Nowadays, the biggest challenge companies face, despite having an abundance of data, is utilizing this data in a smart way. Businesses hire teams to handle large amounts of data, but it can be challenging for humans to process all of it.
AI technology now enables algorithms to scan and understand digital and paper documents, just like humans. This is possible due to advancements in Artificial Intelligence. The technology is known as Intelligent Document Processing or IDP.
Table of Contents
What is Intelligent Document Processing?
Intelligent Document Processing (IDP) is a cutting-edge technology that uses Artificial Intelligence (AI) to seamlessly capture and organize specific data from any form of documents. It doesn’t matter whether your documents are structured or unstructured, IDP’s core mission is to extract unstructured documents and process it to structured information.
Intelligent Document Processing takes the help of AI-based technologies like Machine Learning(ML), Natural Language Processing(NLP) to extract, interpret and process the data from various unstructured documents.
According to industry research, more than 80% of data within any organisation is unstructured, and most of it is locked in documents. These documents can be in various forms- emails, text, PDF or scanned documents, etc.
This highlights the need for a robust tool that can automate the processing of these documents with minimal manual involvement. This is the reason why intelligent document processing tools are gaining paramount importance to the organisation’s operational success.
With Intelligent Document Processing, the diverse teams are now able to automate data capture, classification and extraction across miscellaneous documents
Intelligent Document Processing Workflow
Ideally, there are two key considerations before deploying an Intelligent Document Processing tool.
Firstly, we need to understand the kind of technology we would need to extract the required data from the document. This would largely be determined by the layout and pattern of data in these documents.
Structured data would require less advanced tools and its extraction can be easily automated using Robotic Process Automation (RPA) based automation. On the contrary, unstructured documents throw major challenges in its extraction, and require more sophisticated technology. This is because unstructured and disparate documents prevent the use of regular expressions (Regex) or template matching techniques.
Second stage is the different formats of inflowing data. In a medium or large organisation, data is received in different formats such as paper documents, faxes, attachments of emails, scanned PDFs, etc.
When organisations integrate IDP into their workflow, unstructured documents can yield organised information with minimal involvement of employees. This allows them to focus on more critical aspects of their business operations.
Ideally, an Intelligent Document Processing system is able to recognize, classify and extract distilled information and then route it to the required document workflows for review. So what are the phases to accomplish this Intelligent Document Processing?
Stages of Intelligent Document Processing:
1. Classification of Documents:
The initial phase of Intelligent Document Processing begins with classifying the type of document being processed. So one type of document can be an electronic document and the other one can be a paper one.
This classification is accomplished using the combination of Computer Vision (CV), Natural Language Processing (NLP) and Machine Learning (ML) technology.
2. Extraction of Documents:
Most significant step in the process of Intelligent Document Processing is to extract valuable information from the documents. The OCR software recognizes characters and symbols on a document as it scans the images and photographs of documents.
Other technologies that enable data extraction are Barcode Recognition, ICR (Intelligent Character Recognition) and OMR (Optical Mark Recognition).
Data extraction involves pre-processing by pattern matching tools like Regex (Regular Expression). Further, it heads to the most critical phase – Contextual text Recognition. Although OCR tools extract the entire free text from the scanned documents or images, they fail to actually understand the document like humans do.
Here, AI plays a vital role as the deep learning models actually perceive the documents and the underlying context before they extract the relevant information. This is the fundamental reason that contributes to ‘intelligence’ in the IDP.
In short, OCR helps in “text extraction” while AI helps in “document interpretation”.
3. Export Structured Data:
The next step of intelligent document processing would be to export the structured information using REST APIs. Business teams can easily use this data to make quick business decisions.
Industry Applications of Intelligent Document Processing:
A diverse range of industries can benefit from the Intelligent Document Processing (IDP) technology. Here are some of the industries where IDP plays a significant role in improving the productivity:
1. Accounting
Accounting is one sector that generates a heavy amount of paperwork and documents.
Physical documents like:
- Invoices,
- Bills,
- Contracts,
- Receipts, etc
All these documents result in lesser efficiency and stunted productivity. However, with the help of IDP technology, accounting teams can automatically process the documents and extract key information from those.
Using intelligent document processing (IDP) in the accounting sector can reduce the processing time, eliminate human errors and lessen the processing costs.
With accurate data processing, the risks of late payments gets reduced and even companies can capitalise and build their revenue.
2. Foreign Currency Reconciliations:
Automation not only simplifies but also speeds up your reconciliation processes, without compromising on accuracy.
IDP can smoothly and efficiently do repetitive tasks like transaction matching, thus offering you the capability to drill down on the open entries and exceptions that specifically need additional attention. The result?
Spares more quality time for the team to develop strategically important & qualitative activities.
3. Legal
Legal service providers deal with processing a plethora of documents every day. Some of the main documents include:
- Archiving and auditing documents,
- Mergers,
- Acquisition-related documents,
- Property filings,
- Compliance regulation documents, etc
Majority of these involve complex documentation at each stage. Apart from this, lawyers find themselves referring to volumes of information in the midst of working on a case.
The paperwork for their client/s is often handled by an associate manually and hence is prone to discrepancies and errors. Employing an automated system that uses IDP to manage data and documentation maintains security and improves the quality of work.
4. Medical records:
In the healthcare industry, maintaining records of patients is cardinal. Easy and on-demand access to information can be the need of the hour in the cases of emergency. Hence, digitization of all paperwork pertaining to patients becomes critical.
When a doctor needs to access a particular file, it becomes a task to scan through all the paperwork and find what they’re looking for.
With the help of intelligent document processing, all records and medical diagnostics can be extracted from various reports of patients’ medical history and only related information can be accessed when required.
5. Employee Reimbursement Claims Frauds Detection:
Company employees make fraudulent claims that charge a lot to the company. Manual reviews and audits can miss fictitious claims/expenses, multiple claims made for the same bills.
These claims may be part of mistake or intentional fraud, but ultimately organisations suffer in terms of financial impact.
Intelligent document processing benefits in preventing these frauds as it extracts the data from the employee expense documents, drills down through fraudulent entries and highlights the inconsistencies in the claims submitted by the employees.
This fast-tracks the disbursements and trim out the disallowed claims. As a result, businesses are saving a significant amount of cash outflows in their manual process and ledger.
6. Trade finance and consumer durable finance:
With global trade projected to grow, trade finance continues to be a significant pillar of the bank’s business model. Although the revenue growth outlook is promising, organisations need first to optimise their trade finance business to maximise profitability.
Trade finance is mainly paper-based and labor-intensive. By its very nature, trade finance maintains processes that are highly focused on documentation and checking.
This usually results in longer turnaround time, high handling, high storage costs, high error rates from manual document verification and more operational risk due to staff turnover.
Intelligent document processing can boost productivity since it deploys intelligent OCR to digitise and turn unstructured documents into readily available data sources. IDP enables faster decision-making and compliance checks through ML and cognitive RPA.
7. Supply Chain Management:
In supply chain companies, the main challenge in invoice processing is due to the complexity of semi-structured documents coupled with a lack of extensive intelligent document processing capabilities. Intelligent document processing can bring in magic here!
Since solutions that adopt IDP can match data from disparate systems and pull it together in an understandable way, these solutions can make end-to-end processes simple like:
- Purchase-to-pay,
- Order-to-cash,
- Record-to-report, etc.
Improving processes and eliminating non-value-adding tasks may offer significant savings. Also, a single platform for managing invoices and orders provides a great deal of visibility into the financial supply chain.
Advantages of Intelligent Document Processing
1. Increased productivity:
The main advantage of automation of business processes is that it eliminates manual intervention in a document-centric workflow.
With a single click, data from a document is captured, converted, sorted, indexed and routed to its destination, so it can be stored in a structured format.
This improves the overall productivity and supports the organisation to have effective operation in the workflow.
2. Optimised Savings:
Companies that have adopted the intelligent document processing (IDP) technology into their workflow have observed a significant changes like:
- Decrease in processing time
- Decrease in labour costs by up to 50%
- Reducing operational cost
- Reducing manual labour
3. Reliability:
Intelligent Document Processing helps in improving the quality by ruling out any possibility of human error while processing documents.
Whenever the data processing is done manually, information is always stored in an unstructured manner and is difficult to access quickly.
With processes that are automated with IDP, then the information is organised in a secure location and is easily accessible as well.
4. Simplified Compliance:
Intelligent Document Processing is a secure technology and maintains data privacy. Organisations contain data that is sensitive and it is of utmost importance to protect such data from being misused or manipulated.
An IDP keeps the information safeguarded by storing it in a secure location accessible only by authorised personnel.
5. Scalability:
Intelligent Document Processing is not specific to any particular process and it can be applied to multiple applications in multiple areas.
It does not require any installation, it only serves as a platform for an integrated framework where documents of different formats, sizes, and sources can be scanned and processed. This feature of an IDP system makes it highly scalable and effective.
KlearStack: Intelligent Document Processing with AI-driven OCR
KlearStack is an AI-based platform that turns clients’ unstructured documents into a competitive advantage by automating data extraction from various financial documents without human intervention of drawing templates.
Processing invoices, resumes, legal contracts, and other documents manually would be inefficient, non-scalable, complex, and might lead to errors.
However, due to Intelligent Document Processing models in KlearStack, built using OCR, AI, and ML automate these routine processes, improve efficiency, effectiveness, accuracy, and consistency across various workflows in the organisation.
To learn more about KlearStack IDP solution in details download the Intelligent document processing (IDP) Guide
Irrespective of organisation size and domain, organisations should adopt such AI based tools to reduce the wastage of resources and leakages in the cash-flow.
Enterprises should start investing in document extraction solutions. So that it can help them streamline processes, improve productivity of the employees and help them upskill at work.
If you want to know more about KlearStack’s intelligent document processing platform and how it can help your organisation, schedule for a quick demo today!
FAQs on Intelligent Document Processing
Where is intelligent document processing used?
Intelligent Document Processing is used in commercial real estate, finance, legal, insurance, banking, healthcare, supply chain management, accounting and many other fields. IDP helps in automated data extraction, which eventually reduces time, improving efficiency.
Why do we need intelligent document processing?
The most important advantage of intelligent document processing is to save time, improve efficiency, reduce manual errors, increase data accuracy, and make the workflows streamlined.
What is the difference between IDP and OCR?
Both OCR and IDP can extract and read text. But OCR (Optical Character Recognition) converts text from images to readable text. Intelligent document processing (IDP) is a mixture of OCR and AI. With the help of AI, IDP can understand and extract text.
