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What is Intelligent Document Processing(IDP)?
Intelligent Document Processing automates data capture, understanding and categorization from multiple documents and data sources. IDP turns scanned documents, invoices, email attachments etc. into a categorized and machine-readable format that other software and tools can understand and use. This eliminates the need to manually transcribe those documents and typically an IDP solution is linked via APIs to additional automation solutions.
Accurate data is the basis of every organization, and IDP helps organizations cope with the difficulty of processing large numbers of documents by automating human data entry procedures and transitioning away from old semi-automated OCR (Optical Character recognition) workflows.
Businesses use this technology to digitally connect different parts of their operations (both people and systems) minimize human labor, handle difficulties with reading diverse complicated document formats, and fulfill legal and regulatory requirements. In this article, we'll learn the nitty-gritty of Intelligent Document Processing and how incorporating an IDP solution can help streamline your business.
Why intelligent document processing?
Intelligent document processing (IDP) offers game-changing methods for automating data extraction tasks that were previously exceedingly difficult, if not impossible, to complete. It is also important to know that IDP is so much more than just scanning an invoice. Nowadays, a key advantage of IDP is the use of trained APIs and modules for some of the most popular document types, like bank statements, agreement forms, invoices, IRS forms, driver's licenses, and so on. That implies you won't have to spend a lot of time training the model from scratch, IDP really allows you to hit the ground running.
The various IDP tools, their APIs and modules also indicate missing values, fields, and duplicate data entries, reducing data redundancy, manual processes, and error rates. Once the IDP solution have extracted reliable data, users just need to evaluate and approve the platform's final updates. Users can later upload documents in bulk and process them for future use.
Unsurprisingly, IDP is therefore also on the forefront of integrating with artificial intelligence (AI) and machine learning (ML). In fact it is a great match as you are feeding it more and more data that is then also manually checked and verified. This means that your specific implementation can get smarter and more accurate over time resulting in even more savings.
What are the key components of intelligent document processing?
There are a number of underlying technologies to IDP that make the magic happen and save organizations all that time as well as minimizing errors. Not all solutions include all of these technologies and they do vary in sophistication.
Image processing
The first step is to process the image of the document that has been received (e.g. via scan or email). Computer vision algorithms enable image processing, preparing a document for both optimum OCR/ICR and preservation. The IDP platform will typically generate two versions of digitized documents: one for machine-reading and one for on-screen viewing in a content management system.
Optical character recognition (OCR)
OCR is the technology that translates scanned images of text, whether printed or typewritten, and turns these scans into machine-encoded text. That machine encoded text is then what other software and solutions can understand and use, e.g. a Robotic Process Automation (RPA) or invoicing software.
An finely tuned OCR with very few errors is vital for machines to read text found in documents (images). The usage of different OCR engines is one of the defining features of IDP. More sophisticated solutions apply a multilayered method that combines the output of multiple machines until near-perfect accuracy is obtained.
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Intelligent character recognition (ICR)
Intelligent character recognition is a more advanced type of OCR technology that is growing in popularity. The main difference is that ICR also understands styles of hand writing and various fonts. ICR is evolving as technology advances to provide greater accuracy and recognition rates.
Natural language processing (NLP)
The key aspect of NLP is to understand and process context. This can be context in the sense of tagging certain data (e.g. entities, names, features), understanding synonyms (e.g. if the word bass refers to the fish or the sound frequency) but also industry or language specific terms and acronyms. In your documents NLP searches for paragraphs, words, or other language components that communicate special meaning. Using techniques such as sentiment analysis, deep learning, part-of-speech tagging, named entity tagging, and feature-based tagging, NLP accelerates data discovery.
What are the benefits of Intelligent Document Processing?
According to a Gartner press release, implementing intelligent document processing systems may save finance departments alone 25,000 hours of rework caused by human error at $878,000 per year for a company with 40 full-time accounting personnel. Apart from hard productivity and/or financial gains Intelligent document processing is also gaining popularity because it offers ways to automate data extraction activities that were previously difficult, if not impossible, to do. IDP can also transform the way we work as these new sources of digital data will create better business outcomes and should also stimulate more innovation.
Speed & accuracy
This is typically top of mind for most people implementing IDP and the numbers speak for themselves. An AI-native IDP solution can accelerate data extraction by up to ten times while keeping data extraction accuracy of up to 99.9 % for various document formats.
Improved productivity
Built-in IDP solutions require little or no human intervention due to faster processing times and straight-through processing. IDP eliminates the need for your employees to get involved in data extraction from semi-structured or unstructured documents and manually input that data. This results in increased productivity.
Digitital transformation
Often overlooked but a truly great benefit of IDP solutions is that they enable digital transformation for your business by ensuring paperless document processing and data exchange across systems, part of your business and even with third parties.
Cost efficiency
As manual data entry is no longer needed you also remove human errors and subsequent more manual review. Apart from improving productivity of people (and their happiness) it is not uncommon to see cost savings of up to 70%.
Scalable automation
As IDP solutions are digital it also makes it easy to integrate with your existing system(s), and when combined with other automation solutions (such as RPA) you can really start to scale your automation efforts and reap even greater benefits.
How is Intelligent document processing used?
The main use case of IDP is to target very administratively and document heavy processes and typically ones that include high levels of standardisation. And although perhaps not top of mind for most people, IDP enables tremendous savings across a vast number of tremendously important processes across enterprises and governmental functions. IDP is the next-generation data extraction technology that is used to overcome the limitations of traditional OCR in extracting data from more complex and non-standard documents and therefore allows for vast adoption and as mentioned IDP integrates seamlessly with various automated workflows and business processes. Among other things, Intelligent document processing can help businesses with:
• Bank statements and invoices processing
• Data extraction from income/identity verification documents
• Automated data extraction for financial forms (e.g. IRS)
• Lease agreements
• Sales and offering memorandums
• Processing bill of lading/shipping labels
• Receipts and corporate expenses processing
• Automated document classification.
Success stories of intelligent document processing
Banking and insurance
For a typical bank, most of the products and services provided by them relied on physical data (e.g. printed and signed forms). And their reputation is heavily influenced by how quickly and easily their financial services are made available to clients, i.e. how quickly they can process and the physical data. Intelligent Document Processing shortens the time it takes to collect relevant data such as insurance claims and loan applications, and therefore provide assistance faster. It enables bank employees to concentrate on providing tailored client experiences while IDP handled data collection, categorization, and extraction. Because of the enhanced customer experience, there is typically also an increase in prospective consumers.
Healthcare
Healthcare organizations often needed to maintain records of several thousands of patients and have them easily accessible to provide various services. While most hospitals still maintain paper records that are corruptible and can be misplaced, data digitization and Intelligent Document Processing solution helps hospitals and healthcare providers to easily manage a patient’s medical record and history, and store it in one place without the risk of any damage. IDP also enables a reduction in time and costs involved in manually checking patient records, thereby using vital resources to provide medical attention to patients. Hence, IDP can also assist healthcare and medical organizations to optimize patient assistance and decision-making.
Legal
Law firms face multiple challenges every day with respect to large volumes of data in the form of archiving documents, auditing documents, maintaining mergers, creating acquisition documents, filing property documents, and following compliance regulations. This list is not exhaustive, and each process involvs preparing, collecting, or maintaining multiple complex documents in each stage. Apart from that, lawyers need to go through multiple documents while working on each case. These tasks are usually handled by an associate, and apart from costing valuable time this process often lacks accuracy and is prone to discrepancies that cost valuable time, resources, and even clients. Onboarding IDP helps law firms to manage data and documentation accurately and securely given their importance and sensitive nature. Intelligent document processing will improve the quality of legal services and further help with client satisfaction and should also result in significant cost savings.
What to expect from intelligent document processing
The following steps are typically included in an intelligent document processing platform and this is typically what would happen if you implement an IDP solution. The aim is to turn paper or digital documents into accurately labeled data. Not all implementations require all steps but this will give you a good overview of what you can expect to gain but also what you may need to do and/or change in order to ensure your IDP implementation is sucessful
Classification
Most business documents are collections of pages that include multiple sorts of information. Machine learning and other intelligence-based approaches are used to teach IDP classification engines to identify documents. Automatic document recognition is a critical step in interpreting the data contained inside a document.
Extraction
The artificial interpretation of data by computers is critical to successful data extraction. Because Artificial Intelligence is only as intelligent as its training, the system must be able to locate and classify all extracted information inside a document. This involves segmenting natural language texts and extracting certain data items such as dates, names, numbers, and so on.
Data validation
It is imperative to verify all extracted data before it can be trusted. Intelligent document processing platforms are distinct such that they assess data using external databases and pre-configured lexicons. Any information that does not match is reported for human inspection and correction.
Integration
The needs for data integration are quite different. IDP systems must interface with all downstream applications since they are key sources in the data supply chain. This covers cloud and on-premises databases, as well as document repositories. For portability, labeled data and metadata are linked to human-readable versions of the data.
Wondering how to get started with intelligent document processing? Book a consultation with Turbotic and get a customized data solution for your business.
