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Intelligent Document Processing and its Use Cases

Intelligent Document Processing and its Use Cases

Robotic process automation (RPA), which streamlines some tedious, non-document-focused processes restricted to work that occurs on computer screens, has been the main kind of automation up until this point. Unfortunately, their abilities are limited to jobs that don’t require complex judgment.  


A relatively new category of automation called “intelligent document processing” uses artificial intelligence (AI), machine learning, and natural language processing to help businesses handle their papers more effectively.  


Because it can read and comprehend the context of the information it extracts from documents, it marks a change from earlier legacy automation systems. It enables businesses to automate even more of the document processing lifecycle. 


IDP provides a variety of benefits, including: 


Direct cost savings: Reduces expenses by dramatically cutting costs to process large volumes of data 


Ease of use: Allows businesses to get set up faster and automate more processes 


Process efficiency: Enables end-to-end automation of document-centric processes 


Accuracy uplift: See immediate significant increases in data accuracy with the use of AI 


Strategic goal boost: Intelligent document processing supports business goals like improving customer experience 



Nearly every industry can implement intelligent document processing — and the technology has already brought incredible benefits.  


A 2020 survey by Bain & Company of executives in the supply chain, human resources, operations, and service delivery sectors reported cost savings of roughly 20% per year after implementing intelligent document processing. 


Here are four of the best ideal document processing use cases: 


Data extraction 


Many organizations still use paper documents, PDFs, or images that require some degree of data entry. IDP programs can extract even the most complex data from records, identifying critical information in emails or finding the invoice number in an unfamiliar layout to render it machine-readable data.  


This eliminates the need for manual data entry, reducing hours of mind-numbing work and potential typos and other human errors. 


Document classification 


Since the AI in IDP programs can both read and label information, users can train it to identify and correctly route documents without ever needing a human to read them.  


In the finance industry, lenders can deploy this feature to classify documents applicants send in batches. Tax records, pay stubs, and property assessments are automatically sent to appropriate departments for review. 


Email processing 


Reading and responding to emails is incredibly time-consuming — especially for customer service professionals. AI’s natural language processing capabilities can detect an email’s intent and automatically respond appropriately.  


For organizations with catch-all contact forms or general email addresses, IDP can automatically route incoming messages to the correct department and even extract critical information such as support ticket numbers, addresses, and other data each department needs to begin processing that email quickly. 


E-commerce platforms can help customer service reps respond to emails more quickly since they won’t have to read each message as closely. For instance, when properly trained and set up, the IDP platform can understand when an email is requesting a refund, for which order, and what amount, and automatically route this information to finance for further processing.   




Industries are subject to increasingly complex regulations, with shorter timeframes to meet them. IDP can streamline compliance by quickly responding to requests from regulators and pulling appropriate information or documents from databases with less manual intervention than usual. 


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