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Admiral to analyse Facebook posts to price car insurance premiums

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Update: Admiral have now been force to cancel their plans to launch the firstcarquote program after Facebook blocked them from using personal data.

Facebook announced that protecting the privacy of its users was of the utmost importance and that it had clear guidelines about how information obtained from the social network should be used.

Facebook’s privacy policy states that the site’s data should not be used to “make decisions about eligibility, including whether to approve or reject an application or how much interest to charge on a loan”.

The privacy campaign group Open Rights Group, welcomed Facebook’s decision and labelled Admiral’s proposed scheme “intrusive”. Admiral is understood to be in talks with Facebook about trying to rescue firstcarquote.

Admiral, one of the biggest insurance companies in the UK, is to start analysing car owners’ personalities using social media data in order to price their car insurance.

The move highlights the beginning of a new era for how insurance companies use publicly available information across social media, and will no doubt lead to a debate about privacy.

Admiral will begin the scheme by reviewing the Facebook accounts of first-time car owners and looking for personality traits that are linked to safe driving. For example, the algorithm will scan for signals indicating an individual is conscientious and well-organised.

The process will look at Facebook posts and ‘likes’ – although not a users photos – and reward users who display the habits that research has shown are linked to these traits, such as writing in short sentences, using lists, arranging to meet friends at a set time and place and so on.

If you want to avoid the algorithm punishing you with higher prices, then you may want to avoid using exclamation marks as well as the frequent use of words like “always” and “never” rather than “maybe”.

Admiral’s scheme is called ‘firstcarquote’ and is aimed at first-time drivers – although anyone with a licence can apply. The initiative will be voluntary at first, and will only offer discounts to ‘conscientious’ individuals rather than premium increases.

As well as the rise of black box and telematic technology, the rapid growth of social media as well as personal technology has given insurance companies a huge amount of data on customers. As well as Admiral’s firstcarquote scheme, insurers are currently looking at using technology like smartwatches and fitness trackers to monitor the behaviour and health of customers.

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Life insurer Vitality, for instance, is currently selling the Apple Watch to life insurance customers to monitor how much exercise they do – with the life insurance premiums dependent on how healthy their lifestyle is.

Admiral says that the firstcarquote system provides a way for young drivers to show that they are safe before building up years of no-claims bonus. With the cost of new and young driver car insurance being a big barrier to new customers, this could be a useful way of making it more affordable.

Admiral’s Dan Mines, who led the development of the firstcarquote scheme, denied accusations that it is invasive of a customers privacy. He said: “It is incredibly transparent. If you don’t want to use it in a quote then you don’t have to. We are doing our best to build a product that allows young people to identify themselves as safe drivers.”

“This is very much a test product for us. This is innovative, it is the first time anyone has done this. It is a test, this is early days. The data will only ever provide a discount. We will work through that and learn more.

“I think the future is unknown. We don’t know if people are prepared to share their data. If we find people aren’t sharing their data, then we won’t ever get to consider that [expanding firstcarquote].”

Regarding how Admiral’s algorithms work, their principal data scientist Yossi Borenstein said: “Just like conscientiousness there are other traits which can be indicative of safe driving. Our algorithm for calculating what ‘safe’ looks like is constantly learning, as we match social data to actual claims data.

“Our analysis is not based on any one specific model, but rather on thousands of different combinations of likes, words and phrases and is constantly changing with new evidence that we obtain from the data. As such our calculations reflect how drivers generally behave on social media, and how predictive that is, as opposed to fixed assumptions about what a safe driver may look like.”

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