Artificial intelligence in asset management has been hailed as investing’s next frontier. Although it is already widespread in the industry in various forms, its true potential in portfolio management is still far from being fulfilled.
AI has come a long way since its first recorded uses back in the fifties, and the technology continues to evolve at an unprecedented rate. In a study on AI and finance for the Alan Turing Institute, Professor Bonnie Buchanan puts AI’s “impressive” growth down to declining processing and data-storage costs, and an immense availability of data.
But compared to other fields, the quantity of data or the ability to create and collect new investment data is still not sufficient, despite its perceived abundance, according to Michael Neumann, head of AI quant investing at Arabesque AI in London. Financial data also comes with a lot of ‘noise’, and the definition of success or failure can be more nuanced.
“When it comes to driving autonomously, it’s very easy to identify if it is a success or failure: either the car crashes or it doesn’t,” Neumann tells Funds Europe. “This isn’t necessarily the case with investing.”
Arabesque AI specialises in the use of artificial intelligence to predict stock market movements. The firm saw its profile raised recently when Frankfurt-based asset manager DWS bought a minority stake in it to augment its own digitalisation.
To predict stock prices, Arabesque AI uses a mix of unsupervised and supervised machine-learning models to carry out complex computational tasks and data analysis. It works in a similar way to image-recognition technology.
“What is not happening yet in the funds industry, by and large, is the use of AI to fully power an investment solution,” Neumann says. This kind of application would revolutionise the industry.
Read the full article from our November issue here: Artificial intelligence: Gateway to Wonderland
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