In today's data-driven world, businesses are drowning in documents. From invoices and contracts to insurance claims and loan applications, the sheer volume of paperwork can be overwhelming. This is where Intelligent Document Processing (IDP) comes in.
IDP is a powerful technology that uses artificial intelligence (AI) and machine learning (ML) to automate the extraction of data from various documents.
A study by Express Computer estimated that unstructured data accounts for approximately 80% of the data generated and stored by organisations globally, highlighting the massive potential of IDP to unlock valuable information.
By automating document processing, IDP can significantly improve efficiency, reduce document processing costs, and free up employees to focus on more strategic tasks. Today, we’ll take a closer look at the different types of IDP solutions, learn how to choose the right IDP solutions, and discover the latest technologies in IDP.
What Are Types Of Intelligent Document Processing Solutions
Pre-built solutions
These solutions are designed for specific document types, such as invoices or insurance claims. They are typically easy to implement and use, but they may not be as flexible as custom solutions.
Custom solutions
These solutions are tailored to meet the specific needs of your business. They can be more expensive and time-consuming to implement, but they offer greater flexibility and scalability.
Factors to Consider when Choosing the Right IDP solution
According to Data Semantics, IDP can reduce operating costs by up to 30% YOY. But with so many IDP solutions on the market, how do you choose the right one for your business? Here are some key factors to consider:
How Advanced Tech Helps Current IDP Limitations
The good news is that the field of IDP is constantly evolving. The newest innovations in intelligent document processing are helping to address some challenges. Here's a table comparing current IDP limitations and how the advanced tech can help:
|
Current IDP Limitations |
Advanced Tech |
Benefit |
|---|---|---|
|
Difficulty handling complex document layouts and variations |
Natural Language Processing (NLP) |
Improved accuracy, especially with documents that have unusual formatting or layouts. |
|
Limited ability to continuously learn and improve |
Deep Learning |
System gets smarter over time and requires less upfront training on new document types. |
|
Inability to accurately process handwritten documents |
Enhanced Handwriting Recognition |
Enables processing of applications, forms, and other handwritten documents with greater accuracy. |
|
Limited multilingual capabilities, especially for complex documents |
Advanced NLP techniques |
Improved understanding of context in documents from multiple languages. |
|
Data Integration Challenges: Integrating extracted data from IDP solutions with existing enterprise systems can be complex. |
API Integration Improvements & Pre-built Connectors |
Advancements in APIs and pre-built connectors will streamline data integration, making it easier to connect IDP with various business systems. |
|
Limited Explainability: In some cases, IDP solutions can struggle to explain why they made a specific data extraction decision. |
Explainable AI (XAI) |
XAI techniques will help IDP solutions provide explanations for their decisions, improving user trust and understanding of the data extraction process. |
|
Security Concerns: Since IDP solutions often handle sensitive data, security is a major concern. |
Enhanced Security Features |
Newer IDP solutions will prioritise robust security features like encryption, access controls, and regular security audits to safeguard sensitive data. |
Current IDP status and the future
In 2024, IDP is a well-established technology offering significant benefits. It automates data extraction, slashing costs and errors. However, especially when it comes to complexity & large-scale document digitisation, the current solutions can struggle with the high volume.
The future of IDP is exciting. Advancements in AI, like NLP and Deep Learning, will empower IDP to handle intricate documents, continuously learn, and even process handwritten text.
By embracing IDP and its upcoming potential, businesses can unlock a future of efficient document processing and transform their data into valuable insights.
CBSL's Intelligent Document Processing Solutions
CBSL’s Intelligent Document Processing Solutions are powered by advanced AI and machine learning technologies, including the latest advancements like NLP, Deep Learning, and Active Learning.
Our solutions can automate the processing of various document types, including insurance claims, loan applications, credit card claims, marriage tax claims, and legal documents, improving efficiency and accuracy in these critical areas.
By leveraging IDP, CBSL can help businesses streamline their document processing workflows, reduce costs, and improve customer satisfaction. Check out our website today to learn more about how our Intelligent Data Processing Solutions can help your business.
Our other services include Information data management, business data automation, software solutions, solar solutions, and security printing solutions.
'
Frequently Asked Questions
1. Why Do We Need Intelligent Document Processing (Idp)?
Intelligent document processing (IDP) is necessary because it allows organisations to automate the extraction, understanding, and processing of information from various types of documents.
This technology helps streamline business processes, improve efficiency, reduce errors, and enhance decision-making by turning unstructured data into actionable insights.
2. What Are Idp Examples?
Examples of IDP include:
-
Invoice processing: Automatically extracting relevant data from invoices such as vendor details, invoice numbers, dates, and amounts.
-
Contract management: Identifying key clauses, dates, and obligations within contracts to facilitate review and compliance.
-
Form processing: Extracting information from various types of forms, such as applications, surveys, and insurance claims.
-
Receipt processing: Automatically capturing data from receipts for expense reporting and accounting purposes.
3. What Are The Responsibilities Of Idp?
The responsibilities of IDP typically include:
-
Document ingestion: Accepting documents in various formats such as scanned images, PDFs, emails, and digital forms.
-
Data extraction: Automatically extracting relevant data fields from documents using techniques such as optical character recognition (OCR), natural language processing (NLP), and machine learning.
-
Validation and verification: Ensuring the accuracy and completeness of extracted data through validation checks and human-in-the-loop mechanisms.
-
Integration: Seamlessly integrating with other systems and applications such as enterprise resource planning (ERP) software, customer relationship management (CRM) systems, and robotic process automation (RPA) platforms.
-
Reporting and analytics: Providing insights and analytics on processed documents to support decision-making and process optimization.
4. Which Format Is Acceptable For Intelligent Document Automation Uploads?
Intelligent document automation platforms typically accept a variety of formats including:
-
PDF
-
Word documents (DOCX)
-
Images (JPEG, PNG, TIFF)
-
Emails (including attachments)
-
Spreadsheets (XLSX)
-
Text files (TXT)
-
Web forms (HTML)
These platforms often have built-in capabilities to handle different file formats and extract information from them efficiently.