WOLT
“ The data we can ’ t see will eventually hurt us ”
GARRETT OLSON HEAD OF INSURANCE & RISK MANAGEMENT , WOLT a much more granular way to provide a more insightful snapshot of real-time risk exposures – to have relevant limits at a city or even courier level while also lowering the cost of premiums in the process .
“ Drawing on that dynamic component allows the insurance companies to really understand risk factors better ,” Olson tells us . Those risk factors could include the weather ; riders are more likely to slip or trip when it ’ s icy , or use a car when it rains .
There are also variations between cities – some , like Copenhagen , feature segregated bike lanes , while others , like Prague , have a lot of narrow and cobblestoned streets .
Other cities feature vast and expansive boulevards . Between cities , delivery vehicles also vary ; there are said to be five times as many bicycles as people in the Danish capital , but they are less popular in car-heavy Baku – the capital of Azerbaijan .
Finally , exposure to risk will be influenced even by the smallest consideration like who exactly the courier is . Experienced , full-time courier partners are – in theory , at least – less likely to experience a serious crash than those who dip in and out of the app on a regular basis , perhaps going weeks or months at a time without fulfilling orders while they work other jobs or study .
“ Those are the things that would be captured if we used dynamic risk data . The brush stroke risk exposure and pricing in reality does not represent the entire spectrum of the risk which leads to overinsuring or under-compensating .”
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