In the well-oiled freight machinery, the insurance vertical is a vital cog, helping keep the ecosystem running without any major hiccups along the road. Within freight insurance, there has been a consistent push towards better understanding the risks that fleets are insured against, because accuracy in predicting risks maximizes profit margins.
This has not always been easy; within the insurance landscape there are several stakeholders involved – like shippers, brokers and carriers, with every party driven by its own interests concerning insurance claims. “There’s a bit of a spectrum in terms of the relationship between liability for the freight hauling journey versus actual property – the goods that are being shipped and handed from one party to another,” said Dale Willis, the vice president of data services and insurance at Netradyne, a computer vision startup.
Willis explained that technology can be of use in this regard, as it can help insurance companies phase out “100-year-old proxies” for measuring and quantifying risk, and adopting processes that use available data streams to predict and zero-in on potential risk.
“Ten years ago, we had a broad rollout of GPS tracking in fleets, which is great for efficiency because it helps locate assets and in route management functions. The GPS data stream eliminates the need for the insurance agencies to ask fleets how many miles they drive every year or run an audit to verify their claims,” said Willis.
“GPS data allows companies to watch the trucks move around the grid in real-time and understand data at a more granular level than just counting the number of miles a truck drives. Data can help companies identify where fleets are being driven, when they’re being driven and how they’re being driven,” he continued.
Nonetheless, the freight industry does pose a challenge to the insurance sector, as the market is full of companies that are many decades old, using green screen technology and generally unwilling to adapt to modern technology. Willis, however, was optimistic in pointing out the new rich data sources that are bringing innovators to the space, which will eventually make the industry more flexible and dynamic.
Within the insurance sector, there has been a game theory-like opportunity that indirectly pits insurance companies against each other, as they play cat-and-mouse by capturing the least possible risk at great liability cover prices, while pushing out high-risk opportunities hoping the competition takes the bait.
Willis mentioned that the electronic logging device (ELD) mandate was a turning point in the way the freight industry looked at data utility. “Many carriers are absorbing the fact that data from their ELDs can be used to improve their efficiency. For insurance companies, something as basic as mileage verification can now be done easily, helping them decide their exposure for specific fleets,” he said.
Once the data streams are in order, the incoming data will have to be analyzed to gain insights. Several applications with artificial intelligence models at their core can help insurance companies glean information on operational processes, driver behavior, fuel efficiency and the like. This helps insurance firms to be proactive on their liability covers, and intervene before there is a need for a claim via in-time alerts and effective tools that train truckers to be better drivers and ultimately avoid accidents.
“The future is not just about measuring risk, but trying to diminish risk by intervening proactively,” said Willis. “This is interesting, because the field is just budding right now, and most of the beneficiaries in the short-term will be the insurance companies. Four years ago, we saw technology’s emergence within personalized vehicle insurance, and I think we will see the same play out with commercial insurance.”