In the last few years, Intelligent Document Processing (IDP) has seen rapid growth in adoption rate as organizations deal with high volumes of complex documents. This software enables organizations of all sizes to remove costly and inefficient manual processes, improve data accuracy, and use their existing employees more effectively.
According to Gartner, the IDP market is growing more than 100% year over year, and is projected to reach $4.8 billion in 2022, proving that businesses are rapidly adopting the technology as the necessity for automating complex use cases continues to grow.
And there are no signs of this growth slowing down. Times of economic uncertainty create higher demand for this type of technology. It’s in these times that public and private organizations look to increase efficiencies and cut costs by targeting inefficient, manual processes.
What Is Intelligent Document Processing?
Intelligent Document Processing helps transform structured (forms), semistructured (checks, paystubs, invoices, etc…) and unstructured data (deeds, medical records, emails, contracts, etc…) from a variety of document formats into digitized and actionable information. It uses a combination of technologies, such as optical character recognition (OCR), natural language processing (NLP), computer vision, machine learning (ML) and artificial intelligence (AI), to scan, classify, identify, and extract data.
IDP solutions can understand a wide variety of document formats and the content it contains; extracting, validating, and integrating quality data into appropriate business processes and downstream systems.
Additionally, IDP overcomes the limitations of simple template-based document capture tools and streamlines the document processing activities using human-in-the-loop (HITL) capabilities to handle exceptions and to train and improve its capabilities over time.
Document processing relies on multiple different technologies to operate:
Computer Vision is a technology which is able to derive meaningful information and understanding from videos and digital images, and take actions based on that information
Machine Learning is a branch of artificial intelligence based on the idea that systems can learn from data and uses computer algorithms to identify patterns and make decisions with minimal human intervention
Deep Learning is a machine learning technique that imitates the way humans gain certain types of knowledge—it learns by example. In deep learning, models are trained by using a large set of labeled data and neural network architectures that contain many layers, achieving very high levels of accuracy
OCR is a type of software that converts images of text into machine-readable forms.
How Does IDP Work???
IDP solutions use machine learning to extract data from documents to support automation efforts. IDP generally consists of the following five steps.
- Ingestion & Preprocessing
Data is captured from several content types and prepared for processing. This preparation includes merging/splitting documents, data validation, and corrections to low quality renders. Some solutions also provide tools for data labeling and annotation, often done by a human-in-the-loop (HITL). - Classification
Documents are then classified into different categories. This process can be manual or automatic, with advanced solutions offering suggestions for categories based on existing taxonomies. At this stage, humans are typically involved in category creation and definition, as well as data validation. - Extraction
Machine learning extracts data from various content types and supports the handling of diverse formats. Some solutions require less training data than others for the ML model to quickly and accurately extract data. During this step, humans train the machine learning model to identify fields for extraction. - Validation and Feedback
Extracted data is then validated against internal/external data. Human input is used to deal with outliers, preprocessing, classification, extraction quality improvement, and additional ML model training. - Integration
Validated data is sent to downstream applications for use. Common IDP integrations include customer service platforms, data enrichment tools, and RPA solutions. Ultimately, this is where the data lands for decision making and business process improvement.
Industries That IDP Can Be Applied To
Many industries stand to benefit from the use of intelligent document processing. Many large industries already have this type of software in place to accelerate critical processes and serve customers more efficiently.
Intelligent Document Processing in Banking
Banks are inundated with documentation. From credit card applications, new account opening requests, and changes to personal details, many tasks take up a large amount of employee time when done manually.
Introducing Intelligent Document Processing to the Banking industry can help better leverage internal bank data and streamline the process of acquiring necessary customer information, allowing lenders to review applications faster.
Intelligent Document Processing in Financial Services
Huge volumes of complex and sensitive data make the finance industry an ideal candidate for IDP. It is a perfect solution for automating increasingly complex financial services processes such as mortgage processing, account opening, or account servicing.
To stay competitive, financial institutions need to streamline document-heavy processes without compromising on accuracy or customer service. IDP can help speed up document processing, improve the accuracy and timeliness of decisions, and free up resources to focus on delivering frictionless customer experiences that the competition can’t match.
Intelligent Document Processing in the Public Sector
Every day, public sector organizations must efficiently process millions of forms, applications and images to meet the needs of citizen-centric workflows such as benefits claims or tax returns. These documents come in a wide variety of formats, often with poor readability and high variability, making it very difficult to reliably and efficiently process and extract data for downstream usage.
These outdated, manual workflows and legacy approaches contribute to a massive data backlog and lead to an information bottleneck that results in strained systems, overworked employees, and frustrated citizens due to delays.
Using IDP, government agencies can unlock the potential hidden in their huge volumes of data, gain efficiencies, improve constituent and employee satisfaction, and drive better agency outcomes.
Intelligent Document Processing in the Medical Industry
The medical industry stands to gain significant efficiency improvements through the use of Intelligent Document Processing.
Not only does IDP assist in quickly and efficiently accessing detailed patient notes, managing prescriptions, scheduling appointments, and updating medical records, it also allows the organization to digitize the way that it supports employees.
Many medical organizations have opted to use IDP to ensure that employees’ registration documents, identification documents, and other HR-based requirements are processed quickly and without error. Decreasing the time it takes to manually complete these admin-heavy tasks saves organizations a great deal of time—an absolute necessity when dealing a matter of minutes can mean the difference between life and death.
Intelligent Document Processing in Transportation and Logistics
The sheer volume of shipped goods and their accompanying documents make the logistics sector an industry ripe for IDP. Incorrect information at any stop can delay shipments and have dire consequences for your freight and your customers.
To stay on top of demand and increase resilience to market changes, the transportation and logistics sector can benefit from implementing IDP to automate document-heavy processes to remove friction in their operations without compromising on accuracy or customer service.
Benefits Of IDP
For organizations seeking the long-term value of automating labor-intensive administrative tasks, here are some of the benefits of using IDP.
- Improves Efficiency
IDP solutions require minimal human intervention, allowing existing employees to work more efficiently. This leads to faster response times, better customer service, and even increased revenue - Reduces Costs
By automating the manual effort needed for document processing, IDP minimizes repetitive, low-value tasks and reduces the associated overhead costs. These savings are felt most keenly the business grows or when there are seasonal surges in volumes that historically require hiring temporary staff. - Minimizes Mistakes
It’s an unfortunate reality that as the speed of work increases, so does human error. For employees who may already be at full capacity, pushing for even more productivity can take them to their breaking point, leading to potentially disastrous effects on customer satisfaction. Introducing the use of an IDP platform helps organizations to minimize the risk associated with poor data entry, while increasing the speed at which tasks can be carried out. - Increases Data Security and Control
Sometimes, customer or employee data is lost or misplaced, leaving businesses vulnerable up to the consequences of a data leak. Using Intelligent Document Processing allows a business to capture and process paper files and create an accurate digital version so that the physical copy can be disposed of in the correct manner.
How Hyperscience Can Support Your Business With IDP
Hyperscience provides the most advanced and accurate intelligent document processing software powered by machine learning.
Hyperscience achieves the highest levels of accuracy in the industry using proprietary ML models to extract printed and handwritten text from complex documents, whether they are structured or unstructured. But the platform capabilities go well beyond extraction, helping companies act on that data through workflows to do things like discover, validate, and enrich that data—ensuring that the data that flows into downstream systems enables better decisions.
Our intuitive platform is easy to use and deploy, and is designed to handle real-world conditions—delivering high levels of automation and accuracy in real-life scenarios.
Trained on real-world documents with real-world imperfections, and equipped with pre-trained machine learning models, our intelligent document processing solution can meet your target levels of accuracy and handling times, while involving humans only when necessary. No matter the coffee stains, scan lines, or messy handwriting, Hyperscience turns documents into the structured data you need to serve your customers.
