5 intelligent document processing use cases that prove the benefits of AI

Mar 09, 2022 by Automation Hero

5 Intelligent document processing use cases that prove the benefits of AI

For all the talk about automation being the future, it’s actually been a mainstream aspect of business management for almost 20 years. Until now, most of this automation has been robotic process automation (RPA), which streamlines some mundane, non-document centric tasks limited to work that takes place on computer screens. Unfortunately, their capabilities are limited to tasks that don’t involve high-level decision making.

But advancements in artificial intelligence are starting to bring automation to tasks beyond the scope of RPA.

Intelligent document processing is a relatively new class of automation that leverages AI, machine learning, and natural language processing to help organizations efficiently manage documents. It represents a sea change from older legacy automation systems because it can both read and understand the context of the information it pulls from documents, essentially allowing organizations to automate even more of the document processing lifecycle. 

Five intelligent document processing use cases

With these capabilities, 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. But how exactly do they implement the technology?

Here are five of the best intelligent 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 documents, whether that’s identifying key information in emails or finding the invoice number in an unfamiliar layout, to render it machine-readable data. This completely eliminates the need for manual data entry, reducing hours of mind-numbing work and the potential for 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 that applicants send in batches, so that 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. The natural language processing capabilities of AI can actually detect the intent of emails 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 key information such as support ticket numbers, addresses, and other data each department needs to quickly begin processing that email.

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 will be able to understand when an email is requesting a refund, for which order, and what amount, and automatically route this information to finance for further processing.  

Compliance

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.

This use has proven especially useful in Europe for GDPR Subject Access Requests, which companies must respond to within 30 days to avoid fines. 

Claims processing

IDP tools with end-to-end capabilities make it ideal for claims processing in the insurance industry where complex customer service environments work with support tickets. As claims come in, IDP platforms can automatically identify who the customer is and what the claim is for, then route it to the correct departments for further action. Once approved, IDPs can even automate invoice payments and send customers notification letters that the claim is closed.

With endless Intelligent document processing use cases, organizations are still finding new ways to use the technology in their operations. Virtually any processes that involve converting data and acting upon it are candidates for automation. Even better, the more processes you automate, the more powerful AI will become, enabling it to find ways to automate even more.

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