According to PWC, there are over 4 trillion paper documents in the U.S. alone, and the number is growing at 22% each year.
Unfortunately, these documents still exist largely in business operation scenarios. It doesn’t matter what industry you pick, you’ll most likely find them in large volumes.
The most problematic thing is that documents and information are still being received in unstructured formats that cannot be read or processed by software. Why is that? Because often these paper documents need to be scanned and sent to the various parties via emails.
Next to scanning documents, someone then has to manually sort, convert, extract, and validate data on them. As you can imagine, this is an extremely slow and time-consuming process. The worst part is that this old way of working invites a large number of critical human errors.
Fortunately, there are innovative technologies that can help organizations process documents faster and simplify operational procedures. One of them is Intelligent Document Processing (IDP).
This blog will explain what Intelligent Document Processing is, how it works, what the benefits are, and the most common use cases. So keep reading to learn more about how IDP can enhance your business operations!
What is Intelligent Document Processing (IDP)?
Have you ever seen a sophisticated technology that can understand what a document is about, what information it contains, extract that information, and then deliver it to where it’s needed (e.g. database, ERP system)? Well, that’s Intelligent Document Processing (IDP) in a nutshell.
IDP is a form of intelligent document automation that leverages data science to help machines understand unstructured data and pass it on further as structured data. Structured data forms often include CSV, JSON, and XLSM that can be sent to ERP systems for instance.
Intelligent Document Processing simply automates document processing workflows, using various technology components. These technology components can include:
- Optical Character Recognition (OCR)
- Artificial Intelligence (AI)
- Computer Vision
- Machine Learning (ML)
- Natural Language Processing (NLP)
- Robotic Process Automation (RPA)
Let’s dive into the roles of each of these technologies next.
Optical Character Recognition (OCR)
Optical Character Recognition (OCR) is a technology that extracts data such as text from images or scanned documents with its ability to identify individual characters.
It also converts extracted text into a machine-readable output such as JSON. These are the tasks of OCR in an IDP solution.
Next to that, OCR technology performs several steps to increase the quality of images for more accurate results. You can read more about it in our ultimate guide to OCR.
Artificial Intelligence (AI)
Artificial Intelligence is a computer system that performs tasks, which previously required human intelligence and involvement.
Within Intelligent Document Processing solutions, AI extracts meaning from images, documents or handwritten texts, detects both patterns and anomalies and makes predictions based on algorithms.
Next to that, AI makes the solutions smarter over time, allowing IDP to continuously improve in terms of accuracy (e.g data extraction, classification).
There are four different ways that AI can be utilized:
- Automated intelligence – Simple tasks are automated and don’t require any human involvement.
- Assisted intelligence – Requires human judgment and decision-making for more complex tasks, but the recommendations are provided by the AI system. This is also known as human-in-the-loop automation.
- Augmented intelligence – Focuses on adaptive systems to improve algorithms with the experience and decision-making of humans.
- Autonomous intelligence – AI systems are adaptive and make decisions without any human involvement.
Computer vision is a form of AI that focuses on deep learning that enables computers to understand meaningful information from digital images, videos, and other visual content.
Within an IDP solution, computer vision allows it to see, observe, and understand objects. For example, computer vision can recognize objects such as price tags, soda cans, license plates, utility meters, etc.
It is very much comparable to human vision. Although, with proper data and algorithms, computer vision has the potential to surpass human capabilities in terms of speed and scalability.
Machine Learning (ML)
Machine learning is a branch of Artificial Intelligence (AI), which makes use of algorithms and feeds data to a computer to help the computer learn how to get better at a task.
By implementing statistical techniques, there is no need to write a million lines of code just for the computer to perform a certain task.
The role of Machine Learning in an IDP solution is to train the solution to get better at performing the tasks (i.e., document processing tasks) with a high degree of accuracy.
Natural Language Processing (NLP)
Natural Language Processing (NLP) is also a component of Artificial intelligence, which focuses on enabling computers to understand the full meaning of a text or spoken words in the same way humans are capable of.
NLP enables IDP solution to understand data quicker and more intelligently.
One of the techniques it uses is Named Entity Recognition (NEM) which is the identification of words or phrases in documents. For example, NLP makes it possible for IDP to understand that “Jane” is a woman’s name, and “Amsterdam” is a location.
Robotic Process Automation (RPA)
Robotic Process Automation (RPA) is the automation of rule-based processes with software that often utilizes a user interface. In this type of automation, the software performs tasks that are codified by computers, hence referred to as “robotic” or “robots”.
The technology is efficient when dealing with structured data with little to no variations. The role of RPA in an Intelligent Document Processing solution is to capture information from structured sources. By doing so, IDP can process a transaction or communicate with other digital systems with a set of rules.
Now that we’ve covered the key technologies behind IDP, let’s break down some differences between the following terminologies: IDP, OCR, and RPA.
IDP vs RPA vs OCR
Intelligent Document Processing and Robotic Process Automation both strive to automate processes such as data extraction. How these two solutions differ from each other is by their approach – RPA focuses on rule-based automation, while IDP focuses on AI-based automation.
Often, combining the two approaches benefits organizations more, as not all data is in structured or unstructured formats. Structured document formats are often best suited for RPA to process whereas IDP processes unstructured miles better.
Enterprises can achieve significantly better operational efficiency with the combination of both.
OCR is the underlying technology that is integrated within both RPA and IDP to turn images into text, which is the foundation of data extraction from documents. Without OCR, neither IDP nor RPA could extract data from documents, images, etc.
However, there are a few things that OCR and RPA have in common:
- They struggle to process a variety of documents
- They have limited scalability
- They lack a deeper cognitive understanding of the documents
Intelligent Document Processing, on the other hand, doesn’t have any problems with the previously listed limitations. In fact, it often uses the combination of OCR and RPA to process structured documents and achieve higher accuracy.
Now that we explained the differences between RPA, OCR, and IDP, let’s zoom closer into IDP: what it does and how it works.
How does Intelligent Document Processing work & what can it do?
It’s now clear that Intelligent Document Processing is a sophisticated evolution of OCR that leverages AI to automate tasks within document-related workflows. But what can it actually do? Let’s look at the list of functions that IDP often provides:
- Data Capture
- Data Extraction
- File conversion
IDP captures data from various sources into a computer system for further processing, often with a mobile device. It can be used to scan and capture data from various documents such as receipts, invoices, ID cards, purchase orders, and many other documents.
Upon receiving a scanned or captured image of a document, IDP intelligently extracts relevant data from it using OCR and AI algorithms. All types of data can be extracted including:
- Structured data – Data that is organized and has a logical structure (e.g. CSV, JSON, XML)
- Unstructured data – Requires manipulation such as data cleansing before the data extraction process as it does not always have a logical structure for machines to read (e.g. emails, images, scanned documents)
The more refined algorithms, the more accurate data extraction.
After data extraction, IDP uses AI algorithms combined with NLP to identify document types by matching unknown documents to existing categories.
The characteristics are extracted and fed to the algorithms, which calculate a similarity score. The similarity score is used to determine the most accurate category for document classification.
A few Intelligent Document Processing solutions can automatically anonymize sensitive information from documents. What it entails is the removal or encryption of sensitive data, such as social security numbers for GDPR compliance and other privacy regulations.
After the previous steps, IDP can authenticate the document by comparing it to official records and databases. This is done to avoid harmful fraud attempts and minimize the risks of receiving fabricated documents.
Intelligent Document Processing solutions can use the following methods to detect fraud:
- Data integrity – AI algorithms check data fields to determine the document validity (signatures, merchant names, invoice numbers, dates, etc.)
- Document authenticity – AI algorithms search for anomalies in documents that are hard to detect by human eyes (changes in font, pixel quality, metadata changes, holograms, etc.)
- Facial biometrics – AI algorithms determine whether a person’s face matches with the photo that is uploaded or scanned to verify that it’s the same individual (mostly in Identity Verification related use cases)
Delivery & Integration
After document verification, IDP delivers the machine-readable output to the desired destination, whether it’s a database or an Enterprise Resource Planning (ERP) system.
This very much depends on which types of integrations the Intelligent Document Processing solution provides.
Now that we’ve covered what IDP is capable of, let’s take a look at the main benefits.
The 8 Benefits of Intelligent Document Processing
Intelligent document automation with IDP solutions can be very powerful in making document-related processes more efficient. There are quite a few benefits that you can seek out:
- Increased productivity by six hours a week
- Reduced processing time by 90%
- Up to 99% data extraction accuracy
- Easy data accessibility with digitization
- Improved security & compliance
- Scalability for business growth
- Over 80% cost reduction for a healthier bottom line
- Enhanced data quality and usability
Increased productivity by six hours a week
It is stated by Smartsheet, that close to 60% of surveyed workers estimated that automating repetitive tasks would free them up six or more hours a week (nearly a full workday). This is where IDP comes into play.
IDP can automate a variety of tasks such as manual data entry or document verification. With a simple click of a button, it can capture, convert, categorize, verify and deliver the data to the right endpoint. By doing so, you can increase the productivity of your workforce.
Reduced processing time by 90%
Say that an employee on average needs about two minutes to sort a document and extract the data from it. An IDP solution can do it within 10 seconds. This would mean over 90% of time reduction.
The speed with which IDP solutions process large volumes of data is one of the most notable benefits of using them.
Up to 99% data extraction accuracy
Tedious tasks such as manual data entry are prone to errors. Generally, people aren’t more than 95% accurate. With larger volumes, each % of the errors made can easily cost thousands of euros, eating up your bottom line.
In comparison, an IDP solution can help you achieve more than 99% data extraction accuracy without increasing your overheads.
Easy data accessibility with digitization
Receiving documents and converting them to a digital format is not a problem, regardless of whether they are structured or unstructured. IDP can easily convert any document to a machine-readable format that can be accessible to the parties and systems intended.
Next to that, it can categorize, sort, and route documents to the right department and platform. Cool thing is that you don’t need to engage with an enormous backlog of paper documents anymore.
Improved security & compliance
Another major benefit of Intelligent Document Processing is that it helps businesses improve their regulatory compliance. How?
It can define sensitive data fields such as fields with personally identifiable information (PII), and use data masking to redact or anonymize them. This helps companies ensure compliance with data privacy regulations like the GDPR or HIPAA.
Next to that, IDP solutions use various techniques to detect fraud, which can be useful for Know Your Customer (KYC) and Anti-Money Laundering (AML) checks in the financial industry.
Scalability for business growth
Intelligent Document Processing solutions enable businesses to process documents in large volumes with a speed that a human can’t replicate. It does it without increasing costs.
While your business scales and the volume of documents increases, IDP makes sure that you don’t need to hire more people or spend more money.
Over 80% cost reduction for a healthier bottom line
Sometimes, businesses struggle to keep operational costs low. This brings us to one of the major benefits of IDP, which is cost reduction.
On average, manually sorting a document and entering data into a system can cost anywhere from €4-6 per document. With RPA, the cost per document can be reduced to €1-2 and IDP to less than €0.50.
That’s over 80% cost reduction compared to doing everything manually. Generally, the more documents you process, the more money you save.
Give our ROI calculator a try to see how much you can save up!
Enhanced data quality and usability
As 80% of business data comes in unstructured formats, data quality and usability are not an easy feat for many. This is exactly where Intelligent Document Processing excels.
It is not restricted by the type of document. In fact, it can process and extract data from unstructured and structured documents as long as the AI models have been trained properly.
Once data is extracted, it is converted into machine-readable output. As it can be configured to extract only relevant data, you don’t need to worry about whether the data is well-organized or not. Thus, IDP enhances data quality and usability.
Now that we’ve covered the main benefits of Intelligent Document Processing, let’s go through some of its use cases.
What are the use cases for Intelligent Document Processing?
It should be clear by now that organizations deploying IDP to automate their document workflows can significantly benefit from it. But how can you use it in your business case? Below, we have listed the most common use cases that we often encounter:
- Anonymization of social security numbers
- Automated invoice processing
- Automated data entry
- Automated receipt clearing for loyalty campaigns
- Blacklining payment card numbers
- Client onboarding
- Digital archiving
- Document fraud detection
- Document completeness checks
- KYC automation
- Résumé redaction
- VIN extraction
There are many more use cases for IDP. So, don’t panic if yours is not there! Keep on reading to find out how Klippa can solve your document processing challenges!
Intelligent Document Automation with Klippa DocHorizon
In conclusion, if your business only processes a small number or less variety of documents, then perhaps RPA is a better solution to start with. Often RPA needs intelligence, especially when you deal with documents in multiple languages, formats, and structures. For that, you’d need Intelligent Document Processing.
This is why we at Klippa can confidently automate your document workflows at scale with our AI-powered IDP solution, DocHorizon. It will take your data extraction, classification, document conversion, masking, and verification to the next level.
Our intelligent solution is often used as the backbone of document processing automation on a larger scale. It is made accessible via API and SDK. With our onboarding team and well-structured documentation, it won’t take you more than a day to get started!
We recommend you to book a demo below to start your journey to become a document processing champion!