Business operation leads should ensure that the implementation of artificial intelligence and machine learning tools is effective and targeted

Artificial intelligence (AI), machine learning and digitalisation are key words that those tasked with improving business processes in the insurance sector will be well aware of – but these tools also present the opportunity to show end customers that the insurance industry values them.

This was according to Andy Fairchild, advisor and non-executive director at various insurance-related firms and owner of consultancy Julyfourth Services.

Speaking during an Insurance Times webinar entitled AI: A driving force for the future of insurance yesterday (24 November 2022), in association with Inawisdom, Fairchild explained: “[AI] is how we can show customers that we value collecting their data more than we currently do.

“We must, as an industry, show customers how important that data is and how important data collection for the provision of an insurance product is.”

AI processing of customer data and the use of AI-enabled chatbots to respond to customer queries would improve the customer experience by speeding up often slow customer journeys, said Fairchild.

But the collection of data behind these operations has to be improved too. Fairchild continued: “We can get that customer data from a person-to-person interaction or – increasingly – from a person-to-machine interaction and therein lies a big move for the industry.”

Fairchild added that the better collection and deployment of data to construct AI models could transform customers’ interactions with the insurance sector from a “trudge process” into something that “they really value”.

Revolutionary developments

AI and machine learning also have the potential to “revolutionise” the insurance sector in terms of risk selection and pricing if data collection improves, Fairchild added.

He explained: “The fundamentals of our industry are risk, risk selection, the terms that we underwrite that risk selection on and the price that we put on it.”

However, Sameer Deshpande, head of enterprise architecture at broker PIB Group, said that the insurance sector was lagging behind other areas of financial services in its use of artificial intelligence.

Deshpande explained: “There are a number of areas where [insurance is] still behind the curve – [for example,] manual processes and document processing.

“There are scenarios where the way we interact with our customers is really a low point – it’s still very much dependent on central operations.”

Insurance must move away from these central operations and call centres in order to catch up with the level of service that other industries are providing to customers, Deshpande said.

He added: “We could use modern techniques like intelligent document processing when it comes to a lot of documents being exchanged between the customer and the [insurance business] – there’s a need to extract information out of these emails, [such as] structured data, unstructured data and processing.”

AI powered chatbots could also remove the need for insurers to employ staff to respond to queries and improve response times to customers.

Use case

Despite the advantages that AI can bring to insurance firms in terms of both improving service and demonstrating the value of data, experts speaking at Insurance Times’ webinar agreed that it was important not to rush headlong into adopting AI just for the sake of it.

Alex Molinero, business development director at Inawisdom, said: “With [artificial intelligence and machine learning], you need to keep in mind ‘what’s the business benefit?’

“For each and every use case, you want to ask what the value is.”

Molinero added that when implementing AI into an insurance business, operations managers should focus on “low-hanging fruit” – those areas with the least complexity and the most business value – as this would encourage further, more complex adoption of these useful tools in the future.