How AI is disrupting insurance

Artificial intelligence is breaking down insurance into its fundamental building blocks – data – and helping design products and experiences which are faster, smarter and better for both customers and providers. 

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There’s a saying which goes something along the lines of ‘if you do what you’ve always done, you’ll get what you’ve always gotten’. The insurance sector is acutely aware of the disruptive nature of technology and the affect it is having in other areas of financial services.  

"[AI is] helping design products and experiences which are faster, smarter and better for both customers and providers.”

For insurance it is truly a win-win situation. The right kind of application of these technologies can help customers enjoy more-personalised, efficient service – including fewer questions, forms and time spent applying for cover – alongside improved quality assurance.

On the provider side, the advanced analytics allow efficiency in underwriting with improved completion rates – without compromising the integrity of the insurance risk book.

My colleague Alexis George has written before about Moore’s Law and how the rate of technological change on all areas of business will continue to be felt.

Advances in the sector are increasingly showing the period of unprecedented innovation and change George wrote about in 2016 is finally here.

Change a thing

In my 25 years of underwriting the way things are done haven’t really changed much.

As a sector, insurance has historically not been fantastic at the deep kind of data analytics we now see from machine learning. Give or take a few key terms, we are still asking all the same questions to clients we were from over two decades ago.

Recent years have seen an odd contradiction arise in insurance; while leaders in the industry know they must move to embrace AI but have been hesitant to heavily commit to – and therefore invest in – such systems.

An IBM survey of insurance executives from 2017 found almost all – 98 per cent – said AI would play a “disruptive” role in the industry. Almost as many – 85 per cent – said it would be critical to their business’ future and 96 per cent planned to invest in “cognitive capabilities”.

When the rubber hits the road however the story changes. A 2018 O’Rielly report suggests just 1.33 per cent of companies in the sector were actively investing in AI – compared to some 30 per cent in information technology services.

Things are changing. There have been some high-profile cases of AI application and recognition in the sector which have made news around the world, offering a glimpse into how the industry may look in a machine-learning-dominated future.

Famed investor and Berkshire-Hathway CEO Warren Buffett has openly stated he expects the coming wave of autonomous vehicles will affect premiums at his automotive insurance group Geico.

In China, online-only insurance group ZhongAn has spoken of its use of AI when pricing products, underwriting and detecting fraud, among other reasons.

“Machine learning can optimise the quality of customer service, so the development of AI in the insurance industry will certainly be a big trend,” chief operating officer Wayne Xu, told the South China Morning Post.

In the UK, Neos Ventures is an insurance group which is able to offer competitively priced home insurance policies with a catch – it installs smart monitoring devices in your house. The implication being access to the data lowers customer risk profiles and therefore the price of cover. 

Perhaps the quirkiest standout is US group Lapetus Life Event Solutions, an insurer which offers cover based on a selfie alone – yes, a selfie. The company’s software can use the photo to build a basic risk profile based on your face alone – taking into account factors like if you are a smoker, for instance. 

At ANZ, the bank’s OnePath Life Insurance arm has had some early wins in an AI-based collaboration with the University of Technology Sydney. The pilot program has allowed OnePath to slash the time and effort required to deliver what is ultimately a better service for both consumer and provider. 

As a 2017 report from Delliotte into AI states, insurers using AI to optimise existing services and processes are “already yielding tangible benefits”.

We need to go deeper

ANZ’s groundbreaking work with UTS is designed to provide insight into how AI and machine learning models can lead to improvement in the process of underwriting.

Through work with UTS Advanced Analytics Institute (AAi), OnePath is exploring how modelling customer behaviour through machine learning, data science and probability can help add value and reduce time taken to secure a policy.

Previously, customers would receive a  quote and were then invited to complete their medical history and a lengthy questionnaire. Only following this process -and potentially up to a month later - would they obtain confirmation, or – in the worst-case scenario – news they could not be covered at all.

In late 2017, a group of tradies in Victoria was invited to participate in a pilot testing this new predictive underwriting capability, which draws on big data and artificial intelligence to make the process faster, easier and more accurate.

The pilot was a success and saw a reduction in the application process from 32 questions down to seven questions.  

The improvement in customer experience has been remarkable. Thanks to machine learning, all of the questions previously asked – in some cases up to dozens – are now completely superfluous. 


Using ten years of insurance data ANZ and UTS analysis has effectively made connections between customer segments, the questions and answers, and the resulting claims – allowing them to pinpoint correlations between question responses and claims (see below).

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Pic: Staff showcasing the ANZ and UTS program Source: Provided

This has enabled the OnePath team to pick out the most-relevant medical questions in the underwriting process and discard the least relevant, reducing time, paperwork and cost.

AI 101

Artificial intelligence (AI) is a computer algorithm with human decision-making capability. Machine learning, a subset of AI, is the study of algorithms that give computers the ability to analyse business processes.

Not fade away

While this breakthrough in technology is a game-changer for underwriters it is likely artificial intelligence will never replace the underwriters themselves.

By the reckoning of some, up to 800 million individuals could face displacement by automation by 2030.

One Japanese insurer, Fukoku Mutual Life, made waves in early 2017 when it replaced 30 workers with AI software.

Experts are of the strong view this is unlikely to be the norm. As I have said before, the irreplaceable skills of an experienced underwriter will always be worth their weight in gold. Underwriting will always be part art, part science.

Indeed, decision making capacity and authority is difficult for AI to replace. As technologist Francesco Corea told bankingtech, insurance companies “should be ready to engage intelligently with new types of data”. That engagement model needs people to do the engaging.

As George wrote in 2016, keeping pace with the exponential rise of technology requires us to “think exponentially”.

In insurance, this starts with challenging the status quo.  

Peter Tilocca is Chief Underwriter at ANZ’s OnePath insurance business

The views and opinions expressed in this communication are those of the author and may not necessarily state or reflect those of ANZ.

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