The Role Of Cognitive RPA In The Insurance Industry

Image for post
Image for post

Cognitive robotic process automation (RPA) is a fast-evolving field of computing and is an emerging form of business process automation (BPA) technology. It involves the automation of many internal and external customer journeys through software “bots.”

Where RPA Started

RPA started roughly 20 years ago as a rudimentary screen-scraping tool, technology that is used to eliminate repetitive data entry or form-filling that human operators used to do the bulk of. For example, the software could copy data from one source to another on a computer screen. Imagine a finance clerk handling invoice processes by filling in specific fields on the screen. Early RPA was able to take this function off the clerk’s plate by automating that invoice processing.

The insurance sector soon discovered how this technology could be used for processing insurance premiums. Typically, when brokers sell an insurance policy, they send notices using a variety of inputs, such as email, fax, spreadsheets, and other means, to an intake organization. Intake teams historically managed this multi-step sales process manually, including organizing the data, checking for completeness and accuracy, working with brokers to correct errors, extracting other necessary data from online sources and then completing the sale.

Insurance intake teams and operations teams have, in the last few years, used RPA software to run the structured parts of the intake and claims process. Specifically, these teams would organize incoming data and then feed that data to back-end software bots. The bots would then collate this information into systems of records to complete the workflow. All of this was happening around 2016.

Cognitive RPA Brings Intelligence Into The Equation

Thanks to recent advancements in artificial intelligence (AI) and machine learning (ML), process automation has evolved from being a mere screen-scraping technology with bots handling repetitive processes to more cognitive technology, enabling software bots to make intelligent decisions that assist human workers.

Cognitive RPA (CRPA) involves technologies such as natural language processing, machine learning and deep learning that take information already available in the enterprise to create models that lead to autonomous, cognitive-based decisions. This entails understanding large bodies of textual information, extracting relevant structured information from unstructured data sources and conducting automated two-way conversations with stakeholders. A good application for CRPA is taking accepted and rejected insurance applications and feeding them into a system that can learn how those decisions were made based on information in the applications. CRPA software is then able to automate the acceptance or rejection of subsequent applications, leading to considerable cost savings for the company.

Choosing A CRPA Platform

It’s important to identify and assess the following key features in a CRPA Platform:

• Data Security: When outsourcing sensitive customer data to business to business (B2B) companies, it is imperative to safeguard your customers’ information. Ask any potential vendors if they are SOC 2 compliant. SOC 2 compliance is a voluntary and stringent auditing procedure that probes the security practices of companies storing customer information in the cloud. It guarantees that only the most trustworthy and airtight data security practices are being used.

• Omni-channel Capabilities: Companies and their technologies vary widely — some companies can automate processes over APIs, documents, SMS, voice, email and/or the web. Assess what your company needs and values. Email triaging? Chatbots? Voice recognition? Intelligent document processing?

• Low-Code And No-Code Integrations: Business process transformations that are often dependent on IT teams and having solutions that can deliver outcomes with minimal implementation efforts lead to considerable ROI quickly.

• Ability To Digest Unstructured Data: A large majority of all data is unstructured and does not fit into a predefined mold. Ingesting unstructured data increases a company’s CRPA potential exponentially, as their models can handle any data that is thrown their way.

When choosing a CRPA platform, it is important to take all these factors into account. Due diligence at the beginning of your implementation will make sure your automation initiatives result in quick efficiencies and ROI.

Introducing Inmediate: a platform on which customers, distributors and insurers using smart contracts connect.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store