What has AI made possible in the financial industry that wasn’t possible before?
The aim of artificial intelligence is to enable computers to autonomously perform the tasks assigned to them based on algorithms, while reacting adaptively to unknown situations.
Let’s take an example from asset management: today, personalized investment decisions can be made in line with the customer’s individual needs and everything can be calculated automatically by computers. In the past, this was either a very lengthy process or it was replaced by standard solutions. Or another example from investment banking: AI is already able to make automated optimal decisions about how and at what time orders for shares are executed. Until a few years ago, most buy and sell orders were handled manually by phone. The capital asset pricing model developed in the 1960s, which formulates the expected return of shares on the basis of historical capital market data, still assumed a linear relationship between an individual security and the overall market. But not all things are linear in the world. Today, with AI, we’re able to calculate the expected returns and prices of derivatives in such a way that we can take complexity into account. However, this isn’t calculated on the basis of a linear equation, but on a complex mathematical function that can have millions of parameters.