Lifting the lid on personalised pricing

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Improving health outcomes

Lifting the lid on personalised pricing

While health insurance pricing is bound by Australia’s community rating system, insurers may tailor packages to individuals, or even use analytics to improve their health.

HCF’s My Health Guardian program is one example. The program is linked with health insurance claims and membership data to identify and proactively advise members of risk of hospitalisation.

HCF chief information officer Patrick Shearman told iTnews in December that My Health significantly reduced the number of members requiring hospitalisation.

My Health Guardian has about 22,000 users and targets issues such as weight loss, smoking, blood pressure and cholesterol.

Bansal said overseas insurers had implemented similar technologies, citing one income protection insurance provider that had reduced the occurrence of depression among injured white-collar workers.

“We took unstructured content and claims information from their call centre logs and claims... and we were able to understand and predict that a white collar worker with a back injury has a very high propensity, six months down the track, to be depressed.

“By analysing the data you can say, ‘you know what, I need to find those correlations so I can intervene earlier to prevent that happening’, so you’re not only preventing [cost] for the organisation, but you’re also giving good service to the customer.”

Another US insurer discovered that customers in the nursing profession had the highest propensity of breast cancer-related claims.

As a consequence, that insurer began proactively educating customers in that demographic of breast cancer and the trend it had detected, Bansal said.

The data debate

But aside from the handful of industry standouts, most organisations appear to be in the early stages of big data analytics, with many still struggling to pull together information silos.

Suncorp has moved to decommission its six enterprise data warehouses in favour of a platform that scrapes data from various backend systems and allows it to be analysed.

“I think one of the challenges most banks face is thinking about analytics and information management as very closely related but different aspects,” said IBM Global Business Services partner and financial services sector leader Kevin Jury.

“Whilst you can drive analytics in a big way and do lots of interesting things, it really requires a key ingredient: the data.”

“I think it’s going to be a journey of ‘grow the information management platform’,” Jury said.

“[Businesses will] put the data on the launchpad, do some analytics work … and as more devices get deployed out there, be they sensors or whatever they are, you’ll see more analytics stringing together that sensor data, coupled with mobile data. Then, once again, you’ll end up with a cycle of getting more data up on the launchpad, to do more analytics.”

Last July, iTnews reported that Australian banks were lagging behind their international counterparts in using social media outside of the usual communications and customer support areas.

Ultimately, Gilbert and Tobin’s Leonard suggested that public sentiment would hold the most sway over businesses’ use of data.

He called for an “open and informed public debate” on big data that would raise not only regulatory boundaries but also the risks and benefits to society.

“When you actually look at some of the positive applications of big data today, they are truly amazing, and yet the dark side of big data is also undeniable,” he said.

“I advise people that there are two things that you always need to consider with big data: whether you can do it and whether you should do it. In the second consideration, you apply amongst other things the ‘spookiness’ factor.

“Usually the issue stopping what you might do is concern that the individual might regard that as an unreasonable intrusion upon their privacy.

“I think most banks and insurers are very conscious of their public perception and reputation and are conscious that if they use big data to its fullest, it may lead to results that are not acceptable to consumers and will lead to regulation.”

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