August 21, 2018 by Staff
More than 80% of U.S. insurance customers are under-served, pay substantial premiums and play by the rules, says Halos Insurance founder & chief executive Satadru Sengupta in a media release.
“This low-risk group has fundamentally different needs compared to the group that submits claims frequently,” says Sengupta.
As a result, Halos Insurance, an insurtech founded in Washington, DC, is building an insurance product designed to serve low-risk and accident-free consumers. “We are using the latest technologies and going back to first principles to design products for low-risk groups and reduce accidents for certain high-risk groups,” notes Sengupta.
According to the Insurance Information Institute (III), between 2010 to 2015, annually, only 6% of insured homes filed claims. This number is similar for auto insurance.
On the other hand, more than 70% of the premium collected is spent on claims and claims-related expenses – up to 15% of which is fraud.
According to the Federal Bureau of Investigation (FBI), insurance fraud costs the average U.S. family between $400 and $700 per year in the form of increased premiums.
Today, once a customer is acquired, almost all monetary and operational resources are spent on claims and claims-related expenses, including fraud, leaving a large segment of consumers questioning the value of insurance.
Prior to founding Halos Insurance, Sengupta built and ran the insurance practice at DataRobot, the pioneer of automated machine learning platform used by thousands of organizations around the globe.
“Satadru comes with a rare background,” says Jeremy Achin, CEO & co-founder of DataRobot. “Satadru’s deep knowledge of AI and machine learning coupled with his extensive experience of insurance operations has prepared him to solve critical problems in the insurance industry.”
Sengupta grew his career as a Data Scientist working at AIG, Liberty Mutual Insurance, and Deloitte Consulting Insurance Practice.
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This story was originally published by Canadian Insurance Top Broker.