Intelligent Document Processing (IDP)

Intelligent Document Processing (IDP): Impact for Business in 2021

Organisations often have to handle data from semi-structured and unstructured documents which makes it difficult for work processes to achieve greater level of automation. Given limited human resources, handling documents such as job-application forms, invoices, packing lists, export declarations, and other business documents can be a burden. Manual “eye-balling” of data can be very tedious and prone to human errors. Organisations are beginning to discover the use of Intelligent Document Processing (IDP) to free up staff needed to manage a variety of types of documents. 

What Is Intelligent Document Processing (IDP)?

The term Intelligent Document Processing (IDP) is increasingly used by software vendors to describe the steps involved in getting data from documents using Artificial Intelligence (AI). It is the process of translating the contents of a document, whether physical or electronic, into something that is meaningful for machine (computer) to handle. The process turns the incoming data into something “structured” so that automated software such as RPA (robotic process automation) can take over and continue with automated entry into various systems.

Intelligent Document Processing (IDP) is more than just OCR (Optical Character Recognition). OCR is only a part of the jigsaw puzzle that tries to turn images into machine-readable characters, without discerning what those characters mean. IDP leverages on various aspects of A.I. such as natural language processing (NLP) and machine learning to help with classifying data and grouping the same categories of data points together.  

IDP is like the bridge between the real-life humans’ world of data and automated tools such as Robotic Process Automation which are good with digital structured data (e.g. those in spreadsheets and databases). To put simply, IDP is to convert PDF documents into Excel files or CSV files with data that can be processed by RPA or be imported into existing IT systems.

Impact of Intelligent Document Processing for Business

All types of companies can potentially benefit from IDP. From our experience, we have noted that banking, financial services and insurance (BFSI) and logistics industries make up the majority of users of IDP.  We have helped our customers process documents including trade-related documents (e.g. bills of lading, airway bills, letters of credit), proof of identity or residential address (e.g. passports, identity cards, phone bills), finance documents (e.g. invoices, quotations, bank statements), certificates (e.g. degree certificates, sea-farer certificates), inventory-related documents (e.g. packing lists, delivery notes), and others. 

Intelligent Document Processing (IDP) removes the need for people to process huge amounts of paperwork manually. Converting incoming data from PDFs (both scanned or native PDF documents) into Excel / CSV files make workflows a lot easier for subsequent automation. Products like Gleematic has built in IDP and RPA together, which is a good combination to empower an almost end-to-end automation. This in turn helps to avoid human error, reduce document processing time and reduce operating costs. It is also flexible as the A.I. can learn about new documents or changes in format and react accordingly to capture the new types of data it comes across. 

IDP can enable employees to work remotely together in the creation, editing and processing of documents. Intelligent Document Processing (IDP) promises to make automated processes involving documents, emails and other unstructured data much easier and faster than is required to automate workflows.

Imagine getting work done three to five times faster with the combination of IDP and RPA together.

How Intelligent Document Processing Works

The extraction step is carried out via OCR, which recognizes printed characters and converts them into machine-readable digital data formats. Once the data is extracted, they go through a series of AI-based techniques to improve the extraction results.

Once the information is collected, business applications can take steps to initiate data processing, such as creating new business processes and managing the data. If you are considering introducing an IDP solution to improve your business process and want to explore its full capabilities, take a look at the case study video below about “Extracting Data From Scanned Receipts with OCR”.

How to Implement Intelligent Document Processing (IDP) in your organisation

Here are the tips to choose which IDP solution you are going to use:

  1. The most convenient one that does not require complicated programming code.
  2. Choose IDP that is bundled within or works seamlessly with automated tool software such as RPA. 
  3. Something that can handle documents in multiple languages. This is important especially for companies that work in multiple countries. 
  4. Something that can “learn” and improve with more data. 
  5. Ability to work with multiple enterprise IT applications (e.g. accounting software, ERP software, etc.) 

Gleematic will serve you the combined benefits of RPA and Intelligent Document Processing (IDP), regardless of the industry sector you are in. 

Intelligent Document Processing (IDP): Impact for Business in 2021

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Written by Ada Lim & Elsa Ajarwati

Reference

Engineering, I. (2018, December 5). Deep learning for specific information extraction from unstructured texts. Medium. https://towardsdatascience.com/deep-learning-for-specific-information-extraction-from-unstructured-texts-12c5b9dceada?gi=5740bc3d9fe0

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