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Artificial raises £9.5m Series A funding round

Anna Burge
Anna Burge20-Jun-2022

Artificial Labs has raised a Series A funding round of £9.5m led by Force Over Mass Capital with participation from existing and new investors, including Mundi Ventures, No.9 and MS&AD Ventures.

Artificial raises £9.5m Series A

Artificial’s technology enables an insurer to accept, refer or decline submissions based not only on the characteristics of a risk, but also its value in relation to a target portfolio. As a result, insurers can realise significant operational efficiencies with the opportunity to use all available data for improved risk selection. This benefits both day-to-day and strategic objectives.

The Artificial platform integrates with brokers and insurers on any data set, system or application, normalising data and allowing underwriters to either approve or decline risks in seconds and focus on high-value decision making. Decision making can either be instant or reduces the time for a human to bind up to 85% and allows for informed portfolio management.

The Series A round comes on the back of unprecedented growth in 2021. The company has grown its strategic partnerships to include several leading global insurers and brokers such as Convex, Chaucer, Aon, AXIS and Ed Broking, and the platform is now used across a wide range of s­pecialty product lin­es.

Investment will be used for continued expansion and to further develop the platform across both Smart Lead and Smart Follow underwriting.

David King, Artificial Co-founder, commented:

"The Artificial platform was created to enable insurers to write better risks, faster. The past two years have demonstrated how rapidly the insurance landscape is changing, with unprecedented global challenges driving high demand for digital-first solutions. Our technology allows insurers to capture their data once at the point of entry and harness it throughout the rest of their business, saving time, money and effort."

"Our platform has been built for the new age of commercial insurance, but it also functions today in the market as it exists today. Closing our Series A round is a further endorsement of the capabilities of the Artificial platform and a sign that the market is ready for algorithmically-driven, digital solutions. We're excited to be part of the next era of insurance."

Wouter Volckaert, Chief Investment Officer at Force Over Mass:

"We're thrilled to partner with Artificial. Force Over Mass is committed to supporting companies with the initiative to drive innovation, and Artificial has proven they can deliver new and exciting technology for the insurance market. We are looking forward to the next chapter in this journey."

Jon Soberg, Managing Partner at MS&AD Ventures:

"We are very excited about the team and the technology at Artificial. We think they can enable the next generation of digitally-enabled automated underwriting in the Lloyd's syndicate market, and we are happy to be working with them."

About Artificial

Artificial is an insurance software business offering algorithmic, data extraction and machine learning solutions to commercial insurers, empowering them to write better risks, faster. The company provides solutions to partners across the London and global markets, including Convex, Chaucer, AXIS and more.

The Artificial platform specialises in instantly and accurately capturing data at the point of entry for use in downstream applications. The platform enables clients to augment this data through effortless integrations and use it to write risks algorithmically, build contracts and feed into other systems...

About Force Over Mass

Force Over Mass focuses on B2B technology innovation (Industry 4.0, Artificial Intelligence, Fintech) in Europe and the UK. We invest in companies that combine transformational technology with strong business models.

The FOM partners and team have worked together on 100+ investments across all FOM Funds. We believe that consistent performance is driven by broad sourcing, a disciplined investment process, helping companies scale, and optimal portfolio construction.

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