What is Intelligent Document Processing?
This article will give an in-depth explanation of Intelligent Document processing.
Data has become the cornerstone for most businesses. It can give meaningful insights, generate leads/sales, help a company grow… But this abundance of data must be captured and interpreted. The first problem is the capturing of data from documents. Most companies are not able to effectively extract data from unstructured documents and therefore they do not use data to improve their business. The next problem is when companies do collect data, but they do not know how to extract and interpret this data. These companies waste too much time on manually extracting unstructured data, without getting the insights they desire.
Around 80% of total enterprise data is unstructured and can't be analyzed as is.
Types of data a company encounters
Structured data
Semi-structured data
Unstructured data
The problem with all this data is that around 80% of total enterprise data is unstructured and can’t be analysed as is. Processing this unstructured data is time-consuming and demotivating for employees. How can organisations transform this data to valuable, structured data without overburdening their employees?
Intelligent Document Processing (or IDP) might be the answer.
What exactly is Intelligent Document Processing?
Intelligent Document Processing or IDP, is a technology based on AI and machine learning that allows organisations to automate the data extraction from complex, unstructured documents and convert it into usable data. IDP utilises different technologies to extract, interpret, categorize, relevant data. Before it can be implemented, an IDP system must be trained on a number of different example documents. Afterwards, the system automatically extracts the relevant data. After training, when the system is not sure if the data is correct, it will demand human validation to continually improve the algorithm. The different sub-technologies used within IPD are Artificial Intelligence (AI), Machine Learning (ML), Optical Character Recognition (OCR), Computer Vision, Robotic Process Automation (RPA), and Intelligent Character Recognition (ICR ). IDP can be a huge time saver for businesses that still manually extract data from documents.
Because all these technologies work seamlessly together, an IDP system can learn from itself. This means that organisations can automate data extraction from complex and varying document types and emails.
What is the difference between Intelligent Document Processing and Optimal Character Recognition?
IDP is different from OCR (Optimal Character Recognition). IDP does use OCR technology, but it is larger than just that. It also incorporates so much more technologies that help the IDP system to make well-thought-out decisions. Curious to know more about OCR vs IDP? Read our blog article.
What is the difference between Intelligent Document Processing and Robotic Process Automation?
IDP is also different from robotic process automation. RPA is a separate, single task that runs on a data-driven and trained model. But this model can only do this one repetitive task that it is trained on. RPA does not have the ability to understand and interpret the data like an IDP system. Want to know more details about how these technologies differ and how they can work together? Read our blog article.
Benefits of Intelligent Document Processing
Save time and process documents faster
Improved accuracy
Improved productivity
Process any document
Cost efficient
Success stories in Intelligent Document Processing
Get inspired by these use cases within different industries.
Automating loan applications in banking
Discover how Axa bank manages to process the same amount of loan application documents with less than 50% of the time and effort. Read case here.
Insurer automates incoming communications
The automation of incoming communications at Europ Assistance is being automated using Metamaze. Lean more about it in the case study. Read case here.
Automation of incoming orders
Discover how Group Nivelles saves 70 hours per month and automates 90% of incoming orders. Read case here.