“Artificial intelligence will reach human levels by around 2029.” –Ray Kurzweil, a computer scientist, inventor, author, and futurist.
Just as Ray had predicted, businesses are using Intelligent Document Processing (IDP) to handle data with near-human precision. IDP automates tasks like data extraction, classification, and analysis and bridges the gap between human insight and machine efficiency.
In this article, we'll cover what Intelligent Document Processing (IDP) is, how it works for business process automation, its benefits, and tips on choosing the right IDP tool for your business.
Intelligent Document Processing (IDP) is a technology that uses artificial intelligence (AI) and machine learning (ML) to automate the extraction, processing, and analysis of data from various types of documents like invoices, contracts, receipts, emails, and forms.
Unlike traditional Optical Character Recognition (OCR), IDP incorporates advanced capabilities of AI, ML, and NLP to recognize text and understand the document’s content, context, and structure, providing more accurate and comprehensive data interpretation.
IDP enhances operational efficiency, resulting in more accurate data extraction, reduced manual effort, and improved handling of diverse and complex document types. This technology simplifies workflows and provides valuable insights from data, making it essential for organizations aiming to improve productivity and decision-making.
OCR (Optical Character Recognition)
What it does
Converts documents into editable and searchable text.
How it works
Recognizes text from scanned images and turns it into digital text.
Accuracy
High for simple, well-structured documents; drops with poor quality or complex formats.
Scalability
Easily scalable for handling increased volumes, especially with cloud-based solutions.
Template requirement
Requires templates to operate, which can be costly and difficult to maintain.
Learning capability
Does not improve over time; it requires manual adjustments.
Use cases
Suitable for basic tasks like digitizing documents, IDs, or converting books.
IDP (Intelligent Document Processing)
What it does
Automates the extraction and analysis of data using AI, NLP, and ML.
How it works
Uses AI and ML to extract, process, and understand data from various document types.
Accuracy
Very accurate for structured and semi-structured documents; improves with unstructured data over time.
Scalability
Highly scalable, ideal for large document volumes and cloud-based environments.
Template requirement
Works without rigid templates, adapting to different document formats.
Learning capability
Uses machine learning to continuously enhance accuracy and efficiency.
Use cases
Ideal for automating complex business processes like invoice processing, claims management, and customer onboarding.
Let’s take a closer look at the technology behind Intelligent Document Processing and how it powers advanced automation.
Here are the top five technologies used in Intelligent Document Processing:
The global intelligent process automation size, as per revenue, is expected to reach over $25.9 billion in 2027, growing at a CAGR of 13.8% for the period 2022-2027, with its main drivers being RPA, ML, AI, and cognitive learning technologies. These technologies work together to enable Intelligent Document Processing, streamlining document-heavy complex tasks like data entry, document classification, and data extraction.
Implementing Intelligent Document Processing can reduce errors by over 52% and achieve an accuracy rate of 99%, significantly reducing the risk of critical errors commonly associated with manual document handling.
The accuracy of IDP systems is influenced by several factors, such as:
IDP represents a significant advancement over traditional document processing methods, providing organizations with reliable data extraction capabilities that support better decision-making and operational efficiency.
The evolution of IDP is a remarkable journey marked by significant technological advancements.
Historical Background
The roots of IDP trace back to Optical Character Recognition (OCR) technology, which emerged in the early 20th century. In 1914, Emanuel Goldberg invented a machine capable of reading characters and converting them into telegraph code, laying the groundwork for future developments in document processing.
Intelligent Document Processing has changed how organizations manage documents. As the amount of data grew, OCR’s limitations became clear, leading to the creation of IDP.
From OCR to IDP
To improve efficiency, IDP was developed, allowing organizations to automate over 80% of document tasks, reducing the need for human work.
Handling Unstructured Data
IDP can process unstructured data, which makes up a large part of company information. It uses natural language processing (NLP) to understand and pull relevant details from a variety of document types, including handwritten notes and images.
Expanding Use Cases
IDP is used in a wide variety of industries for tasks such as invoice processing and compliance checks. It identifies and categorizes documents according to well-defined rules, which are established by business analysts and subject matter experts.
Future Trends
In the future, IDP will expand as document types grow more complex, incorporating multi-format integration for processing audio and video content alongside traditional documents. This advancement will enhance business process automation through data extraction and analysis for managing claims and reports.
As per the report by MarketsandMarkets, “The global Business Process Automation Market size is projected to reach $19.6 billion by 2026, growing at a CAGR of 12.2% during the forecast period, 2022-2026.” This projection clearly underlines the need for businesses to adopt intelligent document processing, gaining competitive advantage and streamlining business operations.
Understanding how Intelligent Document Processing works is crucial for enhancing efficiency, reducing costs like operational costs or labor costs, and ensuring compliance, allowing organizations to automate workflows effectively.
The first step in IDP involves gathering documents from multiple sources to create a centralized repository for intelligent automation. This ensures that all relevant documents, whether physical or digital, are captured and ready for processing.
Pre-processing enhances the quality and format of the documents to prepare them for accurate data extraction. This step is crucial for improving OCR results and ensuring the data is machine-readable.
Documents are sorted into categories based on their type and content, enabling the application of specific processing rules for each category. This classification is essential for managing diverse document types effectively.
Key data points are identified and extracted from the documents, transforming unstructured data into structured information. This step leverages advanced technologies to ensure the accuracy and relevance of the extracted data.
The extracted data is checked for accuracy and consistency to meet quality standards. This step involves cross-referencing data with existing records and applying business rules.
The final step involves formatting the data and integrating it into business systems to enable seamless workflows. This step ensures the processed data is ready for further use and automation.
By delving into each step of intelligent document processing, you can get a clear understanding of how the technology works and how to implement it effectively. This knowledge enables your organization to optimize your document workflows, resulting in enhanced productivity and operational efficiency.
For instance, Docxster streamlines document processing through this multi-step approach. First, it captures documents from various formats and automatically classifies them based on content. Next, it uses advanced NLP to analyze and extract relevant data, ensuring accuracy through machine learning and OCR. Finally, it provides analytics for workflow optimization, enhancing efficiency and decision-making.
Intelligent document processing offers a lot of advantages by automating the extraction, processing, and analysis of information from various types of documents. This not only enhances operational efficiency but also drives better decision-making, compliance, and customer satisfaction.
Let’s look at a few key benefits of Intelligent Document Processing across various industries:
Intelligent document processing can save finance departments 25,000 hours of rework and $878,000 annually due to human errors for organizations with 40 full-time accounting staff, according to Gartner.
Benefits of IDP in banking and finance:
Benefits of IDP in healthcare industry:
Benefits of IDP in insurance industry:
Benefits of IDP in manufacturing industry:
In December 2022, in Nakano-ku, Japan, the government reduced its work volume by 30% and outsourcing costs by 25% by using IDP solutions to transform its resident tax collection process.
Benefits of IDP in accounting and finance:
Benefits of IDP in Human Resources:
Each of these sectors benefits from IDP through reduced manual effort, faster processing times, and improved accuracy, ultimately leading to enhanced productivity and customer satisfaction.
Choosing the right Intelligent Document Processing solution for your business involves several key considerations:
Identify the types of documents (invoices, contracts, etc.) and the volume you process regularly.
Look for high accuracy rates in data extraction and effective error-handling mechanisms.
Ensure the solution integrates seamlessly with existing systems and supports APIs for custom integrations.
Choose a user-friendly interface and check for available training and support resources.
Opt for a solution that can scale with your business growth and handle increasing document volumes.
Ensure robust data security measures are in place and the solution complies with relevant regulations.
Research the vendor’s experience and read customer feedback to gauge reliability.
Evaluate the pricing structure and potential return on investment by considering reduced manual labor and errors.
Seek live demonstrations and free trials to test the solution’s effectiveness with your document types.
By considering these factors, you can select an IDP solution that enhances efficiency and accuracy in your document processing workflows.
We’ve already discussed what to look for in the right IDP software. Let’s explore the top five Intelligent Document Processing solutions available. These tools can help you manage your documents more easily and improve your business operations.
Docxster is an advanced AI-driven platform specializing in Intelligent Document Processing. It can automatically read and organize documents like invoices, receipts, and contracts. Here’s a simple overview of what Docxster offers:
Key Features
Free Forever Plan
Docxster offers a "Forever Free" plan that gives you access to basic features at no cost. This allows businesses to enjoy the benefits of AI document processing without spending any money
UiPath is a leading company in intelligent automation, offering strong Intelligent Document Processing features that work well with its robotic process automation (RPA) platform.
It uses artificial intelligence and machine learning to handle unstructured data, helping businesses automate repetitive tasks and boost efficiency.
Key Features:
Automation Anywhere offers an Intelligent Document Processing solution that uses AI, machine learning, and robotic process automation (RPA) to fully automate document-related tasks. It is great at turning unstructured data into organized formats, making it easy to fit into business workflows, which helps improve productivity and accuracy.
Key Features:
Docsumo aims to make document processing easier by using AI to automate data extraction and validation. It works well with invoices, forms, and contracts, helping organizations reduce manual work and speed up processing times.
Key Features:
Nanonets focuses on offering customizable Intelligent Document Processing solutions that can fit different business needs. Their platform uses machine learning to improve the accuracy of data extraction from documents and allows for easy integration with existing systems, making it a flexible option for many organizations.
Key Features:
These IDP solutions enhance efficiency and empower organizations to leverage their data effectively, ultimately driving better business outcomes with intelligent automation.
As companies explore automation solutions, investing in an IDP system could be a strategic move that positions them for success with digital transformation.
Embracing IDP streamlines operations and empowers organizations to confidently make data-driven decisions, ultimately leading to better customer experiences and a stronger competitive advantage. The transition to IDP is not just about adopting new technology; it's about reimagining the potential of organizational workflows and unlocking new opportunities for innovation and efficiency.
Looking for an ideal IDP solution? Docxster is here. Try Docxster for free and see how it can streamline your workflow and amplify your growth!
1. What is the difference between OCR and intelligent document processing?
OCR (Optical Character Recognition) simply converts printed or handwritten text into digital format, while Intelligent document processing not only digitizes text but also interprets, classifies, and processes the data using AI technologies.
Intelligent document processing can handle invoices, contracts, receipts, forms, and reports. It works with both structured and unstructured documents, including handwritten text. It also processes various file formats like PDFs and images.
Yes, IDP can handle handwritten text using advanced AI to recognize and interpret different handwriting styles. While accuracy varies, many IDP solutions can effectively extract information from handwritten documents.
Intelligent document processing (IDP) automates data extraction and entry, speeding up document processing and reducing errors. It ensures data accuracy with validation techniques and allows staff to focus on higher-value tasks, boosting overall efficiency.
Intelligent document processing (IDP) focuses on extracting and processing data from documents using AI, whereas Robotic Process Automation (RPA) automates repetitive, rule-based tasks across various applications without necessarily involving document data extraction.
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