How Location Data Could Result in More Accurate Premiums

For insurers writing policies, it is essential to accurately price risk. Location data is one of the most important types of data used to calculate premiums, especially for home and car policies, where factors like crime rates and nearby threats are key.

Location data could help make premiums more accurate.

The more accurate an insurer’s risk assessment, the more accurate your policy. In some cases, this could mean a reduction in premium, for others this could mean spotting a risk which was previously overlooked.

What is ‘location data’?

‘Location data’ refers to electronic information about location, defined by the Information Commissioner’s Office (ICO) as ‘information collected by a network or service about where the user’s phone or other device is or was located’.

As a consumer, you may be familiar with location services on your mobile phone. Location data has grown to become almost ubiquitous across modern technology, from getting directions across town to ordering a cab. You have to give consent to every individual app or website which asks to access them, as location data is collected by a network or service and, understandably, there are tight security controls surrounding it.

However, data can also be GPS-based, created outside of phone networks by smartphones, tablets or sat-navs, or collected at a local level for example by home or business wi-fi equipment. This is less regulated.

What does it have to do with insurance?

Technology-driven location data can provide more than just a dropped pin on a map.

For insurers, it could also give context. Think average house values, the distance of a building from coastlines or rivers, nearby business competitors, vehicle density of an area and relevant crime statistics.

Studies conducted by Perr & Knight for Pitney Bowes found that around 5% of homeowner policies and as many as 10% auto policies in America could be priced incorrectly because of unspecific location data.

Forbes contributor Hugo Moreno notes: “In many cases, the gap between the estimated and actual location is small enough to be insignificant, but where it’s not, there’s room for error—and that error can be costly.”

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