Manual document processing creates friction in your business. It's a bottleneck prone to human error and a source of tedious work for your teams. Intelligent Document Processing (IDP) transforms this challenge into an opportunity for document automation. By leveraging powerful AI, IDP automatically classifies documents and extracts critical data with high accuracy, eliminating manual data entry. This is the first step to true end-to-end process automation, turning unstructured content into actionable data that accelerates your operations.
What is IDP?
Intelligent document processing is an automation technology that blends optical character recognition (OCR), robotic process automation (RPA), and artificial intelligence (AI). It helps computers decipher unstructured documents, letting you access valuable data hidden in paper forms and siloed databases. It addresses common challenges like:
- Delayed operations due to errors.
- Missing data for decision-making.
- High operational costs due to manual extraction.
- Lack of compliance with regulations due to inaccurate or incomplete data.
Intelligent Document Processing (IDP) differs from and builds upon traditional automation. Traditional automation often relies on Optical Character Recognition (OCR). It primarily focuses on recognizing and converting printed or handwritten text that's in a structured data format into digital form.
While IDP uses OCR, it goes further by incorporating Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) to understand the context and meaning of the information within documents, not just extract the text. IDP adds intelligence and understanding, transforming how businesses handle and leverage information from their documents.
Technologies used in IDP
Artificial intelligence: Used to simulate human intelligence in machines that are programmed to think and learn as they perform tasks that usually need human cognition.
Machine learning: The most common type of AI in use, machine learning systems are trained on large volumes of data so they can learn and identify patterns and make decisions based on the data.
Natural language processing: What AI uses to understand, interpret, and generate human language. It's used in chatbots, virtual assistants, and language translation tools.
Robotic process automation: The use of software robots to automate repetitive, rule-based tasks that usually need human interaction with systems that don't have APIs.
Optical character recognition: Technology that converts images of handwritten, typed, or printed text into data that's machine-readable.
Why should you use IDP?
You can use IDP software to make processing documents of all kinds faster, easier, more accurate, and less expensive. Let’s talk a little more about each of those benefits of IDP.
Process documents faster.
Manual data extraction is tedious. With IDP, documents are swiftly scanned, interpreted, and categorized, allowing for rapid processing. Say goodbye to the sluggish pace of traditional methods.
Increase accuracy.
Manual data extraction is tedious. With IDP, documents are swiftly scanned, interpreted, and categorized, allowing for rapid processing. Say goodbye to the sluggish pace of traditional methods.
Lower costs.
By automating repetitive tasks and minimizing manual data entry, IDP slashes operational costs. The efficiency gains translate into tangible savings, making it a strategic investment for forward-thinking organizations.
How Appian Customers Are Using Intelligent Document Processing
A financial asset management firm had to gather invoices from 22 vendors who billed on varied weekly and monthly schedules. This required an employee to visit each vendor’s website on the day their invoice would be posted, download the invoice, manually enter information into an app, and then wait for further processing. They turned to Appian to automate this process. They leveraged Appian’s platform approach, using RPA in tandem with IDP and AI, to build and deploy a broad invoice processing application that:
Uses a bot to access each vendor’s website to download the invoices.
Uses AI and IDP to extract data from the invoices.
The firm reported to Appian that this combination allowed them to automatically process 100% of invoices from all 22 vendors in the application.
What are the use cases for IDP?
Intelligent document processing can be used in any industry for almost any use case involving document processing.
Insurance
Use case: Claims processing
In the insurance sector, IDP becomes the unsung hero of claims processing. Rapid extraction and validation of data from claim forms, receipts, legal documents, and medical reports translate into faster claims approval and a streamlined reimbursement process.
Government
Use case: Procurement
Governments grapple with massive documentation in procurement processes. IDP comes to the rescue by automating the extraction and organization of key information. This reduces manual workload and enhances procurement efficiency.
Financial Services
Use case: Loan applications
Loan application processing is a document heavy process. When those processes are manual and slow or there are delays due to errors, it means poor customer service experiences. IDP and generative AI can automate loan application processing to improve speed and enhance accuracy.
Cross-Industry
Use case: Large-scale process automation
IDP is not just a standalone solution. It's a crucial component in large-scale process automation efforts. Meaning while you can use it for automating individual tasks, it is better used as part of an enterprise process automation effort. IDP seamlessly integrates into end-to-end automation initiatives, making it an indispensable tool for enterprises aiming to automate their diverse business processes like:
customer onboarding
employee onboarding
purchase orders
contract management
vendor management
Take a platform approach to IDP.
It’s true that there are plenty of standalone intelligent document processing solutions on the market. But I hate to say it, if you’re thinking of IDP as a single, separate automation undertaking, you’re probably doing it wrong. It’s a smarter strategy to invest in a holistic AI process platform with IDP as just one capability. This integrated approach, which includes RPA, AI, and data fabric technologies, paves the way for organization-wide, large-scale process automation.
AI, in particular, is a critical capability to combine with IDP. That’s why the Appian Platform includes AI Skills, a design object that lets you classify and extract data from documents entirely automatically. Watch the video below to see how AI Skills allows teams to apply artificial intelligence to critical use cases, including document classification, email classification, and document extraction.
Why consider a platform approach?
Seamless integration: IDP becomes part of a cohesive automation ecosystem.
Comprehensive capabilities: Address not just document processing but broader business automation needs.
Future-proofing: Position your organization for the future by adopting a scalable and adaptable platform.
IDP delivers significant gains in speed and accuracy. It also fuels wider automation efforts. With IDP, organizations can finally eliminate the burdens of manual document processing and make tedious work a distant memory.
