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Envelop Risk Brings Advanced Machine Learning to Cyber Risk With Dataiku

Following on from its $6 million Q2 Series A investment, top global insurtech firm delivers AI-driven quantification to cyber risk

ID: 1561832
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(businesspress24) - London, UK – 28th October 2020 – Today, Dataiku, one of the world’s leading Enterprise AI and machine learning platforms, has announced its partnership with global specialty cyber underwriting specialist Envelop Risk. Envelop Risk is working with Dataiku to model and mitigate cyber and other forms of complex, unprotected risk for insurers.

Envelop Risk specialises in applying machine learning to complex corporate risks. In May, the firm announced a Series A investment of $6 million, led by AI-specialist investor Alpha Intelligence Capital. Since launch, Envelop Risk has underwritten well over $100 million in premium, placing it among the top insurtech firms globally by this metric. The firm operates as a lead market in cyber reinsurance, in partnership with MS Amlin.

Envelop Risk’s founding team and directors combine decades of leadership experience in both insurance and deep tech enterprises such as aerospace and defense. The firm reconceived how machine learning, human expertise, and underwriting can be integrated, using Dataiku’s end-to-end data science platform to build a system that enables more effective risk management by the underwriters of the future.

The firm began working with Dataiku in 2017 primarily to help with rapid prototyping of business solutions, implementing its collaborative data science platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently. The platform was engaged to help identify emerging cyber threats and quantify the associated risk for insured companies. Through the partnership, Envelop Risk has now been able to integrate advanced machine learning into its underwriting process to demonstrably reduce risk and streamline workflows in its day-to-day operations.

“The Dataiku platform has always stood out to me because of its ability to provide access to nearly everyone without placing constraints on our most experienced code-based data scientists,” said John Kelly, Chief Technology Officer at Envelop Risk. “We were looking for a tool that could help us better collaborate on data science across the corporation with people who have vastly different backgrounds and experience levels. Data scientists can’t operate in silos. They need to be working with domain experts and end users. It’s critical to have a system that can effectively act as an interface between those people, allowing the exchange of ideas, feedback, and results.”

Paul Guthrie, EVP and co-founder of Envelop, says that the platform has driven transparency, which is essential both for interpretability and for the incorporation of expert feedback that can fill any gaps or time lags in Envelop Risk’s data. Using the system built on Dataiku’s centralised data science platform, Envelop Risk’s underwriting team has been able to quantitatively model complex risk and get results on demand, while having access to the ‘why’ and the ‘how’ of those results.

“In the past few years, the pace and scale of data science, machine learning, and ultimately AI adoption has accelerated to enhance or reinvent the processes core to the insurance business, particularly in cyber,” commented Florian Douetteau, Dataiku CEO. “Envelop Risk is at the forefront of helping its customers to mitigate unprotected risk, and it’s a privilege to work with the firm as it develops new products. With the partnership and Dataiku's rapidly increasing presence within the insurance market, we see this sector increasingly executing on its strategic goals by fully embracing and leveraging the power of Enterprise AI.”

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published by: RealWire
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Date: 10/28/2020 - 15:20
Language: English
News-ID 1561832
Character count: 3870
Firma: RealWire
Ansprechpartner: Courtney Dean Feedback to about Pressrelease-id:
Stadt: Lincoln
Telefon: 01522 883 640

Meldungsart: bitte
Versandart: Veröffentlichung

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