What does AI mean in insurance?

Humans started to eat cooked meat, which gave them higher protein meals and was less likely to make them ill through food poisoning. That likely led to our brains growing in size too.

As a community, we also started to sit around the fire with our family groups. Not only did this keep us warm, but it also bonded us together and saw the foundations of language and storytelling begin to form.

Don’t get me wrong, when misused, fire wasn’t all good. After all, as children, we all know that if you play with fire, you get burned.

However, when fire was put to good use, it ushered in a new technological wave of change in human civilisation – one we’re still riding now.

It’ll be all AI on the night

OK, you may have thought you’d accidentally started to read a Yuval Harari essay on civilisation rather than a blog on AI in insurance. But, there’s a logic to my madness.

Fire and AI are pretty similar in that they can both usher in a period of great positivity and productivity.

So what is AI?

To borrow a word or two from Wikipedia:

Artificial intelligence – AI – is intelligence demonstrated by machines, as opposed to natural intelligence displayed by animals, including humans.

That, in many ways, still feels like a grandiose definition as it puts AI on a level pegging with human intelligence, which it definitely is not. Not yet, anyway.

And we shouldn’t really think of AI in that way. I prefer to think of it as a tool for humans to use and benefit from.

AI is smart at taking detailed tasks and turning them around faster, quicker, and more accurately than humans. This leads to many benefits, including lowering costs and lessening time wastage.

AI is also a catch-all term for several arrears of tech. The ones you’re most likely to have heard of are:

Machine learning

Computers are trained to recognise patterns within numerous real-time data points – for example, reacting to competitors.

From that, they make predictions on future outcomes – such as how likely a person is to crash their car.

Deep learning

Similar to machine learning, deep learning models can analyse and draw conclusions from data. However, these models learn by themselves.

Reinforcement learning

Reinforcement learning is a type of machine learning where models are trained to make a sequence of decisions – Trial and error are used to find the best solution.

At the heart of Nuon’s AI is reinforcement learning and you can read more about that in Why Reinforcement Learning for Insurance Pricing?

Is there a need for AI in insurance?

To put it simply, yes. But you didn’t come here to read a blog for a one-word answer.

As mentioned earlier, the world is a funny old place at the moment. In many ways, we’re at the edge of a new frontier where innovation and disruption are the keys to finding your way.

According to a 2020 report by Accenture¹, “76% of insurance executives say the stakes for innovation have never been higher — getting it right will require new ways of innovating with ecosystem partners and third-party organisations”.

And a 2021 report from Deloitte shows that 40% of CIOs are going to increase AI spend².

OK, those points are good indicators of what people are doing, but it’s important to remember the why: – faster, quicker and more accurate.

That also includes reducing human error, where AI becomes a tool that frees up time and takes away the banal tasks, like data entry. This, in turn, allows people to concentrate on human interaction and customer service.

By any definition, most companies would like to work towards those goals – not least the insurance sector where AI – according to McKinsey – can drive a staggering $1.1 trillion in potential annual value³.

That statement from McKinsey gets to the heart of what this blog is all about. AI is not a race to the bottom, or top, of price. AI in insurance is about risk being priced in the right way for customers and providers.