Whenever you say the word “telematics”, people today almost always assume you are talking about motor insurance. Well, it is the only use-case where telematic data is being used for insurance purposes, right? Wrong.
There are plenty of other types of insurance where telematic data is available to help manage and reduce risk and even some where enlightened insurers will give you a discount based on sharing that data. And wherever you find that fire hydrant of telematic data cracked open, you will find a Big Data platform soaking it up and converting it into actionable insights for the insurer and hopefully the customer too.
The connected home
Insurers already know the benefits of monitoring the data from smoke detectors and similar devices, they just need their customers to realise the same and install these devices.
As far back as 2013, State Farm introduced a programme for homeowners and renters centered on home protection and security called “Home Alert”. In this programme, the insurer provides access to approved equipment such as smoke detectors and security alarms at a discount, subsidises the installation and monitoring service and also gives premium discounts of up to 10% based on the these devices being present in the home. State Farm cited the average home fire claim costing over US$34,000, the average water leak claim at over $8,000, and the average crime claim at close to $3,000; so it is in the customer’s and carrier’s interest that these early warning measures are in place to avoid these kinds of claim.
Recently, two other insurers, American Family and Liberty Mutual, teamed up with Nest to take this model to the next level through the “Nest Safety Rewards” programme. In this programme, data showing status of the smart home system is shared once a month with the insurers. To qualify for a free device and insurance discounts of up to 5%, the data needs to show that the system is healthy and protecting the property. The carriers cited statistics that show a significant number of house fires occur, where protection devices are installed but are not working.
The data ecosystem
Insurers going down this track already know there is an ecosystem at work here, consisting of device manufacturers, installers, monitoring service providers, cloud platforms, telcos, etc. Insurance, then, is just one part of the value equation, but one that can really help make the market. Several insurers have launched venture capital vehicles aimed at harnessing the potential industry disruption these ecosystems represent.
For example, American Family has set up American Family Ventures, which boasts an impressive array of 15 companies for which it has provided seed funding of between $500,000 to $2,000,000 each. All of these companies are focused on areas that could impact the insurance industry.
One of their smart home investments is in a company called SNUPI Technologies, which makes ultra-low power devices to monitor the home. SNUPI essentially turns a home’s existing electrical wiring into an antenna which allows the sensors to operate for decades on a single battery, making it a very low cost and durable way to detect water leaks and track humidity associated with mould.
Another interesting approach to making the home smarter was launched by start-up, Neurio. They use a combination of telematic data and Big Data pattern recognition in their solution. The low cost power sensor attaches to the home’s electricity mains and transmits utilisation patterns back via the cloud, to Neurio where they can automatically identify, through the use of data crowd-sourced from their customer base, the signatures of house-hold items such as microwave ovens, kettles, blenders, washers, driers, hair driers and game consoles, etc. It is extremely useful for analysing power consumption and helping customers reduce their electricity usage. It is not yet on any insurers’ ecosystem list, but it could easily be used to determine if and when the home is being occupied which is important to know where rates differ based on the home being a primary or secondary residence.
So from these smart devices in the home, we move on to the use of smart devices and big data on the farm.
The connected crop
Savvy farmers have been clued into data from their crops since the mid 1980’s through the use of satellite imagery for soil, crop and pest management. In 2013, Monsanto acquired the Climate Corporation, a start-up founded by two Google alumni to use weather and soil data to create insurance plans for farmers and generate recommendations for which crop varieties would be best suited to a particular plot of land.
A recent development, as part of the movement to precision agriculture, has been the use of drones to gather data, so that farmers are aware of what’s going on in their fields in near real-time irrespective of weather conditions. By using Near Infrared imagery and Normalized Difference Vegetative Index (NDVI) sensing from the drone platform, farmers are able to quickly identify problem areas within their crops and take corrective action before the problem becomes a claim. In one 2014 study, it was shown that these techniques could identify the precise location of early emergent weed growth down to a couple of centimetres in diameter.
A number of providers of Big Data services for crops have started up over the last few years. For example, Agibotix has a service where farmers can upload their GPS tagged crop images while the service will stitch the images together to get a complete overview of the crop and provide the analysis of the data gleaned from the images to give farmers actionable insights. The service can also provide the drone platform at a discount when bundling the data processing services.
By using the insights from the data and applying precision farming techniques, farmers have been able to increase crop yields significantly while at the same time reducing input costs on fertilisers, pesticides and labour.
While I am not aware of any agricultural insurance programme presently offering discounts for running programmes like these, it must only be a matter of time, since many of the risks are being managed through the use of data-intensive precision farming techniques.
So from precision farming, we move into the realm of the quantified self.
Wearables for life
Vitality of South Africa has recognised the importance of holistic health and wellness programmes for over 15 years and has built up an impressive array of statistics, including:
• Participation in health and fitness programmes reduces health claims by 16%;
• Logging fitness activities reduces risk by 22% for the most unhealthiest category of participants;
• Participating members are up to 64% less likely to lapse their insurance than non-participants; and
• Participating members have up to 53% lower mortality rate than non-participants.
John Hancock in the United States is one of the latest to license Vitality. Their programme has made it even easier for customers to get onboard, by offering a free fitness tracking device and providing more options for automatically synchronising fitness and health related data. Additionally they were one of the first carriers to support Apple’s Health Kit and the Apple Watch for data collection.
The package of incentives John Hancock has set up to reward their members’ data sharing includes: discounts on an array of attractive goods and services; and Life insurance premium discounts of 5% to 15%, depending on the vitality fitness level achieved. Over the policy period, these premium discounts could amount to as much as $36,000 if the top vitality fitness level is maintained continuously.
So we have touched on the use of wearable technology for humans, so what about wearables for livestock?
The connected cow?
It turns out someone has thought of it already. There is currently a research programme in progress in Europe using GPS collars for dairy cows. The aim is to improve the milk production yield at reduced cost. It has a number of clever features.
Currently the livestock behaviour and location are being tracked in response to virtual electric fencing. The GPS collar makes the cow aware when it is close to the virtual electric fence. As the animal encroaches further into the virtually fenced-off area, the negative feed-back is increased via the GPS collar.
Now those of you who may be concerned about animal cruelty, since 2008, there has been an ongoing research programme in Texas studying virtual fencing and the effective stimuli for positive and negative “feed-back” for cows. It turns out that sound has proven to be the most effective motivation for cows, so it may be the song the farmer sings during milking that is playing to move the cow away from the virtual fence.
The European team’s concept, is to take the herd’s position and combine that with pasture “lushness” data (similar to the crop data I mentioned above) and use virtual electric fences to move the herd around so it can graze on the lushest parts of the field. By continually monitoring the “lushness” and moving the virtual electric fence it is hoped that the whole pasture will be evenly grazed and the cows optimally fed.
One insurance use for this technology, relates to real-time monitoring of the health of the herd. When a potentially sick cow is identified, then the virtual electric fence can automatically separate and quarantine the sick individual away from the rest of the herd, thus reducing the chance of widespread infection.
The bottom line
As new sources of data about the people and things we are insuring become available, we gain new opportunities to identify and manage risk.
In many cases, we can incentivise customers to play an active part by sharing data and, based on the insights from that data, modify their behaviour to reduce risk. It is a fantastic model for the insurance industry, one that offers greater transparency and value for all stakeholders.
Uh oh, my home system is telling me I am out of milk - time to move the virtual electric fence. See you next time.
Mr Andrew Dart is an Industry Strategist at CSC.