WHAT’S NEXT FOR UNDERWRITING

When someone makes a claim to their insurer, it’s usually because they’ve gone through a negative life experience. Their home or car has been damaged, or they’ve lost a loved one. RPA allows the insurer to automate so-called ‘keystroke tasks’ – like identifying the basic information around a customer interaction before it fully begins, or lifting and shifting account details from a piece of customer correspondence into a claims form – and creates time for human agents to add light and shade in between. If you like, it's the brawn to the brains of another of the insurance industry’s big trends – the adoption of artificial intelligence (AI) and machine learning (ML). While AI and ML

Insurance use cases for RPA

Extracting data

One global insurer is using software robots to extract information from customer correspondence and match it with the appropriate claims forms – something that would have taken a human agent around 4 minutes each time beforehand.

Customer service

Chatbots provide a first line of defence for insurers in customer service, allowing simple queries to be resolved instantly and collecting pertinent information for later customer service interactions. Where a chatbot is insufficient to deal with a customer, human agents can step in and gain an immediate understanding of the situation thanks to the data already gathered by the chatbot.

Handling forms

Where physical forms or physical documents still exist within a back-office process, integrating OCR scanning with RPA means insurers can automatically ensure that information is transferred from the physical realm to the digital one quickly and with minimal human error.

Underwriting

To understand risk and price a new policy, underwriters need access to multiple sources of information. RPA can ensure that this information is already in place when the human underwriter comes to assess the policy application for the first time, meaning policies can be offered much more quickly.

Product innovation

It’s not just back-office functions being transformed by RPA; insurers are bringing the technology direct to consumers, too. By experimenting with the full scope of RPA, you can roll out on-demand pricing and improve the performance of customer portals, to name just a couple of examples.

attempt to simulate human intelligence to create meaningful interpretations from data, RPA is simply the muscle: it replicates the time it would take for a human to work manually with data, often on arduous and timeconsuming activities. As such, RPA can be said to increase productivity; lead to significant cost savings for the insurer and, subsequently, the insured too; reduce the extent and likelihood of human error; and even increase job satisfaction among employees.

Elliot Green, Sales Director at Genasys, believes that RPA can be a good entry point for insurers to get into more sophisticated

AI, which is often just a buzzword applied to a clever line of code. Green says: “The bulk of insurers and MGAs that we deal with could benefit from automation over actually trying to reinvent the ocean, actually automating a load of processes and using technology to do that is a good starting point for the future, when AI models will become more prevalent. For the bulk of people in the market, doing some automation is a good first step.”

In many cases, Chris Moore continues, the problem with an organisation embracing digitisation and automation is a cultural issue, not a technical one: “I hate the narrative around legacy technology. It’s absolutely a wall that people hide behind. I think when you peel that back, it’s culture. If you don’t have a client-first culture, then you won’t embrace change and I think it’s going to be a real challenge for your business going forward.”