Why robotic process automation in insurance needs an AI upgrade

Robotic process automation has been helping companies improve their processes since the turn of the millennium, relieving employees of tedious duties, speeding up workflows, improving accuracy, and lowering costs. It’s been especially useful in the insurance industry, helping workers streamline monotonous computer-based tasks so they can focus on more important projects in underwriting, customer service, sales, and beyond. RPA can complete many tasks, like form registration, in just 40% of the time as manual processes.

But what if it was possible to complete insurance processes with even greater efficiency? New automation technology leveraging artificial intelligence, machine learning, and other advancements are transforming business operations for companies in every industry, including insurance.

Why robotic process automation in insurance isn’t enough

Automation technology has advanced far beyond the early RPA tools that came out in the early 2000s. New tools with artificial intelligence aren’t limited to repetitive, screen-based tasks — they can replicate advanced actions that mimic human analysis and decision making. Compared to robotic process automation in insurance, AI technology is like a quantum leap in efficiency. Here are some of the biggest problems with using RPA alone:

High implementation costs

Because of its script-based workflows, robotic process automation in insurance is incredibly time-, labor-, and money-intensive to set up and implement. In many cases, it can take months of research for IT teams to design the perfect workflows and then test them to make sure they’re error-free. The high upfront costs dramatically increase the timeline to achieving value.

Lack of flexibility

Since RPA workflows are dependent upon specific screen placements and other sensitive variables, making any changes to a process can eat up massive resources as well. This causes organizations to resist change to avoid the resource-drain of making updates to their RPA. Even worse, workers may be forced to find complicated workarounds to their RPA’s limits that drag efficiency down to pre-RPA levels. What’s more, new software releases can easily render delicate RPA platforms useless, for example, when screen automation bots cannot recognize updated graphics on operating systems and other programs, setting off a chain reaction of issues.

Limited application

Robotic process automation in insurance is limited to completing actions that occur on a computer screen. Unfortunately, so much of the work that overwhelms industry professionals is related to processing documents and extracting information. This still leaves time-consuming labor for workers to manage instead of focusing on their high-level duties.

Transforming insurance with intelligent document processing

The latest generations of AI-powered automation platforms enable intelligent document processing. AI allows machines to take over many tasks related to reading documents and extracting information — essentially saving the human brain from mind-numbing labor for more efficient workflows and less fatigue. Here are a few ways AI outperforms robotic process automation in insurance:

End-to-end document processing

AI can automate virtually every step of the document lifestyle, “reading” the text, classifying the information, and automatically inputting into destination databases or other systems for further processing. This includes common insurance documents like applications, claims, and invoices, as well as contracts, emails, and even call transcripts.

Accelerated claims processing

Claims are only approved or denied at the speed they are processed. Manual and RPA claims processing efficiency is nothing compared to intelligent document processing. AI not only handles data classification in a matter of moments but also plugs information into databases and CRMs. Some AI platforms can even connect to systems that run fraud detection models. All of this lets insurers approve claims in a fraction of the time customers are used to.

More efficient customer service

Better efficiency in document processing translates directly to improved customer service — especially in terms of fast response times. Natural language processing capabilities in AI help it detect the intent of emails to automate responses. If customers email a claim, the AI can automatically recognize the customer’s request, send an appropriate response email, and download and read email attachments for immediate processing.
Robotic process automation in insurance has been a true boon to the industry, but it’s no longer the best technology for the job. AI-native platforms like Automation Hero’s are already helping insurers automate their document processes to compete with the growing threat of fintech insurance companies. See what Automation Hero can do for your organization during a free demo.