The term Internet of Things (IOT) was coined at around the same time when the number of devices connected to the Internet first exceeded the total world population. The total IOT devices have been projected to balloon to 50 billion by the year 2020, according to an oft-quoted Cisco IBSG white paper, and as many as 200 billion according to a joint study by IDC, Intel and the United Nations.
This is the era of internet-connected cars and smart home devices, and they will only become more advanced and numerous. Naturally, insurance companies are chomping at the bit for more relevant data to refine the assessment of insurance policies for homes, cars, businesses, and health, just to name the most popular coverage types.
Automated and More Accurate Data Collection
Is your car equipped with optional rear airbags? This question sounds like it might yield a lower insurance rate if one were to answer yes very tempting. Sometimes people might not even know for sure if their car came with the option.
Is there a smoke detector in every room? This is another question that a lower insurance rate might be on offer if one answered to the affirmative.
In the near future, once the IOT permeates every facet of life, insurance companies can just retrieve all relevant information from the connected devices. Not only will they get more accurate information, they will also have more data on hand for better analysis.
It’s not just limited to insurance companies. Companies across the spectrum are using IoT to increase efficiency and data collection. For example, Toronto Junk Removal Company, Junk-Hero, attached online-connected devices to each truck to gather advanced analytics to optimize scheduling and number of deliveries / day.
The Treasured Behavioral Data
The additional data would include behavioral patterns that insurance companies could only guess at. For example, most car insurance companies assume young males under the age of 25 to be high risk. But if they can learn actual driving behavioral data from connected devices in the car, such as speeding pattern, braking frequency, seatbelt wearing habit and more, they would be able to replace blanket assumptions with much more accurate risk models.
This is equally applicable to other insurance assessments including home insurance. Knowing the number of smoke detectors in a home is nowhere as potent as knowing that the smoke detectors are actually functional and how often they get triggered. If a kitchen smoke detector went off all the time, itd suggest higher risk of kitchen fire.
Trickle-Down Benefits to Consumers
While the trickle-down economics of federal tax cuts are debated across both sides of the aisle, the trickle-down benefits of insurance risks to consumer costs are a matter of fact. When insurance companies are able to manage their risk more effectively with additional and better data, they will pass on the saving to the consumers who deserve it.
After all, not every 18-year-old boy drives like a madman and not every soccer mom is a model driver. Armed with a new treasure trove of IOT data, insurance companies would likely come up with new insightful risk correlations. For one, itd be interesting to see if driving a car with a dog in the front passenger seat poses higher or lower risk than in the back seat.
The question that arises is: Will smart devices at home or in a car be able to tell if theres a dog on the premise?
While technology companies ponder the endless possibility, the Internet of Things is set to revolutionize the insurance industry.