Insurance bosses ‘constantly’ wondering if they are ‘missing a trick’ over AI use

Senior leaders within the insurance industry are ”constantly looking left and right” due to concerns that they may be ”missing a trick” on ways to use artifical intelligence (AI).

That was according to David Carmalt, managing director of financial services at ExploreAI, who said that there was more of a willingness from bosses to explore how AI can benefit their firms.

He explained that the “public hype” around AI had made it easier for senior leadership to get funding for implementations, making them ”think about how money can be spent”.

“This is, albeit, in a way that there is a clear return on investment,” Carmalt said during Insurance Times’ AI: Revolution or Hype webinar, which was chaired by acting editor Yiannis Kotoulas last week (5 October 2023).

”[However], everyone within the industry is constantly looking left and right.

“They wonder whether they’re missing a trick or if a peer is going to overtake them because they’re using a technology that they haven’t looked at too closely.

“For the insurance sector specifically, it’s becoming very clear that across the entire insurance value chain – whether you’re talking about risk pricing, underwriting, reserving, intelligent chatbots or fraud detection – there’s a raft of use cases.

”These use cases are beginning to percolate through that senior folks within firms are recognising.”

ChatGPT

During the webinar, Dewald Botha, director of AI solutions at ExploreAI, added that there had been a “sudden interest” in AI due to technological advancements, improved algorithms and the introduction of ChatGPT.

Botha said that ChatGPT led to a ”marketing boom” as it ”was the first time that the public has been granted access to AI in a simple and user-friendly interface”.

This has been used in the insurance industry – for example, earlier this year (27 March 2023), Zurich said it was experimenting with the tool as it explored how it could use AI technology for tasks such as extracting data for claims and modelling.

Botha explained that algorithmic advancements occurred in 2017 and that deep learning framework was ”instrumental for setting generative AI for its success”.