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Robotic Process Automation: Tackling High-Volume Document Processing with AI

Robotic Process Automation: Tackling High-Volume Document Processing with AI graphic

Organizations that create, receive, store, and process thousands of documents a day often struggle to manage documents effectively on the way in, around, and out of the business. Robotic Process Automation (RPA) is often your team’s best resource to ensure your documents are made discoverable, searchable, secure, and high-quality.

It delegates high-volume, predictable tasks to bots and algorithms. This frees up human employees to tackle more complex and context-rich assignments to humans who are “wired” for that kind of thing.


RPA in the Wild

You probably love doing your taxes every year and filling out forms for other financial purposes, right? Perhaps not. H&R Block uses RPA to augment the expertise of their branch staff and to ensure their clients don’t miss out on any tax deduction opportunities. It means less data entry for tax consultants and faster return processing.

On the flipside of accounting practices, auditors can also leverage RPA to review thousands or tens of thousands of pages of financial records in the time it can take a human auditor to review just a few. Finding needles in haystacks or financial transaction anomalies is daunting for humans, but for an RPA bot, it’s just another day at the office.

Finance isn’t the only industry that benefits. Bots can also be put to work helping doctors diagnose an illness based on available case histories. They can help online retailers handle routine interactions like checking order status or common customer service inquiries.

Knowledge workers are often as time-challenged, distracted, uninspired by minutiae, and prone to error as any us mere mortals can be. The digital age is increasingly infused with Artificial Intelligence (AI), which is a good thing because the pace of document creation and circulation isn’t going to slow any time soon. Many aspects of AI are enhancing our ability to extract insights from structured and unstructured data. Here are five ways RPA is unburdening document authors, reviewers, and approvers from high-volume tasks which lack in strategic value.


1. Optical Character Recognition (OCR) and Intelligent Character Recognition (ICR) Processing

Hospitals and insurance companies are just two examples of organizations which create and process many forms where typed and handwritten text is commonplace. Scanning these forms from paper format is one step to extending the usability of these forms. OCR and ICR raise the bar even higher.

Consider how much time and money it can take to have administrative employees or BPO service providers manually enter form data. Compare that investment with the cost of extending your business applications with OCR functionality. Searching text across documents born digital or converted that way will vastly improve.


2. Image Quality Assurance

The human eye is an amazing organ. It’s amazing how photographers and graphic designers can spot minor image blurriness or a skewed photo. Yet our eyes pale in comparison to a virtual image processing assistant that can deskew, despeckle, or alert their human counterpart to recapture a document or manually fix a flaw.

Anyone that gazes for hours at even the finest of LCD screens can imagine how helpful image processing could be. They can review higher volumes of photographs or clinical images than any human could hope to. All with consistent quality, without taking breaks or getting eye fatigue.


3. Metadata Extraction

Getting the best insights from your document repositories through big data tools often depends on your organization’s ability to extract details from file metadata. Manually profiling documents is often tedious, and is prone to error. RPA engines can pull comprehensive metadata from files long after they are created, at speeds and accuracy humans could never achieve.

Better document metadata is critical for accurate reporting and document discoverability. Document authors may attach keywords about a document which are pertinent to their role, yet an AI engine can profile a document with less bias for a wider audience.


4. Accelerate Approvals and Workflows

Processing travel expenses, approving sales quotes, and reviewing contract terms are just a few examples where busy executives can become a bottleneck to business success. Standard, expenses, forms, contracts, and proposals below a defined value are better assessed based on pre-defined business rules and can be qualified and approved by an AI assistant.

Where anomalies are identified, human approvers can be alerted, or non-standard terms can be escalated to legal departments on a case-by-case basis.


5. Digital Rights Management (DRM) and Document Markup

Though most employees are constantly vigilant about following organizational policies about printing, sharing, or emailing documents inside or out of their organizations, mistakes happen. RPA document processing can identify document text which should be redacted, or when certain DRM controls should be applied to sensitive documents.

In regulated industries like financial services, government and healthcare, a virtual document control engine which governs whether users can manipulate documents can be critical to preventing data loss.

Accusoft has long been helping our customers to extend their business-critical applications with document management and control functionality. With the help of an established industry leader, our team is currently working on an RPA solution that will help automate manual data entry for a variety of organizations.