Intelligent Document Processing (IDP) is a technology that uses artificial intelligence (AI) and machine learning (ML) to automate the extraction of valuable information from digital and physical documents. This advanced tool can understand and interpret various types of documents, such as invoices, contracts, receipts, forms, and more.
In this way, it ensures the accuracy and efficiency of organizational processes. IDP combines different techniques to understand the content and context of documents, regardless of their format, layout, or source. It can handle documents like invoices, contracts, forms, receipts, reports, emails, etc.
Its main goal is to extract valuable information from large data sets without the need for human intervention. Through AI, IDP can eliminate the need for manual data entry and processing, increasing speed and reducing costs and human error involved.
Evolution of Intelligent Document Processing
For at least 3,900 years, humanity has faced the challenge of dealing with document processing. It all started with clay tablets that served to formalize occasions such as marriages and inheritance divisions in Sumerian civilization.
Over the millennia, these records evolved into post-industrial revolution corporate documents. The need to process and organize this information led to the emergence of different professions that dealt with it full-time—archivists, OCR specialists, and information managers, to name a few.
Emergence and popularization of OCR
Speaking of OCR (optical character recognition), this was for decades the only digital method to extract data from paper documents. During this period, which began in the 1950s, the technology allowed partial automation of data capture through the conversion of images into text.
With the development of more modern, powerful, and accessible computers, the amount of data processed by organizations grew exponentially. The first processing solutions to hit the market offered more user-friendly interfaces to complement the optical recognition functionality.
Creation of IDP
In recent years, this process has become easier with the creation of IDP, or intelligent document processing. Advances in AI and ML technologies have enabled the creation of various products that help organizations process and organize their documents more quickly.
These tools allow the creation of specific models that work for well-defined cases, such as receipts, contracts, or medical records. This allows, for example, a company to input the information from a payment receipt directly into its accounting software.
The results are fewer typing errors and reduced bottlenecks in their procedures.
Benefits of IDP
Intelligent document processing has the potential to make a significant difference in the operations of any organization that deals with a large volume of documents. But it is especially essential for those undergoing digital transformation.
Here are the benefits of using IDP in your company:
- Cost Savings: Automating document processing and analysis reduces unnecessary expenses by automating repetitive tasks. It allows you to reduce or even eliminate costs associated with manual data entry and processing.
- Customer Satisfaction: Companies dealing with consumers can process their documents more quickly. An IDP can handle onboarding new customers, reservations, and payments—or any other aspect that requires documentation.
- Scalability: Besides allowing human errors, manual processing limits the number of documents you can handle at a time. With IDP solutions, it is possible to scan papers on a large scale accurately.
- High Customization Capacity: AI models can be customized to process only the specific types of documents you need, exporting their data to the desired system.
How IDP works
The IDP workflow involves seven major steps:
1st Step: Document Acquisition
The IDP process begins with data collection from various sources. At this stage, documents are scanned or sent to the system in digital format. OCR (Optical Character Recognition) software can be used to extract text from them.
2nd Step: Document Pre-processing
In the second step, documents undergo a pre-processing phase to remove noise and improve the quality of the extracted text. This can be done through techniques such as:
- Alignment: Corrects the skew angle of the scanned image.
- Noise Reduction: Eliminates background stains, interfering marks, uneven contrast, and other textual and non-textual noise.
- Binarization: Converts the image of a scanned document from grayscale to black and white.
- Cropping: Removes unwanted outer areas of an image.
The tool can be trained in various languages, being able to read and interpret documents similarly to a data processing worker.
3rd Step: Document Classification
At this stage, document classification occurs, identifying the beginning and end of the source material. Subsequently, documents are classified into specific categories such as invoices, purchase orders, identity documents, contracts, bills, insurance claims, among others.
The IDP workflow uses OCR technology to analyze the data and differentiate whether the source is a PDF document or a scanned image, for example. It does this by extracting characters, numbers, and symbols from the data it verifies.
4th Step: Data Extraction
The most critical stage of the process occurs after document classification is completed. This is the extraction of important data. Here, the IDP deploys AI models trained through deep learning (DL), machine learning (ML), and natural language processing (NLP) to extract useful context from the source.
Document extraction focuses on specific aspects of interest, such as addresses, tax information, monetary values, product technical specifications, etc. The data is then entered into a database or stored for future use.
5th Step: Data Validation and Verification
The IDP also verifies the extracted information to ensure data accuracy and consistency. This can be done by comparing what was extracted with an existing database or through predefined rules. If the data fails validation, it must be manually refined, corrected, or enriched.
6th Step: Data Analysis
Decision-makers use the insights generated by the IDP to improve business processes. Data analysis provides various insights into error rates and document processing times, as well as normalizing data for easier consumption.
7th Step: Integration
When all these procedures are completed, the data can be fed into the company’s IT systems via APIs. This includes both local and cloud databases, as well as document repositories.
How IDP is Applied in Different Sectors
As IDP combines the characteristics of artificial intelligence, RPA, and OCR, it is a great candidate for automating various tasks in different sectors and areas. Here are some of the main use cases for IDP:
Financial Sector
The financial services sector is inherently paper-based. Countless documents and forms are filled out and signed daily for the most fundamental processes—from account opening to loan applications. With the use of IDP, the following key tasks can be easily automated:
- Customer Profile Generation: It is possible to assess risk levels by extracting and processing data from forms and documents. Credit assessments based on this data help process loan applications efficiently.
- Basic Functions: Loan and mortgage documents, account opening and closing, and check processing can be easily handled. The extracted data is configured to automatically update across the institution’s systems.
- Fraud Detection: With the use of artificial intelligence and high-quality, accurate data extraction, IDP makes it possible to detect potential fraud through the use of integrated algorithms.
Decision-making is effectively carried out as IDP can process data from annual bank reports and provide useful information on selected parameters.
Insurance Sector
The insurance market is another sector with a large volume of paper that can use IDP to automate daily office tasks from end to end. This applies to both obtaining completed insurance forms and signing claim settlements. Here are some tasks:
- Form Processing: This task is prone to errors when handled manually. Insurance companies greatly benefit from intelligent and automated processing of insurance forms.
- Cloud Integration: IDP can be integrated with the cloud, providing flexibility to centralize the database.
- Error Reduction: Data collection is done with fewer errors and more precision, accuracy, and organization with the help of IDP.
- Claim Definition: The evaluation of questionnaires for claim determination is done more quickly by automating the data extraction and analysis process. This helps professionals determine the actual claim value.
Healthcare Sector
The healthcare sector is another that deals with a large amount of documents, such as medical records, prescriptions, invoices, etc. IDP can help improve the efficiency and accuracy of data processing in healthcare, such as:
- Information Extraction and Validation: The technology allows extracting data from electronic medical records (EMR), such as medical history, diagnosis, treatment, medication, among others. IDP can help reduce transcription errors, improve data quality, and facilitate information sharing among healthcare providers.
- Medical Invoice Processing and Reconciliation: IDP can help speed up the revenue cycle, reduce administrative costs, and increase patient satisfaction in situations such as claims, payments, or reimbursements.
- Health Data Analysis and Reporting: IDP can help provide data-based insights and recommendations to improve decision-making and health outcomes. This applies to things like test results, quality indicators, public health statistics, etc.
Retail and E-commerce
The retail and e-commerce sector benefits from IDP to automate and optimize processes such as:
- Order Processing and Management: Includes confirmations, invoices, receipts, and bills. Intelligent Document Processing can help improve the accuracy and speed of order processing, reduce billing errors, and increase customer satisfaction.
- Returns Management: Includes requests, authorizations, labels, and refunds. IDP can help simplify and expedite the return process, reduce operational costs, and improve customer loyalty.
- Contract Management: Includes contracts with suppliers, partners, and customers. Intelligent Document Processing can help extract and verify the terms and conditions of contracts, ensure compliance and fulfillment of contracts, and facilitate contract renewal and cancellation.
Government and Public Sector
The government and public sector can use IDP to improve the efficiency and transparency of processes such as:
- Document Management: Assistance in managing identity records, such as ID cards, passports, and driver’s licenses. IDP can help verify and validate the authenticity of identities, reduce the risk of fraud, and facilitate the issuance of documents.
- Public Document Management: Includes certificates, declarations, licenses, and permits. Intelligent Document Processing can help capture and extract data from public documents, reduce processing time and cost, increase accessibility and availability of documents, and ensure data security and privacy.
- Processing and Managing Public Requests and Services: Includes social benefits, taxes, health, education, and transportation. IDP can help automate and optimize the delivery of public services, improve citizen satisfaction and trust, and increase government efficiency and accountability.
Conclusion
Intelligent Document Processing (IDP) is an innovative solution that combines advanced AI, machine learning, and OCR technologies to automate data processing across various sectors. Its ability to accurately and quickly extract, analyze, and organize information significantly reduces manual work, saves time and costs, and improves operational efficiency.
Companies from all segments, from the financial sector to the public sector, can benefit from implementing IDP, especially those undergoing digital transformation. With its versatility and customization capabilities, Intelligent Document Processing is an essential tool for organizations looking to modernize their operations, minimize human errors, and increase the scalability of their processes.
The future of document management is being shaped by these technologies, bringing more innovation and intelligence to corporate daily life.
SoftExpert IDP
SoftExpert IDP is a comprehensive solution that helps organizations process large amounts of unstructured documents, such as invoices, contracts, receipts, and more, accelerating the document digitization process.
The integration between IDP tools and SoftExpert Suite offers intelligent workflow automation, increasing the efficiency of organizational processes. Learn how SoftExpert IDP can revolutionize document management in your organization and drive your success by contacting one of our specialists today.
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