Investment managers view generative artificial intelligence (GenAI) as the “holy grail” to create value, but the availability of data and cultural change are some of the main challenges, according to a Citigroup executive.
The industry has applied AI via a “three-pronged” approach, according to a Citigroup report published this week based on more than 40 interviews conducted with C-suite executives of top global investment firms, many of which have operations in Asia, including Hong Kong.
The most common use of AI is to enhance operational efficiency and productivity, followed by investment research and client engagement, according to the report. The third envisions the potential of using GenAI in alpha generation, investment decisions, or automated creation and management of funds.
“For the investment management industry, the holy grail is to find an alpha generation idea,” Helen Krause, head of global data insights at Citigroup, said in an interview with the Post.
But right now generative AI is not yet there from the perspective of helping generate additional returns on its own, she added.
Many investment industry players started to explore and find uses for the technology after Microsoft-backed OpenAI launched the groundbreaking ChatGPT GenAI app in November 2022. Generative AI describes algorithms that can be used to create new content, including audio, code, images, text, simulations and videos. Large language models such as ChatGPT are deep-learning AI algorithms that can recognise, summarise, translate, predict and generate content using very large data sets.
Krause said investment managers across hedge funds, sovereign wealth funds and asset management firms are enthusiastic about GenAI’s potential benefits to save costs and improve productivity and efficiency.
Wealth management, ESG analysis and private markets are also seen as areas where AI can add value. These areas often require tailor-made solutions and have less available information.
However, there are significant challenges and concerns about AI applications, especially as the investment management industry is highly regulated and is answerable to its fundholders, Krause said.
For example, many of the executives surveyed highlighted that changing the company culture is a critical challenge in increasing the adoption of AI tools and solutions across their organisations. When a firm already has a successful portfolio management team, incorporating an AI tool takes a lot of convincing. Employees must also be “upskilled” or trained to use the technology.
Data is another factor hindering the deployment of AI, the report said.
Investment managers often face issues leveraging AI, given that their data is siloed within different systems, Krause said. If the data is “in one place”, creating a “feedback loop” for an organisation to use any information through investments, distribution and operations, more uses will materialise, she added.
“In order to get AI in place, [investment managers] need to sort out their data pipeline [and] be able to change people’s mentality,” Krause said.
“The technology side of breakthrough is definitely thought-provoking. What we have learned and heard is this is not a silver bullet [that is] going to solve all the issues. You need to have a robust risk and control environment to run this successfully.”