How to Stop Car Theft Using Data
At the end of March, 2019, BBC News reported alarming statistics on car theft in the UK. According to ABI (the Association of British Insurers) a new insurance claim is filed every six minutes in the UK, and the number of insurance claims for car thefts in 2018 is 12% higher than 2017, numbered at 56,000. In fact, the article states, new, keyless cars might be even more at risk for theft. By using technological devices, thieves can simulate key signals, open the car and drive away.
One solution to this conundrum is to stop using technology and roll back to older car door-opening mechanics. Or, this is another alternative: use technology. One that would prompt immediate reaction whenever a car door is being unlocked and the car is being driven away by someone other than the owner.
The technology that enables this is actually connected car data. Connected cars send data attributes during different car “events”. These data attributes include information about door lock and unlock, ignition status and location.
Apps and services can use these data attributes to create alerts about a potential theft. These alerts can be sent to drivers, insurance companies and the police who can then react immediately to halt it.
For example, a driver could get an alert on her or his phone that the car door has just been unlocked, despite the fact that the whole family is sitting in the living room. The driver could then immediately call the police and report the theft, while providing the location of the car as it is being hijacked and taken away. It would be much easier for the police to stop the theft and arrest the perpetrators in this case.
Police forces could also use such a service to track the status of cars in a neighborhood prone to theft. Police could monitor doors being unlocked and engines being turned on within the neighborhood polygon during the hours most car thefts take place, for example between 2:00 AM and 5:00 AM.
To avoid false arrests, when such an event occurs, police could contact the driver through an app to ask if she or he is using the car. Unless driver confirmation is sent back, a police car could then locate the car and stop the robbery. Obviously, this use case requires driver consent for the police to monitor personal information. However, if this technology is used as a temporary measure to reduce crime and protect civilians, it is probable that high percentages of consent will be secured.
For insurance companies, monitoring these alerts and alarming the police could prove to be a more cost-effective way to deal with car theft than paying and dealing with insurance claims. Stopping car theft, even at the cost of running the theft-prevention operation, might be less resource-intensive than operating an insurance claims process.
Because of the multiple uses of this data, such apps can be developed by independent companies who could sell these services, or by the insurance companies and police forces themselves. This data is already available for app development: it is already being gathered by OEMs and then normalized, secured and reshaped by companies like Otonomo, making ready for good use. The need is there, now the service just has to be created.
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