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Intelligent document processing (IDP), also referred to as intelligent data capture, is the next generation of automation that can capture, extract, and process data from a variety of document formats.
Intelligent document processing refers to software solutions that use the power of AI and machine learning technologies to efficiently process all types of documents, extract relevant information, and then feed the output into downstream applications such as process automation solutions, document management, and so on.
It is considered one of many automated data capture methods available.
According to Gartner, companies globally increase their use of paper by 25% per year. Without automation solutions, organizations need to scan paper documents, and employees need to manually extract information in order to organize and decrease the time required to retrieve these documents in the future.
However, with the technology advancement, new methods for automatically extracting information from documents, such as OCR and ICR, were developed.
In order to meet their difficult intelligent document automation and digitization demands, businesses want more complicated, adaptable, and precise solutions than OCR.
Because unstructured data accounts for 80% of an organization’s content and information generation will continue to grow, businesses will need more powerful solutions that can automate the entire process of capturing, extracting, and processing content with minimal human intervention, resulting in intelligent document automation.
In this post, we will define Intelligent Document Processing (IDP), compare it to other document capture approaches, and discuss the benefits it provides companies.
What is Intelligent Document Processing?
Intelligent document processing is the automation of data extraction from complicated semi-structured/unstructured documents and transform it into structured useable data providing end-to-end automation to document-centric business practices.
Intelligent document processing converts unstructured data by utilizing technologies such as Artificial Intelligence (AI), Machine Learning (ML), Optical Character Recognition (OCR), and Intelligent Character Recognition (ICR) to classify, categorize, extract, and validate the extracted data.
The majority of these technologies are simple to connect with other enterprise systems like as ERP, CRM, and DMS.
The bulk of organizations’ information is unstructured, and it contains important data that businesses must comprehend and use in order to continue to improve, learn how to improve their customer experience, modify their business model, or just study data.
IDP can automatically identify through all of this data, extract important information, classify it, and drive the flow of information for simpler management and better business decisions.
Always keep in mind that data is an organization’s most important asset, which this technology makes instantly accessible for business operations processing.
In today’s increasingly digital and automated world, the ability to extract data within documents is becoming increasingly important.
Intelligent document processing (IDP) is gaining popularity because it offers innovative solutions for automating intelligent data extraction tasks that were previously exceedingly difficult,
Intelligent Document Processing Benefits
Intelligent document processing helps organizations integrate with other core business applications, minimize human intervention, handle challenges associated with reading complicated document formats, and fulfill legal and compliance requirements.
Despite having a wealth of data, the largest problem companies face today is leveraging this data in a responsible way that is most relevant to their performance.
Intelligent document processing is gaining attention as it helps organizations reduce costs, enhance accuracy, speed up automation, improve productivity, and simplify compliance.
Intelligent document processing reduces the costs of manually processing documents, extracting information, and feeding other business systems.
Companies that have used IDP technology into their workflow have seen a considerable reduction in processing time and reduced labor expenses by up to 30%.
It is not sufficient to extract data; it must be highly precise and of high quality.
Extracting data with high precision is crucial for businesses since content is where employees spend the bulk of their time exploring, updating, and making critical business choices.
It provides trainable machine learning technology for continual categorization accuracy improvement.
IDP aids in quality improvement by eliminating the chance of human mistake when processing papers.
Intelligent document processing solutions readily interface with your organization’s systems, such as business automation solutions, allowing you to simplify business operations with little to no human participation.
End-to-end process automation is made possible by IDP. Because IDP can be linked to any platform, it helps connect all of the systems involved in automating complicated business processes.
IDP combined with RPA allows organization to fully automate enterprise business processes.
Because IDP solutions can process documents with little to no human interaction, your organization’s workers can devote the time required to manually extrapolate data to focus on more strategic work
Intelligent document processing significantly improves performance by automating manual labor processes such as data input, document sorting, and information validation and reducing the time necessary to handle these documents.
Simplified Compliance & Security
Intelligent capture connects information to an audit trail, which aids in compliance with government requirements and ensures the correct retention of documents and other sensitive data.
It reduces the possibility of sensitive information being exposed to unauthorized parties. Furthermore, IDP can assist to streamline and improve the accuracy of regulatory reporting.
Intelligent Document Processing vs OCR
Even though IDP and OCR are frequently used interchangeably, there is a big difference between these terms.
OCR is used to turn almost any image containing written text into machine-readable text data. IDP uses cognitive technologies to classify, categorize, extract, and validate the extracted data. IDP employs OCR technologies to extract data thus OCR is considered a subset of IDP.
IDP was created to address the shortcomings of OCR, especially its inability to extract data from complicated documents.
To summarize, OCR is a subset of IDP, but not the other way around.
Intelligent Document Processing Components
An Intelligent Data Processing system will be able to detect, categorize, and extract distilled information, which will then be sent to the appropriate document workflows for review.
To effectively process complicated documents automatically, IDP follows three phases.
The first step is intelligent document capture. As a prerequisite, scanning should already be in place to convert paper documents—physical mail—into digital images.
Using technologies like AI, ML, OCR and ICR, relevant and important data will be captured from these documents.
With the help of these technologies, semi structured and unstructured documents can be processed and it has increased the accuracy of data being extracted.
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In this phase, the processor pulls important information transferred within documents from the output of the first phase and other digital sources by utilizing a pattern matching tool such as Regular Expressions.
The artificial interpretation of information is critical to successful data extraction. Because AI is only as intelligent as its training, the system must be able to locate and classify all anticipated information inside a document.
To assure the correctness of the processing outputs, the extracted data is subjected to a number of automatic or manual validation tests.
IDP systems are distinct in that they utilize external databases to verify information. Any information that does not match is highlighted for human inspection and correction.
The collected data is then compiled into a final output file, which is commonly in JSON or XML format. APIs are used to send the file to a business process or a data repository.
The collected information should be saved somewhere or transmitted to be processed by automated business processes.
Many solutions provide interfaces with CRM, ERP, and DMS systems, allowing extracted data to be automatically saved, organized, and secured in these systems.
Intelligent Document Processing Use Cases
Organizations in a variety of sectors can benefit from IDP capabilities to save time and boost efficiency while processing papers.
Among the possible applications are:
- Invoice Processing
- Digital Document Archiving
- Insurance Claims Processing
- Fraud Detection
- Contract Administration
- Mortgage Loan Application Processing
- Employees Onboarding
Organizations are increasingly trying to automate their workers’ monotonous and time-consuming activities in today’s digital environment, particularly following COVID-19, to let them to focus on more essential subjects.
Employees will spend a significant amount of time retrieving important business information as the amount of data created continues to grow. Scanning and other technologies have shown to be useful in many situations, however complicated unstructured documents require a superior method of processing.
Intelligent document processing has enabled the automation of corporate operations and the improvement of overall efficiency and productivity.