Cognitive Document Automation: The Missing Link to Robotic Process Automation

Cognitive Document Automation: The Missing Link to Robotic Process Automation

In today’s competitive market, end-to-end automation is the key to success. Robotic Process Automation (RPA) plays a key role in enabling it, helping companies improve efficiency and lower operational costs.

These automated systems improve our understanding and integration of information, transforming inefficient legacy systems into modern solutions that accelerate business processes. At the same time, they enhance acquisition and third-party web-based systems.

That said, handling unstructured information remains a challenge despite the automation of several processes. Inefficient management of documents such as emails and documents (PDFs, spreadsheets, etc.) creates roadblocks, making it difficult for employees to analyze and understand each document’s information effectively.

Despite introducing automation through RPA, companies fail to process documents efficiently, increasing operational costs, as a result. According to Deloitte, the cost of managing records physically is five times higher than digital records, even after factoring in Data Recovery (DR). This cost trickles down to your customer and ultimately impacts the quality of your service.

This is where Cognitive Document Automation (CDA) can transform the core of information management. CDA is the missing link that completes robotic process automation and allows us to automate document management intelligently.

In this article, we will discuss why you need Cognitive Document Automation to bridge the gaps in automation and make most of Robotic Process Automation.

Why Do We Need Cognitive Document Automation in RPA?

Robotic Process Automation is not simply replacing your employee’s keyboard activity by supplementing it with structured and verified information. It relies on a series of processes where we use machines to limit and replace manual intervention.

Although you can use an RPA system for databases, applications, PDF, or even spreadsheets, most business processes rely on information stored in business documents and messages. However, in the absence of an intelligent solution, this system is one-dimensional and fails to automate processes completely.

Cognitive document automation is an intelligent solution that leverages OCR and artificial intelligence (AI) to automate the extraction, understanding, and integration of documents required in organizational processes. It enhances the ability of robotic process automation, enabling businesses to automate their processes more effectively.

Companies with document-centric RPA models benefit significantly from CDA. The technology helps companies accelerate business processes, boost productivity, and efficiency, better engage and empower customers, and reduce labor costs. You can automate information processing for unstructured data.

Extracting, processing, and organizing information in this manner helps us understand our wealth of data and send relevant insights to teams in a timely manner. RPA can only automate repetitive manual tasks interacting with applications and websites, communicate with systems, and trigger responses.

Thanks to CDA, you can automate document capture and electronic data capture simultaneously. By adopting CDA, we can increase the productivity of existing staff, minimize operating costs and significantly accelerate ROI and paybacks.


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What Are the Areas Where CDA Can Help RPA?

Cognitive Document Automation is essential for filling in the gaps in RPA. Here are a few areas where CDA can revolutionize your business when used collectively with  RPA.

1. Provider Credentialing

Whenever new providers sign up for renewal or apply to join a network, you must validate their credentials. Document transformation and capture embedded in CDA helps us extract and classify the incoming credentialing information.

All the while, RPA analyzes this information and validates it against the data found on the web. To do this, the system pulls information found online, as well as the information extracted from capture. This collective wealth of data is then compiled into one document, where a customer service agent can review it. Intervention from capture RPA led automation not only saves money but also decreases the time to process applications significantly.

2. New Customer Onboarding

Banks must verify the personal IDs and credit-worthiness of new customers applying for a line of credit. For this, customers can snap a picture of their ID through a mobile phone, and then forward it to a mobile ID and verification software, which can then confirm the customer’s identity. Here too, CDA can easily use transformation and document capture to extract and classify customer applications. What took days and months can now be done in a few hours by using CDA for data extraction and RPA  for pulling together credit verifications from the web.

3. Invoice Management

CDA is often used for invoice extraction. This intelligent software is mostly embedded with pre-configured features implemented by keeping best practices in mind. This is why CDA systems can automatically identify and extract data from invoices regardless of the currencies and countries involved.

Users only have to enter data in the field data to provide initial samples for supplier invoices. Once you do that, the system uses AI and machine learning to embed the design in the machine’s memory and recognize those invoice fields in the future.

4. Customer Verifications & Approvals

Since most data is unstructured and inaccessible, we need an intelligent tool to verify, classify, extract, and organize information effectively. Machine learning is an important part of CDA and enables us to do every one of these things while utilizing data that was hard to use. Additional information gives us useful insights and makes decision-making more efficient.

CDA allows companies to resolve operational issues such as Anti-Money Laundering (AML), Customer Due Diligence (CDD), Know Your Customer (KYC), and Anti-Money Laundering (AML), and other compliance requirements to cut down delay in verifications.

CDA first captures and extracts indexes and subsequently classifies loan application documents. Afterward, RPA can then send ID verification information per form Know Your Customer (KYC) checks, ensuring that you can do customer verification in minutes instead of days.

5. Mortgage Loan Processing

Mortgage loan processing takes considerable time and effort. CDA can help us capture and classify information from mortgage applications and supporting documents. At the same time, RPA helps by compiling additional data from both external and internal systems. Most notably, for delivering all data to a system of record and identifying verification in a KYC (Know Your Customer) check.

Once the mortgage loan application is closed, RPA and CDA collectively help you compare and validate documents for compliance. You can also execute pre-established rules for moving mortgage loan docs via post-close workflow and integrate closing documents with the system of record.

Collectively, CDA and RPA automate both physical and electronic document & data capture, helping you transform your workflow into a fully automated and intelligent business flow.

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