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The UK insurance industry is making big data a strategic priority in 2016.
Research commissioned from censuswide by data warehousing company Teradata has found that 82% of UK insurance companies with more than £500m turnover are prioritising big data strategies in 2016.
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The survey polled 300 senior decision makers from the insurance industry, split evenly between the UK, France and Germany.
In the UK, 42 respondents were from companies with turnover between £50m and £500m and 22 from companies with turnover of £500m or more.
Among the smaller UK-based firms, a minority of 46% are making big data a priority.
Some 73% of the larger firms are using big data to increase premiums by tackling underwriting fraud.
Large French and German firms are ahead of the UK when it comes to what the survey calls "full deployment of customer data". On average, 76% of the French and Germans do this, while 63% of the British do.
The survey also looked at internet of things (IoT) data. Here, the British were ahead in their use of IoT data, such as telematics in car insurance. Three quarters of UK insurers pronounced themselves “very well equipped” to exploit this.
Lesley Winrow, head of insurance, Teradata UK and Ireland said: “It is reassuring to see that UK insurers have grasped just how crucial IoT data will be. However, it is time for smaller UK firms to follow suit. As insurers develop their big data projects, they will understand how they can use insights to differentiate themselves from the competition on more than just pricing”.
“Insurers who don’t have an advanced big data strategy are depriving themselves of the significant revenue-boosting capability to make far more personalised offers that will be more engaging and compelling to individual consumers.”
Read more about big data in insurance
- Ordnance Survey opinion: Harnessing the power of big data presents insurers with a business opportunity. But is this industry ready for it?
- Most insurance companies do not have big data strategies despite the industry's reliance on access to accurate data.
- Commercial insurance companies lose billions each year to fraud, but there is a major opportunity to use analytics tools to stop this haemorrhage.
Risk and privacy
At a Teradata organised discussion event held in the City of London, to coincide with the publication of the research, David Thomson, director of policy and public affairs at the Chartered Insurance Institute, cautioned against too great an embrace of the trend towards personalised offers in insurance: “Part of the genius of insurance is that it is based on pooled risk. That has been its social value.
"There is a danger of sleepwalking away from that into individual pricing.”
At the same event, Renate Samson, chief executive of civil liberties pressure group Big Brother Watch said: “Personalisation is slightly horrifying, and won’t be allowed under the terms of the EU’s GDPR [General Data Privacy Regulation]. You will not be allowed to analyse, profile or predict on the basis of behaviour, attitudes or preferences.
"And people feel creeped out having their social media activity or web browsing watched. If an insurance or other financial services company comes to me offering a service and I realise they’ve been looking at my Facebook or Twitter, they will come a cropper. If you think that personalisation is the key, run the other way.”
Stephen Brobst, chief technnology officer at Teradata, had a more positive take on using big data to deliver more personalised insurance: “As long as companies say what they do and do what they say, that is key. If I allow, as a consumer, an automotive insurance company to collect the data on my driving habits that allows them to see I am a better driver than the rest. The first car that I ever owned cost less than it did to insure it for a year.
"It is outrageously stupid to be put in the same risk pool as bad drivers.
“The same thing applies to healthcare. If you smoke and I don’t smoke, I don’t see why I should pay the same premium as you. Smoking is ultimately under my control. I shouldn’t subsidise the bad habits of others.
“Anonymised data can be used very well by actuaries to understand risk.”