InsurTech pioneer Quantemplate appoints industry veteran as CEO and receives £2.5 million in new capital to accelerate growth

InsurTech pioneer Quantemplate appoints industry veteran as CEO and receives £2.5 million in new capital to accelerate growth

Leader in machine learning data transformation and analytics sees fivefold increase in revenue, with ambitious plans for expansion

Quantemplate, an InsurTech firm which uses machine learning to help re/insurers grow their business through data transformation and analytical insights, today announced that David Lundgren has been appointed CEO and Board Director. The company has also received £2.5 million (GBP) of new capital to accelerate its expansion plans. This follows breakthrough revenue growth of 500 percent during the last 12 months, driven by leading multinational insurers and reinsurers licensing Quantemplate’s unique technology solution.

Lundgren brings deep insurance industry and operational expertise from firms such as Allianz, CUNA Mutual, General Electric, and AgPro Exchange. He currently serves on the boards of Jewelers Mutual and Bunker.

David Lundgren, Quantemplate CEO

“Quantemplate’s data transformation and analytics suite, powered by machine learning, gives our clients the tools to expand their business, cut costs and, most importantly, drive forward the digital transformation which is a strategic imperative for most insurers,” said Lundgren. “This year, to add to the continued confidence of the investment community, Quantemplate has also experienced a real shift in market momentum with leaders in the Life and the P&C sectors, as well as major reinsurers, signing multi-year agreements with us.”

The latest £2.5 million of capital, from Columbia Lake Partners, is in addition to fresh financial commitments from Quantemplate’s original investors: specialists in InsurTech venture capital Route 66 Ventures and Anthemis, alongside insurance industry leaders TransAmerica Ventures and Allianz. Quantemplate has received a total investment of over £10 million since its founding five years ago.

Daniel Bull from Columbia Lake Partners, the firm’s newest capital partner, said “Quantemplate has shown impressive traction in acquiring some of the world's leading insurance companies as customers. The team has proven that they truly understand the needs of the insurance vertical, and Columbia Lake Partners is excited to be a part of their continued growth in the UK and Europe.”

Yann Ranchere from Anthemis added "Quantemplate is continuing to establish itself as a key player in the digital transformation of the insurance industry. With David Lundgren bringing his unique insurance experience and new funding from Columbia Lake Partners as well as historical investors, we are excited to see Quantemplate enter a new phase of growth."

Designed for re/insurers, Quantemplate automatically unifies the disparate types of data these companies have to process, solving issues of data integrity or compatibility through machine learning. Traditional technologies and outsourcing have fallen short when faced with these intractable problems. In contrast, Quantemplate provides analytics which can generate unique business insights from this disparate data – around market opportunity, underwriting profitability, claims and fraud, and MGA (managing general agent) integration. The solution integrates alongside clients’ data ecosystems seamlessly, without disrupting workflows.

Commenting on Lundgren’s arrival and the new finance, Quantemplate Co-founder and Chairman Adrian Rands said “we built this company from day one with a foundation of deep expertise in the insurance industry and a vision to help clients gain the insights which bring competitive advantage. Now, with this expanded support, we can accelerate Quantemplate’s growth and deliver on that vision.”

The firm’s expansion plans focus on the UK, US, and European markets.

About Quantemplate

Quantemplate provides machine learning data transformation and analytics software to the re/insurance industry. The technology enables business users to take raw data sources, cleanse and harmonise them with tools powered by machine learning, then perform analysis to develop competitive advantage through proprietary insights.

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