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Robotic Process Automation and Cognitive Document Automation Make for Better Business

But we are still often left with a crucial gap. How do you handle information sources that lack structure, like the documents and emails that still flood organizations every day?

The fact is that no matter how much ROI we see from RPA, if we still rely on repetitive, manual and error-prone methods to process our documents, our business isn’t getting the full benefits of automation.

RPA + CDA

This is where cognitive document automation (CDA) can serve as a powerful partner to RPA. Together, RPA and CDA connect paper, people and processes through foundational artificial intelligence (AI) and software robotics. CDA encompasses multichannel document capture, intelligent OCR and machine learning. This automates the processing of unstructured data contained in documents and emails (e.g., sales orders/invoices, enrollment forms, claims, contracts and correspondence).

The “intelligence” component is a game-changer. Alone, information capture systems excel at extracting raw data from documents and electronic data sources. But in the past they have struggled to provide understanding of that data in context for better decision-making. True CDA employs AI algorithms that help computers understand, decide, learn and predict to better automate business processes that require information capture. AI can cluster, classify, separate, OCR, extract, understand human language and machine-learn information from any document type or data source.

It’s helpful to think of RPA as the repetitive “hand work” of processing electronic data. CDA is then the intelligent “head work” of understanding what a document or email is about, what information it contains and what to do with it.

RPA + CDA deliver proven ROI across many industries and use cases. They can automate everything from insurance claims to financial services to customer onboarding to invoice management.

Here are just a few of the benefits of RPA + CDA:

  • Increased productivity of all types of data handling
  • Reduced operations costs through fewer manual tasks
  • Enhanced data quality and lower error rates
  • Improved compliance and audit trails
  • Faster customer engagement and turnaround times
  • Lowered cost of ownership and time-to-configure
*This blog first appeared on our partner Kofax’s website.

CDA (and The Evolution of RPA)

Learn more about how CDA and RPA work together to make organizations more efficient in this white paper.

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