Timely, accurate data is the foundation for every modern business and central to digital transformation efforts. But extracting data from a variety of sources, including complex documents, can be a time-consuming and complicated process.
Legacy data processing automation tools, such as optical character recognition (OCR), which have been used for years to capture information from structured text files, has significant limitations when processing unstructured or semi-structured files, as well as physical documents.
In this post, we review how intelligent document processing (IDP) enables organizations to capture, analyze and harness the power of their data in a faster, more cost-effective and seamless way.
Intelligent document processing definition
Intelligent document processing is a form of intelligent automation that leverages advanced technology to extract semi-structured or unstructured data from documents, emails, PDFs, images and other files and convert it into structured, usable data.
Intelligent document processing enables enterprises to eliminate manual data processing tasks, which greatly improves processing times, reduces costs and eliminates errors.
The technology behind intelligent data processing:
- Artificial intelligence (AI)
- Machine learning (ML)
- Optical character recognition (OCR)
- Intelligent character recognition (ICR)
- Computer vision
- Natural language processing (NLP)
- Deep learning
IDP vs RPA vs OCR
Terms like IDP, robotic process automation (RPA) and OCR are sometimes used interchangeably to describe automated data processing. However, each of these tools has distinct capabilities and use cases. While IDP, RPA and OCR solutions are related and often used together, they are neither interchangeable nor wholly replaceable.
IDP and robotic process automation
RPA is a type of intelligent automation that uses machines or robots to perform simple and repetitive tasks with limited human intervention or supervision. While the RPA solution relies on data from other business applications to complete processes, the software typically does not support data capture or analysis. Instead, it relies on an IDP solution or similar technology to process data and apply insights within the RPA workflow.
IDP vs. OCR
Optical character recognition (OCR) is a core technology that extracts text from structured documents and creates a new text file. While helpful, this tool has limitations, especially in the modern business landscape, where data is contained within complex, unstructured documents.
IDP differs from OCR in that it can:
- Identify and extract data from unstructured sources, such as articles, images, charts, emails, PDF files, contracts, forms and other files
- Automatically integrate the extracted data into existing workflows, such as RPA
- Add context to data and leverage intelligent automation tools (such as AI and ML) to make decisions about how the data can be usedIDP Checklist
Here’s a list of questions you should ask when evaluating an IDP solution …
- Does the solution process unstructured and semi-structured data?
- Can the tool perform automated data recognition, extraction and classification?
- Does the tool leverage AI, ML, and other advanced technology to improve analysis capabilities?
- Does the tool leverage NLP to provide context for data?
- Can the system integrate with other intelligent automation solutions or software?
How IDP works
There are a number of steps that enable IDP to work. We’ll dive into them below.
All files, documents and other content is uploaded to the IDP platform for processing. For physical documents, files must be scanned and converted into an electronic format first.
The IDP tool leverages OCR, NLP, computer vision, AI/ML algorithms, and other intelligence-based techniques to recognize document characters within document elements and unstructured copy.
The IDP tool extracts relevant data from the document set. The solution leverages predefined rules and models to properly categorize the extracted data, such as dates, names, numbers, and other relevant information.
- Data Validation
All data extracted by the IDP tool must be validated. This is done by cross-referencing data with external sources and models within the tool. Data that cannot be verified via automated means is flagged for manual processing by humans.
The real value of IDP solutions comes through integration with other business applications. The IDP tool can be used to support downstream activity, such as processing claims, registering customers, creating documents, invoicing or compliance.
IDP use cases
IDP systems are used in many different industries, including financial services, insurance, logistics, legal, and healthcare. Common use cases include:
- Document conversion: IDP software can be used to convert physical documents and paper files into searchable digital formats.
- Document creation: Intelligent capture solutions can combine data from different sources to produce a single report or file.
- Workflow enablement: Data extracted from IDP solutions can be used to inform automated workflows, such as claims management, loan processing, compliance reporting, customer registration and more.
- Data processing and storage: The IDP solution can classify and store data in a way that is easily searched to support other business processes or enable future use cases.
IDP Industry applications
There are many industry applications for IDP.
- Process customer applications for loans, lines of credit or new accounts
- Support the calculation of credit risk scores
- Validate customer data, including personal information, income, credit scores, assets and more
- Process and analyze huge volumes of data
- Calculate risk for specific customers or customer segments
- Calculate insurance premiums and other contract terms
Supply chain and logistics
- Process all documentation across the entire supply ecosystem, including orders, invoices, payment receipts, contracts, customer profiles, manifests, and more
- Streamline and optimize logistics throughout the supply chain, including transportation between partners, delivery to customers, warehousing, and shipping
Legal and compliance
- Compile data from different sources to create contracts, reports, or other legal documents
- Archive records and other documents for simple search and retrieval, as well as compliance
- Automate patient registration, billing, claims processing, health records management and other routine and recurring tasks within the patient lifecycle
Intelligent document processing benefits
By eliminating manual processes, IDP offers businesses a host of important benefits, including:
- Faster processing time: Automation greatly reduces the time it takes to recognize, extract, analyze and organize data
- Improved accuracy: Leading IDP solutions offer near full-proof processing accuracy
- Resource optimization: Most IDP tools complete routine and recurring tasks with limited or no human intervention, which frees up staff to focus on higher-value activity
- Cost savings: IDP greatly reduces time spent by knowledge workers to extract, analyze and verify large amounts of data
- Improved customer experience: Faster, more accurate processing tends to increase customer satisfaction and loyalty
Inscribe and intelligent document automation
Inscribe’s intelligent documentation automation makes it easy to process customer applications and extract key fields from documents including bank statements, transactions, and payslips.
We work with clients to help reduce manual processes and integrate our easy-to-use API to automate document checks, streamline account opening or underwriting processes, and enhance compliance.
Key features include:
- Easy-to-use API
- Trust score
- Quality score
- Decision engine
To learn how Inscribe can help your organization can improve your customer experience with a 10X reduction in application review times through intelligent document processing, contact our sales team to set up a demo today.