10 Intelligent Document Processing Examples & How They Work

Explore 10 real-world intelligent document processing examples showcasing how OCR and ML technologies streamline data extraction from PDFs, scanned images, and more. Get insights on how businesses leverage IDP to boost efficiency and accuracy in document handling.

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10 Intelligent Document Processing Examples & How They Work

Intelligent Document Processing (IDP) uses technology like Optical Character Recognition (OCR) and Machine Learning (ML) to improve document handling. Normally, businesses have to spend a lot of time manually entering data from different documents into their systems. This takes up a lot of time and can lead to mistakes that cause problems.

Intelligent Document Processing (IDP) fixes this by automatically getting data from documents like PDFs, scanned images, and paper forms. With OCR, it can read text accurately and turn it into editable and searchable data. ML helps the system improve over time by learning from mistakes and documenting changes without needing humans to fix them.

Intelligent Document Processing (IDP) saves time and reduces mistakes. It simplifies things for workers and lets businesses use their people for more important jobs, making them work better and faster.

Intelligent Document Processing (IDP) is improving the work of many industries. In this blog, we'll discuss Intelligent Document Processing examples and its benefits.

10 Intelligent Document Processing Examples in Real Life

Intelligent Document Processing (IDP) is used in many industries. It changes tradition, manual document handling into fast, automated processes. Here are ten real-life examples of intelligent document processing.

10 Intelligent Document Processing Examples in Real Life

1. Invoice processing

One of the most common intelligent document processing examples is in invoice processing. Handling invoices by hand has many problems. There can be data entry mistakes, delayed payments, and trouble tracking financial obligations. Traditional methods requires extensive human work. This causes delays during busy times and raises operational costs.

Moreover, invoices can come in different formats and styles. This makes data extraction harder and increases the chance of errors. 

Intelligent Document Processing (IDP) addresses these challenges by automating invoice processing and data extraction. IDP extracts key information from invoices, such as vendor details, invoice numbers, line items, and amounts. With IDP, you’ll process invoices faster and improve efficiency in accounts payable.

Here’s how IDP helps in invoice processing:

  • Optical Character Recognition (OCR) technology scans paper invoices and converts the text into machine-readable data.
  • Machine learning (ML) algorithms check the extracted data against predefined rules and historical records. This helps in ensuring accuracy.
  • AI models sort the extracted information into fields like invoice number, date, and amount. This helps in seamless integration with ERP systems.
  • IDP systems have automated workflows that identify and flag any discrepancies or anomalies in the data.  These flagged items are then sent to human reviewers for quick resolution.
  • IDP easily connects with ERP and accounting software. This makes the whole invoice processing cycle automatic. This integration also reduces manual intervention and speeds up processing times.
  • The system continually learns and improves over time through feedback loops. As more invoices are processed, the IDP system gets better and faster at extracting and processing data.

IDP reduces human error and improves invoice handling. This leads to timely payments and better financial management.

Suggested Read: Detailed Guide on Invoice Processing Methods

2. Customer onboarding

Customer onboarding is critical in the banking, insurance, and telecommunications industries. In these industries capturing accurate customer data quickly is essential for service activation. Traditional methods often involve a lot of paperwork and manual data entry. This can cause delays and mistakes, which can affect customer satisfaction.

Moreover, sometimes the onboarding process includes handwritten forms and notes. That’s where Intelligent Document Processing (IDP) can help. IDP (Intelligent Document Processing) is great at reading and understanding handwriting, including cursive. It can accurately fill in any missing characters. Whether it's tax documents, patient forms, or government paperwork, IDP easily converts them into digital formats.

Intelligent Document Processing (IDP) improves the customer onboarding process by automating data extraction from important documents in the following way.

  • IDP systems utilize OCR and ML to extract data from customer documents. This data includes personal details, document numbers, addresses, and other pertinent information.
  • The extracted data is then automatically cross-checked with internal or external databases to ensure it is accurate and complete. This step includes checking the authenticity of documents and compliance with regulatory requirements.
  • Once validated, the data is fed into the business’s CRM or customer management systems. This integration triggers further onboarding steps, such as account creation, background checks, and initial customer communications.

IDP helps meet regulatory standards by keeping accurate records and ensuring data integrity. It also speeds up the time from application to activation. This greatly improves customer satisfaction and increasing the chances of keeping customers.

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3. Contract management

Contract management involves organizing and administering documents that detail agreements between parties. Manually doing these has several challenges. These include tracking expiration dates, and renewal terms. It also includes manually checking specific clauses across many documents and systems.

This can cause missed deadlines. It can also lead to not meeting terms and to inefficiencies in renegotiating or ending contracts. Plus, manually searching for information in contracts takes a lot of time and can lead to mistakes.

Intelligent Document Processing (IDP) simplifies contract management by automating the extraction and categorisation of key information from contracts. 

Here’s how IDP helps in contract management:

  • IDP extracts key information from contracts. This information includes key dates, business names, clauses, and financial terms. It reduces errors common in manual entry.
  • IDP ensures contracts follow the law. It reduces the risk of penalties and disputes.
  • IDP streamlines the contract management workflow. It does this by automating tasks such as creation, review, approval, and monitoring.
  • IDP provides timely and accurate data. It gives insights for informed decision-making in contract management, aiding strategic choices.
  • IDP uses strong security measures. They protect sensitive contract data. This ensures compliance and stops unauthorized access.
  • IDP saves costs and improves financial performance by reducing manual labour and errors.

IDP makes contract lifecycle management more efficient. It lets businesses quickly respond to chances to renegotiate or renew contracts and to keep following contract terms.

4. Claims processing

In insurance, claims processing is extremely important. It directly affects customer satisfaction. It requires precise data extraction and interpretation in specific formats. Too many document structures and layouts can make this hard. It also takes a lot of time. These inefficiencies cause delays in resolving claims. They also raise costs and anger policyholders.

Intelligent Document Processing (IDP) offers a solution by automating the extraction and analysis of data from claims documents. IDP technologies like OCR and ML are adept at handling structured and unstructured data. They let companies upload claims records. The companies can then apply "matching rules" to verify insurance policies. For instance:

  • Claim Forms: IDP systems can quickly extract important information likepolicy numbers, incident dates, and claim amounts. This ensures that data is processed accurately and swiftly.
  • Medical Reports: These often contain complex and extensive data. IDP helps by parsing detailed information. This includes diagnosis codes and treatment histories. It makes claims adjudication faster by using medical records.
  • Receipts: For reimbursement claims, IDP can extract itemized costs from receipts, automating calculations and validations needed for claim settlements.

IDP helps insurance companies reduce the time to process claims and boost accuracy. This enhances operational efficiency and improves customer experience by expediting claim settlements. Also, cutting manual data handling reduces the risk of errors and fraud. This helps make claims processing more secure and reliable.

5. Regulatory compliance

For businesses operating in heavily regulated industries such as finance, healthcare, and energy, staying compliant with industry regulations is important. Compliance involves managing many documents. These include financial records, patient files, and safety reports.

Handling these documents manually exposes organizations to risks. These risks include non-compliance and severe penalties. Meeting all regulations requires much manpower and resources. 

Intelligent Document Processing makes compliance much easier. It does this by automating the extraction, management, and analysis of data from these critical documents. It supports monitoring compliance and helps organizations stay current with changing laws and rules.

Here is how IDP helps in regulatory compliance:

  • IDP automates document verification against regulations, reducing the risk of non-compliance.
  • Ensures accurate data extraction, preventing errors and inconsistencies that may lead to breaches.
  • Monitors documents for compliance changes, allowing prompt adjustments.
  • Provides comprehensive audit trails, aiding compliance demonstrations during audits.
  • Automates processes, saving time and resources.
  • Handles increasing volumes of documents as businesses grow.
  • Mitigates risks associated with non-compliance through consistent adherence to regulations.

IDP speeds up the compliance workflow with automation and AI. It reduces the chance for human error. This ensures that businesses can more efficiently meet regulatory requirements.

6. Data insights

Many companies deal with large volumes of unstructured data daily, found in various documents like market research reports, customer feedback forms, and operational logs. Manually analyzing this data is time-consuming, costly, and prone to inaccuracies, which can lead to misguided decisions and missed opportunities.

Intelligent Document Processing (IDP) transforms how companies gather insights from their documents.

Here's how IDP helps gather data insights from the extracted document:

  • IDP accurately extracts data from various documents, including unstructured formats like PDFs and scanned images. IDP uses OCR to turn scanned papers, PDFs, and images into readable text, ensuring all important information is captured.
  • By converting unstructured data into structured formats, IDP organizes information in an easily searchable and analyzable way. This structured data provides a comprehensive view of business operations, customer interactions, and market trends.
  • IDP integrates with analytics tools to analyze extracted data, uncovering patterns, trends, and insights. Businesses can make informed decisions and drive strategic initiatives by transforming raw data into actionable insights.
  • IDP's real-time processing capabilities allow businesses to access up-to-date insights. This allows for agile decision-making and enables companies to respond promptly to market changes and emerging opportunities.
  • IDP solutions are scalable, meaning they can handle increasing amounts of data without compromising speed or accuracy. This is essential for growing businesses or having seasonal peaks in data processing needs.

With IDP, companies streamline their data processing workflows and enhance the quality of insights derived from their documents. This leads to more informed decision-making, improved operational efficiency, and a better understanding of market and customer dynamics.

IDP also helps in risk management by providing timely and accurate data that can highlight potential risks before they become big issues.

7. Boosting HR processes

Human Resources departments are tasked with managing a myriad of documents, such as employment contracts, personal identification documents, benefits forms, leave requests, and training materials, which presents considerable challenges. 

These documents often vary widely in format and complexity, making manual processing slow, prone to errors, and a drain on resources. The need for precise data entry and strict confidentiality complicates these tasks, with compliance risks looming over any mistakes.

Intelligent Document Processing (IDP) addresses these challenges by automating the extraction and processing of data across the full spectrum of HR documents. By leveraging OCR technology, IDP systems can accurately transform text from paper-based and digital formats into machine-readable data. Machine learning algorithms then categorize and integrate this data into HR systems, enhancing data accuracy and security. 

For example, IDP can extract data from:

  • Employment Contracts: Automating the capture of start dates, salary information, and role descriptions.
  • Personal Identification Documents: Extracting and verifying employee information quickly and accurately.
  • Benefits Forms: Streamlining the enrollment process by capturing plan selections and dependant data.
  • Leave Requests: Automating the approval process by extracting dates and types of leave directly from request forms.
  • Training Materials: Compiling and organizing data on employee training progress and completion.

This automation not only speeds up HR processes but also significantly reduces the administrative burden, allowing HR professionals to devote more time to strategic initiatives such as talent development and employee engagement.

8. Empowering legal teams

Legal teams often must manage legal documents. These documents include contracts, litigation papers, corporate filings, and compliance paperwork. This is hard not just because of managing these documents. It's also because of using all legal data well. It's for better decisions and risk management. That’s where Intelligent Document Processing helps.

Intelligent Document Processing (IDP) transforms legal document management.

  • IDP quickly identifies and retrieves legal precedents from extensive databases, reducing research time.
  • During litigation, IDP automates scanning and categorizing documents. This streamlines the discovery phase and improves accuracy and speed.
  • IDP monitors compliance documents. It aims to find legal risks early. This helps with proactive management and compliance upkeep.
  • IDP extracts vital information from contracts. It finds key terms and renewal dates. This helps legal teams manage obligations well and stay ahead of deadlines.

IDP boosts the efficiency and accuracy of legal operations. It also helps legal teams manage workload well, cut risks, and improve service. And it does all this without much cost.

9. Revolutionizing mortgage processing

Mortgage processing is document-intensive, involving numerous forms such as loan applications, credit reports, and property appraisals. The manual handling of these documents can lead to significant delays, errors in data entry, and a slower approval process, ultimately impacting customer satisfaction and operational efficiency.

Intelligent Document Processing (IDP) revolutionizes this sector by automating the extraction and processing of data from these critical documents. IDP systems employ OCR for mortgage processing to accurately convert text from documents into digital data, which can be analyzed and processed using machine learning algorithms. These technologies enable the automated identification and extraction of key data points such as applicant income, property values, and loan amounts.

This automation automates the entire mortgage processing workflow by:

  • Speeding up the loan application review process by quickly extracting applicant information and cross-referencing it with credit reports.
  • Improving accuracy in property appraisals by automatically capturing and analyzing data from appraisal documents.
  • Improving compliance and risk management by ensuring that all necessary data is accurately recorded and easily accessible for audits and reviews.

By reducing the reliance on manual processing, IDP accelerates the mortgage approval process, minimizes errors, and enhances the customer experience by offering faster loan processing times.

10. Accelerating research & development

Research and development (R&D) in fields such as pharmaceuticals, biotechnology, and engineering rely heavily on managing and analyzing lots of documentation. 

These include research papers, patents, and experimental data. They are key to driving innovation. Handling these documents using the tradition method is slow and hard. It could delay research and the introduction of innovations to the market.

Intelligent Document Processing (IDP) makes R&D better. It automates the management and analysis of these vital documents. IDP systems make it easy to sort and extract data from complex documents. They let researchers quickly access and combine information from many sources.

Intelligent Document Processing (IDP) accelerates research & development by:

  • IDP simplifies data collection from various sources, reducing manual entry and errors. This allows researchers to focus more on analysis and innovation.
  • IDP uses advanced algorithms to ensure high data accuracy, reducing inconsistencies and errors. Accurate data leads to better-informed decisions.
  • IDP expedites literature reviews by extracting and summarizing information from numerous documents. NLP technology quickly identifies key concepts and trends.
  • IDP standardizes and digitizes data. It makes data easy to share across teams. It enhances collaboration and efficiency in R&D.
  • IDP automates patent information extraction and analysis. It speeds up review and gives a full understanding of the patent landscape.
  • IDP offers real-time data extraction and analysis. It lets researchers quickly respond to new data and insights. This speeds up the R&D process.

Automating these parts of document processing with IDP lets R&D teams spend more time on research and less on admin tasks. This speeds up innovation and discovery.

Conclusion

Adopting Intelligent Document Processing can benefit organizations across various industries. It helps increase operational efficiency, minimizes errors, accelerates processing times, and vastly improves accessibility to critical data. The role of Intelligent Document Processing will become increasingly central in helping organizations manage their information more effectively

Choosing the right technology partner is essential for businesses looking to implement IDP. Docsumo stands at the forefront of this technology, offering robust IDP solutions tailored to meet the specific needs of different industries.

With Docsumo, businesses can use OCR and machine learning technologies to transform document workflows, improve decision-making, and increase efficiency. Docsumo’s IDP solutions ensure that document processing is as efficient and error-free as possible, enabling you to focus on core activities and strategic growth.

FAQs: Intelligent Document Processing Examples

What are the most common examples of documents that can be analyzed by intelligent document processing solutions?

Intelligent document processing (IDP) solutions commonly analyze invoices, receipts, contracts, forms, and emails. For instance, extracting data from invoices for payment. Or capturing information from insurance claim forms for processing.

What is IDP in document processing? 

IDP stands for Intelligent Document Processing. It means using AI and machine learning to automate processing documents. It involves data extraction, classification, and validation to streamline document-based workflows.

What are IDP products? (Briefly explain different types of IDP solutions available)

IDP products include various solutions. They have OCR, NLP, and ML algorithms. OCR reads text, NLP processes language, and ML learns. These include software for capturing documents. They also include tools for extracting data and systems for classifying documents. The systems are tailored for specific document types and industries.

What are some of the best IDP tools?

Notable IDP tools include ABBYY FlexiCapture, UiPath Document Understanding, and IBM Datacap. These platforms offer full document processing. They include data extraction, classification, and integration with other business systems. This improves efficiency and accuracy in document workflows.

What are the techniques used in intelligent document processing?

Intelligent document processing techniques include Optical Character Recognition (OCR) to extract text. They use Natural Language Processing (NLP) to understand content. Machine Learning (ML) to recognize and classify patterns. And they use Robotic Process Automation (RPA) to tasks like data entry and validation.

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Written by
Karishma Bhatnagar

Karishma is a passionate blogger who comes with a deep understanding of Content Marketing & SEO tactics. When she isn’t working, you’ll find her in the mountains, experiencing the fresh breeze & chirping sounds of birds.

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