The startup will use the funds to hire more than 50 engineers, data scientists, business development, insurance and compliance specialists, as well as scale into new industry verticals and across into Europe.
Since its founding in 2018, DigiSure has built a business around using AI and machine learning to manage big data in real time in order to provide a nuanced risk assessment and more fairly priced liability insurance for individuals renting vehicles. DigiSure has a total of 12 clients, including motorcycle rental company EagleRider, EV rental company Envoy and truck rental company Fetch. DigiSure says it goes beyond credit and driving history to give users a more personalized quote, and in the process helps operators lower their own insurance costs.
“With our DigiSure Protection Suite, we screen all the people who are looking to rent and operate vehicles, we prevent bad actors from getting on these vehicles that might harm other people and then we provide insurance to the operator, as well as to the individual renters,” Mike Shim, DigiSure’s co-founder and CEO, told TechCrunch.
Property and casualty insurance, which is usually one of an operator’s top operational costs, is nearly a $700 billion industry in the U.S., and Shim thinks that’s in large part because of outdated screening methods that result in bad actors slipping through the cracks and causing damage. Traditional auto insurance carriers typically provide a quote by comparing statistical averages to information like a user’s age, gender, education level, location, driving record, credit history, vehicle details and location, but in the vehicle rental space, Shim says underwriting is limited or non-existent.
“There is therefore a huge opportunity to improve the quality of the risk management by using more sophisticated pricing models that lead to better conversions and lower losses overall,” he said.
DigiSure’s Protection Suite uses traditional underwriting factors, as well, but also utilizes the renter’s transaction history alongside external data sources that a normal insurance company wouldn’t have access to. According to a statement from the company, the Protection Suite includes “AI-powered identity verification utilizing biometrics technology, advanced fraud detection, credit checks, driving history and telematics data integration.”
It then plugs the data into its proprietary machine learning algorithms to get better at providing real-time insurance quotes over time, says Shim. For example, DigiSure’s data science team might find that the ratio of rider height to seat height of a motorcycle is an important risk factor in predicting low-speed tip overs and then recommend improvements to the model.
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The startup will use the funds to hire more than 50 engineers, data scientists, business development, insurance and compliance specialists, as well as scale into new industry verticals and across into Europe.
Since its founding in 2018, DigiSure has built a business around using AI and machine learning to manage big data in real time in order to provide a nuanced risk assessment and more fairly priced liability insurance for individuals renting vehicles. DigiSure has a total of 12 clients, including motorcycle rental company EagleRider, EV rental company Envoy and truck rental company Fetch. DigiSure says it goes beyond credit and driving history to give users a more personalized quote, and in the process helps operators lower their own insurance costs.
“With our DigiSure Protection Suite, we screen all the people who are looking to rent and operate vehicles, we prevent bad actors from getting on these vehicles that might harm other people and then we provide insurance to the operator, as well as to the individual renters,” Mike Shim, DigiSure’s co-founder and CEO, told TechCrunch.
Property and casualty insurance, which is usually one of an operator’s top operational costs, is nearly a $700 billion industry in the U.S., and Shim thinks that’s in large part because of outdated screening methods that result in bad actors slipping through the cracks and causing damage. Traditional auto insurance carriers typically provide a quote by comparing statistical averages to information like a user’s age, gender, education level, location, driving record, credit history, vehicle details and location, but in the vehicle rental space, Shim says underwriting is limited or non-existent.
“There is therefore a huge opportunity to improve the quality of the risk management by using more sophisticated pricing models that lead to better conversions and lower losses overall,” he said.
DigiSure’s Protection Suite uses traditional underwriting factors, as well, but also utilizes the renter’s transaction history alongside external data sources that a normal insurance company wouldn’t have access to. According to a statement from the company, the Protection Suite includes “AI-powered identity verification utilizing biometrics technology, advanced fraud detection, credit checks, driving history and telematics data integration.”
It then plugs the data into its proprietary machine learning algorithms to get better at providing real-time insurance quotes over time, says Shim. For example, DigiSure’s data science team might find that the ratio of rider height to seat height of a motorcycle is an important risk factor in predicting low-speed tip overs and then recommend improvements to the model.
“We’re basically constructing a composite risk profile on that user and building a profile on that user over time,” said Shim. “Our technology is creating a next generation underwriting model for next generation mobility.”
DigiSure is able to perform screenings and come up with a quote in seven seconds or less, according to Shim. On the user side of things, by the time they’ve begun the checkout process and are ready to finalize a booking of, say, an RV rental, DigiSure is able to offer up a dynamically priced bundled insurance product at the point of sale, making it feel like a real-time process.
DigiSure is still new, so there’s room to grow, says Shim. The traditional world of vehicle insurance is not built for newer mobility models, like peer-to-peer, which is currently DigiSure’s bread and butter, or shared micromobility, which the company sees a lot of potential in.
“The main problem was that insurance companies were just not serving our mobility customers and not able to keep pace with not only all the new business cases but also the fact that consumers are just looking to move and get around in different ways,” said Shim. “We’re basically creating a mobility insurance platform and a risk platform that is trying to get ahead and support these innovators.”
In the case of shared micromobility, where there’s no bundled insurance product offered at checkout, DigiSure would primarily offer its fast screening services to filter out potential loose cannons from hopping on shared scooters or bikes. The operator could then point to this service in order to lower its overall insurance costs, which typically make up a fairly large portion of the operating costs pie in an industry that’s barely been able to make a profit yet.
Presently, DigiSure doesn’t provide any insurance that covers the rider in the event of personal injury, but Shim says that’s standard for the industry. The platform provides property insurance for the operator or the owner of a vehicle on a peer-to-peer marketplace that protects the vehicle itself. It also provides casualty insurance for both the marketplace or operator and the rider or driver, which includes liability coverage to protect those parties if the driver is responsible for an accident that causes injury to another person or damage to another person’s property.
While insurance is certainly on offer here, it’s the screening tech that makes DigiSure’s product unique.
“Our view is it’s better to focus on the screening tech to weed out bad actors and keep the platform safe,” said Shim. “Those 1% to 2% of the customer base are likely the ones who are going to cause 30% to 40% of the worst-case claims costs. If you can control for those outcomes, you can really impact your bottom-line insurance costs.”
This funding round was led by Morado Ventures, with participation from Xplorer Capital, Valor Equity Partners, Clocktower Technology Ventures, True North Cos and ex-Upwork CEO Fabio Rosati.
Source: Tech Crunch
