We live in a world where the volume of information generated daily is massive, especially through documents. Companies from all sectors and industries depend on these records for proper operations related to their internal processes, cooperating to achieve efficient results. However, managing and processing these documents quickly and accurately can be challenging. This is why Intelligent Document Processing (IDP) has become increasingly popular. In this post, I will explain what IDP is, how it works, and describe some cases of its use in different sectors and industries.

What is IDP?

Intelligent Document Processing (IDP) is a technology that uses artificial intelligence (AI) and machine learning to automate the extraction of valuable information from digital and physical documents. This advanced tool is capable of understanding and interpreting different types of documents, such as invoices, contracts, receipts, and forms, among others, ensuring the accuracy and efficiency of organizational processes.

IDP is a technology that combines different techniques from natural language processing, computer vision, and machine learning to understand the content and context of documents, regardless of their format, layout, or font. IDP can handle documents such as invoices, contracts, forms, receipts, reports, emails, etc.

The key objective of IDP is to extract valuable data from large datasets without the need for human intervention. There are several advantages to automating part of your document processing with IDP. Through artificial intelligence, IDP can eliminate the need for manual data entry and processing, increasing speed as well as reducing costs and human errors involved.

Modern organizations typically have large volumes of three types of data: structured, unstructured, and semi-structured. Structured data is organized and more easily read by human data processors. Unstructured data takes time to process and analyze. Semi-structured data falls somewhere between the other two. IDP is capable of automating the processing of any type of data.

How does IDP work?

The IDP workflow involves SEVEN major steps:

First step – Document capture

The IDP process begins with collecting data from multiple sources. In this step, documents are scanned or sent to the system in digital format. OCR (Optical Character Recognition) software can be used to extract text from these documents.

Second step – Document pre-processing

In the second step, the documents go through a pre-processing process to remove noise and improve the quality of the extracted text. This can be done through techniques such as:

  • Alignment – Corrects the tilt angle of the scanned image;
  • Noise reduction – Elimination of background stains, interfering lines, irregular contrast, and other textual and non-textual noise;
  • Binarization – Conversion of the scanned document image in shades of gray to black and white;
  • Cropping — Removing unwanted outer areas from an image.

The tool can be trained in multiple languages and is capable of reading and interpreting documents similar to a data processing worker.

Third step – Document classification

In this step, the document is classified, first identifying the start and end of the source material. Documents are subsequently classified into specific categories such as invoices, purchase orders, identity documents, contracts, bills, and insurance claims, among many others.

The IDP workflow uses OCR technology to analyze data and differentiate, for example, whether the source is a PDF document or a scanned image. It does this by extracting characters, numbers, and symbols from the data it checks.

Fourth step – Data extraction

The most critical step in the process occurs after document classification is complete. This involves extracting important data from documents. Here, IDP deploys trained AI models that use deep learning (DL), machine learning (ML), and natural language processing (NLP) methods to extract useful context from the source.

Document extraction focuses on specific aspects of interest, such as addresses, tax information, monetary values, technical product specifications, among many others. The data is later entered into a database or stored for later use.

Fifth step – Data validation and verification

IDP also verifies the extracted information to ensure data accuracy and consistency. This can be done by comparing the extracted information with an existing database or using predefined rules. If issues are identified during validation, the data must be manually enhanced, corrected, enriched, etc.

Sixth step – Data analysis

Decision makers use the insights generated by IDP to improve business processes. Data analysis provides numerous insights into error rates and document processing times, as well as normalizing data for easier consumption.

Seventh step – Integration

When all these procedures are completed, the data can be fed into the company’s IT systems through APIs. This includes on-premises and cloud databases and document repositories.

IDP use cases

As IDP combines the characteristics of artificial intelligence, RPA, and OCR, it is a great candidate for automating multiple tasks in different sectors and industries. Here are some of the most prominent IDP use cases:

 Financial sector

The financial and banking sector is an industry that is naturally paper based. Countless documents and forms are filled out and signed daily for the most fundamental processes – opening an account or applying for a loan. Using IDP, the following key tasks can be easily automated:

  • Generation of customer profiles to assess the risk level, extracting and processing data from forms and documents. Risk scores based on this data help process loan applications efficiently.
  • Basic functions like loan and mortgage documents, account opening and closing, and check clearing can be processed easily. The extracted data is configured to update automatically across all systems throughout the entire institution.
  • Using artificial intelligence and high-quality and high-precision data extraction, IDP enables detecting potential fraud using built-in fraud detection algorithms.
  • Decision making is conducted effectively as IDP can process data from bank annual reports and provide useful and meaningful information on the chosen parameters.

Insurance sector

Insurance is another paper-intensive industry that can use IDP to automate end-to-end daily office tasks, from getting insurance forms completed to signing claims settlements. See some tasks below:

  • Form processing is prone to errors when handled manually. Insurance companies benefit greatly from smart, automated insurance form processing.
  • IDP can be integrated with the cloud, providing flexibility to centralize the database.
  • Data collection is done with fewer errors and more precision, accuracy, and organization with the help of IDP.
  • Assessing questionnaires for determining claims is made less time-consuming by automating the data extraction and analysis process to help professionals determine the true value of the claim.

 Healthcare sector

The healthcare sector is another area that deals with a large number of documents, such as medical records, prescriptions, invoices, etc. IDP can help improve the efficiency and accuracy of document processing in healthcare, in tasks such as:

  • Extraction and validation of data from electronic medical records (EMR) such as medical history, diagnosis, treatment, medication, etc. IDP can help reduce transcription errors, improve data quality, and make it easier to share information among healthcare providers.
  • Processing and reconciling medical invoices such as claims, payments, reimbursements, etc. IDP can help accelerate the revenue cycle, reduce administrative costs, and increase patient satisfaction.
  • Analysis and reporting of healthcare data such as test results, quality indicators, public health statistics, etc. IDP can help provide data-driven insights and recommendations to improve decision-making and health outcomes.

 Retail and e-commerce

The retail and e-commerce sector also benefits from IDP to automate and optimize several document-related processes, such as:

  • Processing and managing orders, such as confirmations, bills, receipts, invoices, etc. IDP can help improve order processing accuracy and speed, reduce billing and shipping errors, and increase customer satisfaction.
  • Processing and managing returns, such as requests, authorizations, labels, refunds, etc. IDP can help simplify and speed up the return process, reduce operational costs, and improve customer loyalty.
  • Processing and management of contracts, such as contracts with suppliers, partners, customers, etc. IDP can help extract and verify contract terms and conditions, ensure contract compliance and enforcement, and streamline contract renewal and cancellation.

 Government and public sector

The government and public sector can also use IDP to improve the efficiency and transparency of document-based processes such as:

  • Processing and management of identity documents such as ID cards, passports, driver’s licenses, etc. IDP can help verify and validate the authenticity and eligibility of identity documents, reduce the risk of fraud and identity theft, and streamline the issuance and renewal of identity documents.
  • Management of public documents, such as certificates, declarations, licenses, permits, etc. IDP can help capture and extract data from public documents, reduce processing time and cost, increase document accessibility and availability, and ensure data security and privacy.
  • Processing and managing requests and public services, such as social benefits, taxes, health, education, transportation, etc. IDP can help automate and optimize the service and delivery of public services, improve citizen satisfaction and trust, and increase government effectiveness and accountability.


    In this post, you learned what IDP is, how it works, and what some of its use cases are in different sectors and industries. IDP is a solution that uses artificial intelligence to extract, classify, and validate data from structured, semi-structured or unstructured documents, quickly, accurately, and automatically. IDP can provide several benefits to organizations that handle a large volume of documents, such as reducing costs, increasing productivity, improving quality, and generating insights and value, among others.

    SoftExpert IDP

    SoftExpert IDP is a complete solution that helps organizations process large quantities of unstructured documents, such as invoices, contracts, receipts, among others, accelerating the document digitization process. The integration between IDP and SoftExpert Suite tools offers smart workflow automation, increasing the efficiency of organizational processes. Find out how SoftExpert IDP can revolutionize document management in your organization and boost your success by contacting one of our experts right now.

    I want to learn more about SoftExpert IDP


Camilla Christino


Camilla Christino

Business Analyst at SoftExpert, completed a Bachelor's in Food Engineering at Instituto Mauá de Tecnologia. She has solid experience in the quality area in the food industries with a focus on monitoring and adapting internal and external auditing processes, documentation of the quality management system (ISO 9001, FSSC 22000, ISO / IEC 17025), Quality Control, Regulatory Affairs, GMP, HACCP and Food Chemical Codex (FCC). She is also certified as a leading auditor in the ISO 9001: 2015.

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