Verikai, which leverages data and machine learning to change how insurers perceive risk, has collected $6m in its Series A round.
The round was led by Iowa-based venture capital firm ManchesterStory. Additional contributions to the round came from early-stage venture firm ValueStream Ventures and startup accelerator Plug N Play.
With the close of the investment, the company will build out its corporate structure, with a key focus on expanding their sales and marketing efforts.
Prior to this round, the InsurTech closed a seed round in 2018 for an undisclosed amount. The capital was supplied by Aioi Nissay Dowa Insurance Company Limited and National General Insurance.
Verikai co-founder and CEO Hari Sundram said, “The strong interest from the VC community signals a realization that differentiated underwriting and applied data are now necessities for insurers seeking profitable new premium.
“This funding will allow us to build out a marketplace infrastructure where risk and rate can be fundamentally aligned between distributors and carriers. Ultimately, this alignment allows employers and individuals with positive behavioural attributes to receive the rate relief they deserve.”
The InsurTech company offers a data platform, with the hopes of closing the gaps between underwriting and actuarial processes. Its data analysis and insight are directly served via a real-time API into the underwriting workflow.
Founded in 2018, the company has a database made up of over 4,000 behavioural attributes, 260 million people across the US and is modelled on over 25 million unique claimants. This helps firms to better underwrite risks.
ManchesterStory co-founder and managing partner Matt Kinley said,. “Verikai leverages alternative data on individual behaviours, along with the largest set of carrier-informed underwriting outcomes, then calibrates and trains it with their machine learning-informed modelling to create an ultra-accurate prediction of future claims
“InsurTech is our core focus, and we are excited to back a company with such a strong product-market fit.”
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