What do you get when you cross technologists with investment professionals? A different kind of number game.
Adrenalin flowed freely in London this November when experts from tech startups in New York, London, Milan and Bangalore caught up with investment experts from Allianz Global Investors (AllianzGI) to brainstorm on using technology to improve investment decisions.
30 hackers, 10 teams, 49 hours and 3 challenges: the Allianz Hackathon had all the ingredients of an exciting game show - How can Artificial Intelligence and alternative data complement traditional data analysis to improve asset class forecasts? How can AI algorithms limit systematic cognitive bias in the process of selecting stocks? Which alternative data sources such as social media, search engines, job portals and online marketplaces can complement AllianzGI’s own research and how?
Around 100 participants watched as startups presented their ideas to experts from AllianzGI and Allianz Asset Management as well as to an external venture capitalist. The best solution for each of the three ‘challenges’ will be implemented as a prototype in 2019 together with the winning company.
Thorsten Heymann, the Global Head of Strategy at AllianzGI and the host of the hackathon, believes that AI and Big Data in active management could offer big advantages for customers. Excerpts from an interview:
- How did the hackathon go?
Thorsten Heymann: "It was exciting! The hackathon was yet another step in our digital transformation journey. The technological developments based on AI, machine learning and alternative data are rapid. There are obvious advantages. We have been using technology in active management for a while, to develop the best possible performance for our customers. This is why we at AllianzGI have invested heavily in quantitative investment approaches in recent years and have built up AI expertise in all relevant asset classes. We hope that the symbiosis of this experience with young technology startup talents will enable us to further extend our lead."
- What does this mean in concrete terms?
"One question, for example, is how can forecasts be optimized if we have alternative data, such as social media data, analyzed by AI algorithms in addition to existing traditional financial data? Or whether we can use AI to identify cognitive distortions in investment decisions, which will enable us to minimize human biases in the process of selecting securities in the future. These two questions are aimed at making proven approaches even more efficient using the latest technology."