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A strategic guide to intelligent document processing
By adopting intelligent document processing solutions, finance departments alone can save 25,000 hours of rework caused by human errors at a cost of $878,000 per year for an organization with 40 full-time accounting staff, according to a Gartner press release.
Intelligent document processing enhances the human understanding of unstructured data through data science tools like computer vision, optical character recognition, machine learning and natural language processing.
The reason why intelligent document processing is gaining traction is that it provides solutions to automate data extraction tasks that were previously difficult, if not impossible to solve.
What’s new is the single platform solution that is transforming the way we work. New sources of data create better business outcomes and pave the way for human-initiated innovation.
Intelligent document processing tools are powerful software that charges the data supply chain with labeled data from any text-based source.
What is intelligent document processing?
Intelligent document processing automates the extraction and processing of data from a variety of document formats.
It uses deep learning tools to automate document processing. With the help of RPA bots, AI and computer vision, intelligent document processing extracts unstructured data from documents (e.g., email text, PDF and scanned documents) and converts it into structured data.
As defined by Deloitte, “intelligent document processing automates the processing of data contained in documents ― understanding what the document is about, what information it contains, extracting that information and sending it to the right place”.
How IDP works?
Embedding document processing software within the RPA platform is what enables business users to automate processes end-to-end. When IDP and RPA are brought together on the same platform, you have the two important pieces of the automation puzzle working in sync, seamlessly.
While IDP is a major as well as significant component of the automation workflow, RPA brings everything together – starting with downloading a document from a source such as an email and sending it for processing.
After structured and unstructured data is successfully extracted, the platform facilitates validation and decision-making. Successfully extracted data is then entered into a system of record, completing the workflow.
RPA also offers the flexibility of integrating any content-driven platform easily.
While the goal of IDP is simple to articulate in theory, in practice it can take a number of different forms.
5 Intelligent document processing stages and components
- Pre-processing – As documents arrive to be processed in various conditions, IDP applies techniques such as noise reduction, binarization and de-skewing to maximize the quality of documents.
- Image processing – IDP first uses computer vision to understand document structure and identify “features” such as text, graphs and pictures. Older technologies such as OCR and ICR can then be leveraged to extract text from the document. During this process, some IDP solutions create a digitized version of the document or “digital twin,” that is primed for machine-reading.
- Classification and data extraction – Using machine learning (ML) and NLP, IDP automatically identifies, separates and classifies document components. An IDP’s classification engine is responsible for parsing out all these different components, accurately categorizing them and routing them to their next destination. One of the key deliverables of IDP systems is their ability to pinpoint valuable information and extract it for further analysis or processing. To accomplish this, IDPs often include a library of pre-trained extraction models or a pattern matching tools such as Regular Expressions (RegEx).
- Data Validation – IDP platforms leverage external databases and pre-configured lexicons to validate data extracted from documents. Not only does this process ensure the data quality, but that data is collected in the right format and prepped for immediate usage. The data validation process typically leverages a HITL (Human-in-the-Loop) machine learning framework, whereby problematic data is routed to humans to review and correct. This approach enables the validation model to continuously learn and improve its accuracy over time.
- Integration – The last step of the IDP process is to integrate the validated data into large enterprise systems and workflows.
- BI and analytics – Business intelligence is also a good reason to choose intelligent document processing. The solution can provide a complete overview of all the bots operating in an environment, offering real-time operational insights such as the number of document processes at work, accuracy rates and information relevant to business outcomes. At a glance, users can get insights on processes end to end.
Advantages of using a fully integrated document processing platform
Document extraction solutions or traditional optical character recognition (OCR) will only solve a small part of the processing problem. In other words, you will need to think about the bigger picture.
Consider everything that’s involved in processing a document to ensure smooth, fast operation with no errors to get the highest return on your investment.
And that’s why an end-to-end automation solution (a platform approach to IDP), powered by Robotic Process Automation (RPA) and artificial intelligence (AI) makes sense.
Let’s dive right into other advantages of using a fully integrated document processing platform.
1. Increased effectiveness and efficiency
On average, simple manual document processing costs around $6-8 per document. For more complex documents, average cost per document can be upwards of $40-50. More than 70% of businesses would fail within 3 weeks if they suffered a catastrophic loss of paper-based records due to fire or flood.
According to industry experts, intelligent document processing ushers in a variety of significant changes.
- Reduce the risk of errors by 52% or more
- Reduce the expense of manual document processing by 35%
- Reduce time spent on document-related tasks by 17%
- Reduce document processing times by 50-70%
- Reduce operating costs by 30% YOY
- Reduce document verification time down by 85%
- Reduce the entire financial aid application process down from 6 weeks to just a couple of days
- Achieve a 99% accuracy rate
2. Improved compliance and security
An intelligent document processing solution’s impressive accuracy rate makes it the ideal solution for handling any compliance-related document or those that include sensitive information such as personally identifiable information (PII) or health records. As IDP eliminates the need for humans to open up, review or handle any of the data included documents, it minimizes the risk of exposing sensitive information to outside parties. In addition, IDP can help streamline and maximize the accuracy of regulatory reporting.
3. Enhanced data quality and usability
On average, 80% of an organization’s data is “dark data” — meaning it’s locked in emails, text, PDFs and scanned documents. Using RPA and AI-based tools, IDP unlocks the value of dark data by transforming into high quality, structured data that is primed for analysis.
As the experts at Mckinsey explain, “by combining the data derived from paper documents with the wealth of digital data already available, a comprehensive data landscape can be established, significantly enhancing data evaluation and analytics possibilities.”
4. Promotes and scales automation
Along with workflow management tools, intelligent document processing is a powerful enabler of end-to-end process automation. It helps link various systems that go into automating complex business processes and achieving hyperautomation.
Furthermore, cognitive technologies such as RPA and AI need structured high-quality data to “learn” from and operate. By transforming unstructured data found in documents into streams of cleaned, structured data, intelligent document processing optimizes data for RPA/AI consumption as well.
It saves resources on data entry, makes critical information available faster, and helps businesses to build a digital workforce.
A checklist when choosing an automation tool
What to look for in an automation tool? Consider this checklist when starting out on your automation journey.
- A fast start: How much time and effort will your prospective solution require to get you started with your first document?
- Ease of use: How easy is it to operate and maintain day to day?
- Intelligence: How resilient is it to document format changes? Can it extract data based on content using machine learning models?
- Straight-through processing improvements: Does your prospective solution provide better ROI over time as it learns from your corrections?
- Automation end to end: Is it just a document processing solution or can it help you automate data entry downstream and drive insights from the data?
Choose a solution with all the items on the checklist. And that’s where a fully integrated or native, intelligent document processing (IDP) platform comes in.
Relevant industries for IDP
Organizations are overwhelmed by documents. So, the potential impact of intelligent document processing is immense in paper-heavy processes.
Automation software can extract and organize data across industries and business functions, right out of the box.
- Financial services (including loan and claims processing and bank account openings)
- Healthcare (including medical forms, billing, and patient records)
- Business functions— F&A (invoices and purchase orders), HR (employee forms and onboarding documents), IT (employee records and service requests), and others.
- Aviation – (Contactless check-in, boarding of passengers in the post-covid world)
Intelligent document processing use cases
IDP solutions tend to be “non-invasive” and easily integrate into existing systems, business applications and platforms. They also run from a wide range of pre-built, out-of-the-box solutions to more complex, bespoke implementations.
- Invoice Processing
- Digital Document Archiving
- Insurance Claims Processing
- Fraud Detection
- Case Reviews
- Contract Administration
- Mortgage Loan Application Processing
- Customer Onboarding
IDP solution providers
1. Azure Form Recognizer
Applies advanced machine learning to accurately extract text, key-value pairs, tables and structures from documents. Tailor Azure Form Recognizer to understand your documents, both on-premises and in the cloud. Turn documents into usable data at a fraction of the time and cost, so you can focus more time acting on the information rather than compiling it
2. Hyperscience
An input-to-outcome platform for the automation of document-based workflows. Hyperscience embraces a human-centric approach to product design, creating solutions that not only provide stellar UX, but aim to enhance human behavior and decision making rather than replace it. Customers include TD Ameritrade, ONE Insurance and Fidelity Investments.
3. Automation Anywhere
Uses AI technologies such as natural language processing (NLP), Computer Vision, deep learning and machine learning (ML) to classify, categorize, and extract relevant information, and validate the extracted data.
4. Amazon Textract
A fully managed machine learning service that automatically extracts handwriting, printed text, and data from scanned documents. With Textract you can quickly automate manual document activities, enabling you to process millions of document pages in hours.
The time is ripe for intelligent document processing
It is true that the time is ripe for intelligent document processing where AI is playing a significant role in advancing document processing. Yet there is more innovation to come in this space.
- First, as the formats and structures of semi-structured and unstructured documents continue to explode, AI models will need to keep up. From reading overly complex table structures to processing government-issued IDs with holograms or watermarks, AI models will be challenged to remain accurate.
- Second, while this space has been coined intelligent document processing, video and audio file types are on the rise. It is only a matter of time before these file types are on the critical path for processing insurance claims or filing police incident reports.
So stick around, it is sure going to be an exciting journey.
