What does AI mean in insurance?

There’s a lot of buzz around AI in all areas of our life. How people feel about that covers the full range of positive, negative or indifferent emotions. In this blog, we get to the heart of what AI means for insurance.

It’s fair to say that we’re living through a unique period in human history. For the vast majority of our time on planet Earth, we’ve lived a low tech lifestyle as hunter-gatherers.

Each day brought its own challenges of where to find food through grazing the land and hunting fauna. Then, with the invention of fire around 60,000 years ago, everything changed.

A four-sided tetrahedron - The elemental symbol for fire
A four-sided tetrahedron - The elemental symbol for fire

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.

Is Nuon right for you? Let’s talk! Get in touch now to find out more about how our AI insurance products can benefit your business.
AI being used to assess accident damage
AI being used to assess accident damage / v7labs.com

How is AI changing insurance?

Tried and tested is always the best method, right? Well, not any longer. Today, agile insurers are turning to AI to gain new customers and grow their businesses. 

Knowledge and certainty create security, which is the backbone of insurance. Yet, the way they’ve been used hasn’t changed in centuries. Well, not until recently when AI began to disrupt classical thinking.

Claims processing is one area where artificial intelligence is making a big difference. By using AI with big data sets, insurers are now able to process claims at incredible speed. 

Let’s look at a comparison to see how the legacy and AI methods differ. 

With motor insurance, the legacy approach involves the tried and tested method of:

  1. Investigation
  2. Loss assessment
  3. Review
  4. Document collection
  5. Loss adjustment
  6. Payment within 30 days

This is a system that works, or at least it did before insurers were able to tap into the power of big data and personalised insurance. By doing that, we can take an agile approach with AI that is far leaner:

  1. Self-assessment via a smartphone app
  2. Big data and AI process the claim and identify risk leakage
  3. Loss assessment takes place in seconds – reducing costs, improving efficiency and boosting client experience
  4. Processing and claims payment can happen within five minutes

That’s a game-changer in terms of process, efficiency and customer satisfaction.

The story so far – how is AI being used in insurance today?

Lemonade was founded in 2015 and valued at $5b in 2021, making it one of the fastest-growing insurance companies ever. They put their growth down to the use of AI.

Policyholder reports a claim via their phone, recording a video to explain what happened. Lemonade then uses AI to analyse the videos for signs of fraud, amongst other data.

Through this approach, AI has helped Lemonade reduce its loss ratio from as high as 368% in Q1 of 2017 to 71% in Q1 of 2021. 

Ageas uses AI to undertake the evaluation of vehicle damage after an accident. They identify what level of damage has occurred and estimate the costs and labour required to repair. 

US insurer Allstate partnered with the Earley Information Science agency to develop a virtual assistant called ABIE. 

ABIE uses natural language processing to process 25,000 inquiries per month, answering common questions from agents.

Cape Analytics harvests satellite image data, runs it through an AI network, and then provides insurance companies with detailed information about homes and properties – construction, land use, size, etc. 

How can agile companies move ahead of legacy competitors?

The simple answer is through more reliable and competitive rates. 

The combination of AI and big data is a potent one as it allows for hyper-personalisation where policies no longer need to be generic. They can now be suited to an individual’s personal history and track record.

“In contrast to traditional insurance companies, which have been data-rich but have customarily relied on actuarial approaches, startup competitors like Lemonade and Traffk are employing machine learning analytics and drawing upon thousands of data elements to provide personalized analysis and drive insurance purchases.” – Randy Bean, author of Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI

How AI can help financial modelling?

We’re living through a world of change – and that’s not even taking COVID into consideration… – where the world is going to look very different quite soon.

Take the motor insurance sector as an example. A 2015 KPMG report predicts a shrink of 60% in the sector when driverless cars become the norm. That’s a massive hit for your bottom line to take. 

And let’s not forget, motor makes up more than 40% of the insurance industry as a whole.

As Mike LaRocca – CEO of State Auto Financial – said, “The power of change is coming, and if we fail to see it, we could be dead too.”

However, through AI, motor insurance’s loss ratio will drop sharply with risk concentrated on the AI algorithm and other aspects, such as IoT – Internet of Things – and other hardware.

“Technologies will drive industry transformation and upgrading, which will reconstruct existing insurance processes. It will also optimise and innovate products to provide a better service experience.” – Zhu You Gang, senior vice president of Ping An Property & Casualty Insurance.

SOURCES
1 / Technology vision for Insurance 2020 / accenture.com
2 / 2021 insurance outlook / deloitte.com
3 / Artificial intelligence in business / mckinsey.com
4 / Rewriting the rules: Digital and AI-powered underwriting in life insurance / mckinsey.com
Is Nuon right for you? Let’s talk! Get in touch now to find out more about how our AI insurance products can benefit your business.

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