IDP Versus OCR – Take OCR Output to the Next Level With Intelligent Document Processing
The article explains the difference between an Intelligent Document Processing IDP tool and an OCR tool for easy data integration with business systems.
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We all know what Optical Character Recognition is. It is a tool that converts the data on a printed document or an image into a digitized format. It involves digitizing text strings on the paper such that the digitized document can be stored easily in the central storage, such as the enterprise content management system. However, the data cannot be used directly in enterprise business systems or ERP systems. Here, Intelligent Document Process (IDP) steps in. It not only converts the document to a digitized form but also covers the data to a structured form that can be easily integrated with business systems.
What Is Intelligent Document Processing?
Intelligent Document Processing (IDP) is an artificial intelligence/machine learning-powered solution for intelligent data capture. Intelligent Document Processing allows contextual extraction of data as compared to text string extractions in OCR. For example, a number 12345 that is extracted by using OCR is a plain number. However, when it is extracted by using Intelligent Document Processing it assumes a contextual meaning. It takes on a specific label such as an invoice number, an invoice payment amount, or a record number in a long winding document.
How Does Intelligent Document Processing Take OCR Output to the Next Level?
OCR just digitizes data. However, the contextual referencing of data in Intelligent Document Processing imparts an intelligent reference that is useful in data integration in the core systems or ERP systems. It also allows collecting data in a systematic format that eliminates data preparation work that is required for analytics. The contextual referencing and pre-defined business rules for extraction also allow correlating data during analysis to derive 360 degree picture, which forms an integral part of data analytics.
Intelligent Document Processing is thus much more than simple OCR. It takes the OCRed output to a much higher level in the data lifecycle that otherwise would have remained “just an extracted text string”. Moreover, it is compatible with most OCR engines in the market thus ensuring that your existing technology investments are augmented and not wasted.
OCR requires a template to process each new type of document. Whereas Intelligent Document Processing is template-free. It uses Artificial Intelligence / Machine Learning algorithms and fuzzy logic to ascertain the position of different pre-defined fields on the document that simplifies data extraction and easy assimilation.
OCR engines use the “what you see is what you get” principle. Intelligent Document Processing on the other hand has a number of pre-processing and post-processing features. The pre-processing ones allow to improve the hue, brightness, and contrast, reduce noise, deskew, remove horizontal and vertical lines, correct of characters and color, smoothen and complete characters, etc. The post-processing ones allow to auto-correct, auto-validate, auto-format the data, and much more. Together, pre-processing and post-processing improve the accuracy of the extracted data to 99%* thus requiring only limited eyeball verification by the humans in the loop.
Where Is Intelligent Document Processing Used?
Intelligent Document Processing is the go-to tool in all paper data-intensive industries and services. Banking and Financial Services, Insurance, Trade Financing intermediaries, Legal, Auditing, Manufacturing & Logistics, Supply Chain, Healthcare, Government & Public Services are the most prominent ones. All these industries generate thousands of documents as a result of their business processes, on a daily basis. Each of these industries operates as an ecosystem. When a paper document leaves their office, the data is totally disconnected from the electronic systems. The receiving entity has to use Intelligent Document Processing to ingest the data in their systems and expedite the business processing. As businesses increasingly operate on a global turf in a 24x7 mode, the above-mentioned services have to fall in their step. Intelligent Document Processing is highly beneficial in this scenario.
Use Cases for Intelligent Document Processing
Businesses have a wide trajectory of Intelligent Document Processing use case implementation. Some important use cases are mortgage document processing and customer onboarding in Banking and Financial Services. Bills of lading management and customs document management in Logistics. Invoice processing and EXIM process management in Manufacturing.
Besides, Intelligent Document Processing has extensive use in support functions. Candidate application processing and employee data updation in Human Resources. Contract administration and case reviews in
Legal firms and departments. Response management and contextual data extraction in Customer Management.
Benefits Brought to the Table by Intelligent Document Processing
Here are some important benefits brought forth by Intelligent Document Processing –
· Ingest unstructured data from paper forms, PDFs, images, and email attachments
· Convert unstructured data to a structured format for easy and fast integration with business systems
· Process thousands of paper form documents on a daily basis
· Expedite business processes and propagate a paperless environment
· Auto-classify and auto-index the documents at the ingestion stage
· Extract key points and append them as metadata prior to digital processing
· Improve speed of processing and productivity even in the paper-driven environment
Intelligent Document Processing magnifies the output of OCR by manifolds. It makes the OCR output not only useable but also highly integrable with business systems. It brings paper data on the same level as all other digital data that can be easily analyzed. It makes the unstructured data, which was ignored earlier, very usable and expedites business processes.
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