Hedge fund tycoon and City veteran Alan Howard has backed a series B investment round into London macro analytics startup Quant Insight (QI).
Additional backing came from Stone Milliner Asset Management's Jens-Peter Stein, in a round understood by City A.M. to hold a multi-million dollar valuation.
QI also said that over 80 per cent of the capital in the funding round came from its own clients. The funding will be used to boost the startup's presence in the US and Asia, after the company increased its client numbers by 50 per cent so far this year.
"QI helps untangle complex markets and identify what is driving asset prices," commented Howard on his investment.
"I can see many applications for QIs technology and am pleased to support them in their expansion."
The hedge fund billionaire and co-founder of asset management firm Brevan Howard appeared recently in the news over an impressive comeback on his AH Fund, which brought its total year-to-date returns to 44.3 per cent in May.
Howard had launched the AH Fund last year, as investors began to defect from Brevan Howard. The thought was that investors would be persuaded to stick with a fund which counted Howard as its sole manager.
It's not the first time Howard has made an investment into AI startups, previously giving £4m to fintech personal investment app Arkera in April earlier this year.
Developed by a group of former investment bankers, data engineers and Cambridge University academics, QI combines investment expertise with data algorithms and machine learning to deliver an analytics web platform that provides investors with actionable insights on their trades.
These include the ability to empirically reveal key market drivers, optimise trade selection, quickly spot regime shifts, build portfolios with specific macro characteristics and identify valuation anomalies.
Mahmood Noorani, the founder of Quant Insight, said:
"We are delighted to welcome the new investors to the Qi team; their commitment is testament to the industrys need for fact-based analysis rather than opinion-based macro research to explain the dynamics of asset prices.
"We believe using AI and machine learning based models together with quality data provides a clear competitive advantage to discretionary managers, and we look forward to further developing our offerings to help investors make sense of todays complex trading environment."