Data science community Auquan secures £1m to disrupt financial markets with AI
AI startup Auquan secures £1m to enable investors to beat financial markets with math puzzles
June 2019 – Auquan’s global community of data scientists is providing a new way to beat financial markets – by solving fun maths puzzles. FinTech startup Auquan harnesses this collective brainpower through a gamified crowdsourcing platform to vastly improve the financial performance of their clients – some of the world’s biggest asset managers.
The company just completed a new round of funding from Episode 1 Ventures, the backers of Zoopla, Shazam, Betfair and Natural Motion. The new capital will be used to secure key senior hires and to expand Auquan’s existing community of 10,000 data scientists.
Auquan allows investment funds to translate complex financial problems into abstracted mathematical challenges that its network of 10,000 data scientists can understand, regardless of financial expertise. This provides access to more data science talent than any single fund could ever hope to hire. The AI models developed by these data scientists have already significantly improved the performance of Auquan’s clients.
The equation is simple: more data scientists equals multiple solutions which results in superior fund performance. London-based Auquan (pronounced awe-quan) has already worked with some of the world’s biggest investment funds, managing capital in excess of hundreds of billions of dollars.
In the last few years, data scientists have stepped into the spotlight as modern-day superheroes. Their superpower is the ability to take raw data and extract meaning to make better decisions, impacting an entire spectrum of industries. Whether we realise it or not, the work of data scientists lies behind most of our daily experiences. From the flights we take, to the food we eat, to our pension pots.
Founder Chandini Jain said: “The work of data scientists is especially important in the area of finance, where a single slip in rationality can lead to a devastating effect on the value of an investment portfolio. Algorithms don’t feel the emotional strain of a declining portfolio value, or make flawed decisions tainted by innate human biases. As a result, algorithmic decision making in financial markets has grown explosively in recent times.”
The finance industry has more job openings for data scientists than any other industry. But while demand is high, the supply of skilled data scientists is not even close. Especially rare, are data scientists with financial expertise.
Since launching in 2018, Auquan’s community has grown to over 10,000 puzzle-loving data scientists from some of the highest-ranked universities around the world including Oxford and MIT and currently working in some of the biggest tech companies, including Amazon, Google, Uber. These data scientists around the world compete to solve the puzzles on Auquan’s platform and submit their solutions in a bid to win cash prizes.
A recent Auquan competition winner, Mike Axiak, is a senior software developer at Hubspot and a graduate from MIT: “I didn’t have any experience in finance, but the problems on Auquan’s platform had interesting twists – like a stock selection problem disguised as a challenge to create a well balanced, high scoring football team. When I couldn’t beat the benchmark score in a puzzle right away, it fueled my inner nerd to keep trying the problem till I was on top of the leaderboard”.
Auquan is on a mission to translate even the most complex financial problems into fun puzzles for the best and brightest minds to solve. The founders, Chandini and Shub Jain, are life-long math puzzle enthusiasts. They also happen to be veterans of both finance and tech, having worked for the likes of Microsoft, Optiver and Gusto. Auquan is proving that the future of investment success is gamified and crowdsourced.
Auquan (https://auquan.com) crowdsources machine learning models for finance companies from their community of exceptionally talented data scientists. By solving fun math puzzles, a global community of 10,000 data scientists without financial expertise are helping fund managers, with billions of dollars under management, beat the market.
About Episode 1:
Episode 1 (https://www.episode1.com) is an early-stage venture capital investor that manages a £60m Enterprise Capital Fund, investing between £250k and £1m into high potential software-based businesses with significant operations in the UK.
Chandini Jain <[email protected]>