Deep learning has been very successful in social sciences and specially areas where there is a lot of data. Trading is another field that can be viewed as social science with a lot of data. With the advent of Deep Learning and Big Data technologies for efficient computation, we are finally able to use the same methods in investment management as we would in face recognition or in making chat-bots. In his session at 20th Cloud Expo, Gaurav Chakravorty, co-founder and Head of Strategy Development at qplum, will discuss the transformational impact of Artificial Intelligence and Deep Learning in making trading a scientific process. This focus on learning a hierarchical set of concepts is truly making investing a scientific process, a utility.
Serena Capital, a major player in financing and accompanying high growth digital companies, has launched its 3rd fund in 8 years; Serena Data Ventures, dedicated to Big Data and Artificial Intelligence. Institutional investors and large corporate groups have committed close to 80 million Euros to Serena Data Ventures which just closed its first investment in Heuritech, a French startup specialized in deep learning technologies. Serena Capital reinforces its start-up support with the arrival of 3 new Venture Partners and Amélie Faure hired as Operating Partner. At the end of 2016 Serena Capital published a study focused on the "Data Revolution" and the great dynamism of European start-ups in the field of Big Data and Artificial Intelligence. In the coming years identifying and leveraging data will disrupt all business sectors including banking, insurance, health, energy, manufacturing, trade, logistics, etc.
Colonial First State data scientists are working with a team of computer engineering PhDs from the University of Technology, Sydney, to develop deep learning algorithms to predict investor responses to market shocks and tailor the communication of financial advice. A five-year partnership between Commonwealth Bank of Australia-owned CFS and UTS has resulted in the asset manager providing 20 years of investment and behavioural data for 1 million customers to machine learning researchers at the university, who are using its cutting-edge super-computers to forecast investor reaction. Peter Chun, the general manager of product and investment at Colonial First State, said artificial intelligence and big data analytics will also help the asset manager predict which customers might be more receptive to investment opportunities. He points to the example of the government's non-concessional contribution rules for superannuation; customers have a window of opportunity before June 30 to invest more than the caps.