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Can artificial intelligence be good for insurance?    

15 August 2023    |    By: Joe Sharpe

It’s said that 2023 will be seen as a key year in the advancement of commercial artificial intelligence (better known as AI), prompted by the launch of ChatGPT in November 2022, which has subsequently rocketed artificial intelligence into the gaze of the mainstream media and through 2023 has remained as a globally trending topic.

According to Google Trends, the global popularity for the search term ‘artificial intelligence’ on Google’s search engine has more than doubled since December 2022, hitting peak popularity in between the months of April 2023 and May 2023.

AI however isn’t an entirely novel concept, in fact it’s something that engineers and computing experts have been studying and building since before the 1950’s – the nature of AI however means that as time goes on and as computing power improves, AI’s capacity to learn improves and therefore we should expect to see a positive correlation between time passed and the capability of AI in the future. AI is able to learn from AI and thus a culture of rapid information sharing is created which goes way beyond the ability of a group of even the brightest humans.

In order to understand if AI can be good for insurance, we need to explore exactly what AI is and what sort of impact it could have, not just within insurance but across a full spectrum of industries such as technology, hospitality and healthcare to name but a few.

The theory behind AI aims to help us understand how we can make humans and machines more alike in a bid to make our daily lives more productive and more efficient. In practice, AI is a tool which can be deployed to help humans' complete complex tasks quickly and could exist as an extension to our very own cognition. With the help of AI, we as humans are able to carry out complex mathematical calculations in a very short space of time which can then go on to inform better decision-making processes, regardless of context.

According to this article by McKinsey & Company, artificial intelligence is:

“A machine’s ability to perform the cognitive functions we associate with human minds, such as perceiving, reasoning, learning, interacting with an environment, problem solving, and even exercising creativity. Voice assistants like Siri and Alexa are founded on AI technology, as are some customer service chatbots that pop up to help you navigate websites.”

There a several ways a computer can harness the power of AI, one of which is a hot topic in the media at the moment; machine learning. Machine learning is a form of artificial intelligence which allows a machine to use data to train its own decision-making processes:

“Machine learning algorithms can detect patterns and learn how to make predictions and recommendations by processing data and experiences, rather than by receiving explicit programming instruction. The algorithms also adapt in response to new data and experiences to improve their efficacy over time. Machine learning has already had impact in a number of industries, including achievements in medical-imaging analysis and high-resolution weather forecasting.”

In essence, with machine learning a computer is able to use reason to learn from huge datasets, much beyond the capacity of even the most intelligent human being. Through this, machines may be able to make pinpoint accurate decisions and take action according to its decisions about a particular dataset.

You may also have heard of deep learning. This is an enhanced type of machine learning which allows for a broader range of data to be introduced into the process. This could include images and audio alongside numerical or written data. Deep learning uses ‘neural networks’ which are set up to mimic the way neurons interact in the human brain. Deep learning allows AI to not only use reason, but also to make sophisticated predictions based on existing data. Deep learning adds extra dimensions to the complexities of regular machine learning through the use of a broad range of data types. A simple way to describe this would be that a machine learning model may be able to recognise the letter ‘A’ as the letter A, whereas a deep learning model may also be able to recognise a hand drawn photograph of the letter ‘A’ as the letter A, something that a simpler machine learning model may not be able to do. 

AI is threatening to disrupt many industries thanks to the potential benefits it boasts, the same can be said for the insurance industry also – AI has the potential to completely transform the way insurance works globally and, when used correctly, could prove to be very advantageous for insurers, brokers and customers alike.

There is no precise use case for AI in the insurance industry, rather it’s more likely to be used to revolutionise certain processes or touch points in the insurance cycle. Take the introduction of live chatbots for example – AI could be used to process insurance renewals without the need for any human intervention. An AI chatbot could quite easily reach out to a customer, check their cover is still suitable and offer a renewal quote accordingly. After receiving confirmation from the customer, that same AI could then complete the transaction and arrange the insurance cover, before sending out the relevant documentation to the customer.

Although this is a very over-simplified example of AI in insurance, hopefully you understand the concept and how a chatbot could be deployed by an insurance company in this instance. AI efficiencies mean that smaller tasks in the insurance cycle could be totally automated and could be set to ensure that the customer gets the very best deal, 100% of the time, reducing the margin for error which occurs when a human carries out the same task. 

We are only really scratching the surface when we consider chatbots and their use within insurance customer service. AI which uses deep learning models can offer far more complex solutions to everyday insurance problems, from processing claims and analysing risk, to marketing new insurance products and even arranging claims. As an industry which handles vast amounts of data every minute, the world of insurance is crying out for new technologies to ensure better outcomes for insurance customers. AI hopes to break down barriers and provide insurance professionals with the tools they need to make insurance better and more accessible for everyone involved, whether that’s insurance underwriters, brokers, loss adjusters or even customers – AI offers the potential to introduce improvements that everyone can benefit from across the entire industry.
Joe Sharpe
Article by
Joe is an account executive at Premierline with over 8 years’ experiencing providing insurance solutions for a range of business customers, from SME to larger clients. Joe is passionate about providing customers with high-quality technical advice on insurance products and services that can help protect UK businesses. By keeping ahead of the trends and investigating the goings on within the insurance market, Joe enjoys writing content to share with Premierline customers to keep them informed on the insurance products that matter to them.
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