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A Swyfft $7.5M investment into big data aims to demystify home insurance

 

When it comes to home insurance, outdated pricing methodologies and a lack of insight lead to inaccurate pricing that require a big data solution.

Homeowners typically spend at least $1,000 a year to secure homeowner insurance cover, according to ValuePenguin’s 2016 analysis. Weather is the leading cause of damage to a home, and disasters like hurricanes and fire cause the highest costs.

As an example, the residents of Florida can expect to pay almost double the national average, due to the high hurricane risk. However, these risk estimations are often incorrect.

To counter and improve upon this, intelligent home insurance enterprise Swyfft has just raised $7.5 million in Series A funding to develop a unique algorithm-driven platform that uncovers premium policies.

With this latest round of funding, Swyfft is going up against the insurance giants of the world — the likes of GEICO, Esurance, Progressive and more. In this established market, the platform differentiates itself not only with big data and intelligent policies, but also through the speed of response.

“Big data and AI tools let us uncover better insights from the past to help predict the future,” said co-founder Sean Maher. “We’re thrilled to secure this finance that will help us to develop new patented-technology, protecting our customers while also reducing their costs.”

The company’s web app is powered by a complex analytics engine that incorporates 3D modeling, machine learning and millions of unique data points that uses big data to provide a truer assessment of the risks to a home, giving potential customers a quote in less than five seconds.

Complex LiDAR data and 3D modeling help Swyfft to map and predict wind patterns and nearby dangers, through understanding the building’s surroundings. In this way, the company’s patented algorithms surface more accurate and often less expensive quotes by bringing the power of AI directly to the consumer.

This article was originally published sociable.co and can be viewed in full

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