1 - Collection

Data is collected from various sources and in multiple formats and prepared for processing. This comprises document merging/splitting, data validation, and adjustments to low-quality renderings. Some solutions also include tools for data labeling and annotation, frequently performed by a human-in-the-loop (HITL).

Step 2 - Classification

Documents/information is then classified into several groups. IDP uses sophisticated systems to generate category ideas based on existing taxonomies. The software can also accept documents at scale, classify them, and route them to third-party sources for further processing. Humans participate in category design, definition, and data confirmation at this stage of intelligent document processing. 

Step 3 - Extraction

Advanced document processing software use ML models to identify fields for extraction and then extract data from various content types and formats. At this stage, humans can train APIs to identify specific fields for extraction. 

Step 4 - Feedback and Validation

The extracted data is validated against internal and external data sources. Human input is used to cope with outliers, preprocessing, categorization, extraction quality enhancement, and further ML model training.

Step 5 - Integration

Validated data is given to downstream apps for usage. Customer service platforms, data enrichment tools, and RPA systems process this data further. At this stage, insights from extracted data are used for decision-making and business process optimization. 

Top benefits of Intelligent Document Processing 

Why are businesses using IDP in the first place for document processing? For starters, the software eliminates manual data entry and processing errors that plague industries dealing with high volumes of data and documents. The other benefits are: 

#1. Improves data accuracy by more than 99%

IDP eliminates the likelihood of human mistakes in manually reading documents and transcribing data to various formats. Accurate data is critical for successful decision-making and risk management, and intelligent document processing software Docsumo captures data with more than 99% accuracy at a 95% straight through rate (STP). 

#2. Improves efficiency by 10X

IDP automates the tedious process of evaluating unstructured data to extract useful information, resulting in increased productivity. This allows staff to focus on more value-driven tasks to improve production, efficiency, and bottom line. 

#3. Improves customer satisfaction

Intelligent document processing shortens response times in client-facing business operations that require examining customer documents like insurance and mortgage. Document reviews are completed quickly and accurately, resulting in faster processing times. 

#4. End-to-end data security

An intelligent document processing platform like Docsumo invests in security best practices to ensure data integrity. GDPR compliance, SOC-2 certification, and role-based access ensure sensitive information is protected from unauthorized access. 

#5. Processes information at scale

Owing to the ability of intelligent document processing platforms to process large volumes of documents using limited resources, they allow organizations to scale data extraction processes without increasing the headcount. 


Intelligent document processing software help some of the world’s biggest data-driven businesses automate unstructured and semistructured document processing with more than 99% accuracy. 

The key features of Docsumo for intelligent document processing are: 

  • Ingest, classify, and preprocess documents with ML-based pre-trained API.
  • Accurately capture key values and tables from unstructured documents like IRS form 1040, bank statements, bills of lading, and ACORD forms among many others. 
  • Create Excel-like formulas to validate data within a document, across documents and databases. 
  • Directly integrate Docsumo’s API with your existing systems to make intelligent automated decisions.
Suggested Case Study
Automating Portfolio Management for Westland Real Estate Group
The portfolio includes 14,000 units across all divisions across Los Angeles County, Orange County, and Inland Empire.
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Pankaj Tripathi
Written by
Pankaj Tripathi

Helping enterprises capture data for analytics and decisioning

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