What is your "Vitality Age" and how will it impact on your Life Insurance policy?

Hold on to your hats (and your insurance policies), the insurance business is about to get a whole lot more interesting.

Research released this week by the Actuaries Institute has found that there has been more gathering of data on people in the past two years than at any other time in human history…think about that!

The ground-breaking research on big data and its impact on the insurance industry looks at how the use of this data will irrevocably change the industry, and covers car, health, life, home and contents.

Insurers are testing an intensely personal new use for the vast dossiers of data being amassed about Australians enabling them to predict people's longevity.

Insurers have long used blood and urine tests to assess people's health—a costly process. Today, however, data-gathering companies have such extensive files on most consumers—online shopping details, magazine subscriptions, leisure activities and information from social-networking sites—that some insurers are exploring whether data can reveal nearly as much about a person as a lab analysis of their bodily fluids.

This data increasingly is gathered online, often with consumers only vaguely aware that separate bits of information about them are being collected and collated in ways that can be surprisingly revealing. The Productivity Commission recently published a 500 page draft report on data availability and use that favoured individuals having more control over how their personal data was used and how they could access and control it and has called for more consultation on this issue.

Making the approach feasible is a trove of new information being assembled by giant data-collection firms. These companies sort details of online and offline purchases to help categorize people as runners, dieters or couch potatoes. But using this information in the life insurance application process would open a can of worms.

Let’s use the example of imaginary 40-year-old insurance buyers, "Beth" and "Sarah."

Using readily available data, an insurer could learn that Beth commutes some 45km to work, frequently buys fast food, walks for exercise, watches a lot of television, buys weight-loss equipment and has "foreclosure/bankruptcy indicators."

"Sarah," on the other hand, commutes just a kilmotre to work, runs, bikes, plays tennis and does aerobics. She eats healthy food, watches little TV and travels abroad. She is an "urban single" with a premium credit card and "good financial indicators."

Sarah appears to fall into a healthier risk category. Beth seems to be a candidate for a group with worse-than-average predicted mortality. The top five reasons: "Long commute. Poor financial indicators. Purchases tied to obesity indicators. Lack of exercise. High television consumption indicators."

Another example would be a life insurer might wanting to scrutinize an applicant who reports no family history of cancer, but indicates online an affinity with a cancer-research.

Whether you realize it or not, you may be significantly increasing your personal transparency, as all this information is in the public space and electronically mineable."

A key issue is whether society wants individuals to pay a price for insurance that reflects their risk or should everyone have access to affordable insurance regardless of the risk?

There are also questions around privacy issues, who owns the information, what personal data might be used for and to whom it may be passed 

Some examples of how insurers worldwide are using data 

►     In Australia, MLC ‘s Basis Peak smartwatch is being offered in conjunction with its On Track program to help policyholders save on their life insurance if they get enough exercise and sleep.

►     South African insurer Discovery uses a range of data and health information to determine a policyholder’s “vitality age”, which is an indicator of overall health that may be higher or lower than their actual age, and which can improve over time as the policyholder works towards living a healthier life.  

►     Discovery’s motor insurance division collects data on drivers through a telematics device and rewards good behaviour for drivers by granting points for braking and speeding habits; no mobile phone use, car service history, tyre checks, etc. Those points can be redeemed for fuel, Uber discounts and free coffees and smoothies. 

►         As self-driving cars become a reality, insurance may indeed shift from insuring the driver at all (based on their behaviour) to product liability insurance for the car manufacturer. 

►     Nest, a business owned by Google, has a number of connected home products, such as programmable security systems, smoke and carbon monoxide detectors. It has partnered with American Family Insurance, and Liberty Mutual Insurance. The insurer subsidises the cost of the smoke detector, with the product then sharing data with the insurance firm so it knows the insured’s house has working smoke detectors.