by Lionel Semonin, Chairman of Alphien
Photo: Lionel presenting about sustainable AI research at NExT Workshop 2019
The financial industry is facing many challenges in adopting machine learning techniques. The adoption has been very slow and limited to automatizing repetitive tasks. Robo advisors are merely using customer information to profile risk tolerance and to know more about their clients. The challenge is to use AI techniques in the investment process, and that is a disruptive change which is upcoming in finance.
The world of systematic investment require a full stack of highly advanced technology in order to make use of machine learning. The race for rapidity has led high frequency traders to use the most advanced specialised hardware (including dedicated fiber) to take advantage of price discrepancies between exchanges. Even in lower frequency strategies, technology is ubiquitous in a historically highly regulated industry.
The appetite for quantitative strategies is thriving as the alpha generated by traditional managers has been statistically poorer. Nevertheless, the ability to understand machine learning remains very doubtful. The term ‘black box’ has been given for years and has deterred investors to adopt model based approaches. The need for a third party to vet the quality of the research to make sure that it is reliable, robust and scientifically viable has been very important.
The access to the data has been extremely difficult and costly for academia and entrepreneurs in general. Technology start-ups as well as independent researchers have not been able to access the relevant data to carry out their research.
Alphien platform is an answer to all these problems through an interactive platform for quantitative developers to create investment strategies, that would be accessible and potentially adopted by institutional investors and asset managers. The platform allows users to make the AI research in finance more explainable, better documented and checked by Alphien ambassadors. The separation between the community performing research and the platform independently checking what has been done by industry experts should boost the credibility of AI in the industry.