Indian IT company Mphasis has entered a strategic partnership with Sixfold, a US and UK-based AI underwriting company, to bolster capabilities in insurance underwriting.
As an implementation partner, Mphasis will integrate Sixfold’s AI platform to assist insurers in accelerating their underwriting processes.
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The platform aims to streamline submission intake and provide underwriters with contextual risk insights to enable quicker and more confident decision-making.
Sixfold’s AI solution, tailored for life and disability, commercial property & casualty and specialty, and reinsurance, is designed to reduce review times by more than 50% and increase gross written premium (GWP) per underwriter by supporting smarter and faster risk selection, while maintaining accuracy.
The collaboration seeks to optimise underwriting processes, improve operational efficiency and promote intelligent decision-making through Sixfold’s advanced AI technology.
Mphasis chief solutions officer Srikumar Ramanathan stated: “By leveraging Sixfold’s AI expertise in combination with expertise from Mphasis.ai and our insurance technology capabilities, we are able to deliver advanced, data-driven automation solutions for global insurers, driving efficiency, accuracy and innovation across the insurance value chain.”
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By GlobalDataSixfold’s platform is already in use by carriers and is designed to integrate into existing workflows.
It also adjusts to the specific risk appetite of each insurer, providing recommendations that adhere to the insurer’s underwriting guidelines.
Sixfold founder and CEO Alex Schmelkin said: “Sixfold was built to solve real problems for underwriters – and to make the entire process better for brokers and customers. That means making implementation simple and fast.
“Mphasis has a great track record of getting technology live inside real-world insurance workflows. With them, insurers can move quickly, see impact fast and do it all without adding extra work to their teams. That is a win for everyone involved.”
Last year, Sixfold raised $15m (£11.07m) in a Series A funding round, using the investment to expand its AI and machine learning engineering team.
