Artificial intelligence (AI) is rapidly being adopted across the financial landscape. In asset management, applications of AI are articulated around the technology’s key inherent capabilities: the ability to conduct repetitive tasks efficiently; the ability to extract information from unstructured data sources; and the fact that AI algorithms are able to improve themselves, according to a research paper by the CFA Institute. Wide range of existing and emerging applications of AI in asset management, focusing on three major areas: portfolio management, trading and portfolio risk management. Looking at how the technology has been used so far in the industry, it outlines three main intrinsic capabilities of AI that are relevant to asset management.
First capability, the paper says, relies on the fact that AI models are objective, highly efficient in conducting repetitive tasks, and able to identify patterns in high dimensional data that may not be perceptible by humans. AI can also analyze data with minimal knowledge of their structure or the relation between input and output, a feature that’s is especially useful for forecasting, yielding more accurate estimates. AI techniques are already an essential part of the practice, notably for its ability to process large amounts of data to generate trading signals. Moreover, algorithms can be trained to automatically execute trades based on these signals, which has given rise to the industry of algorithmic trading.