AI’s Impact on Pension Funds: Opportunities and Challenges

According to the Mercer CFA Institute global pension report, pension funds could use artificial intelligence (AI) to lower costs, boost investment returns, and highlight potential risks, however, there are still “significant challenges to overcome” in its application.

The 17th of October marked the release of the annual joint report from the consulting firm and investment professional association, which identified AI as useful for assisting pension fund managers in sifting through massive amounts of data to identify investment opportunities and construct customized investment portfolios.

David Knox, the main author and senior partner at Mercer, wrote, “AI will impact the operations of pension systems worldwide.” It has the potential to significantly enhance the member experience and retirement outcomes.

innate language Pension funds could also use AI to analyze their members, collecting data from emails and phone calls to personalize their marketing and outreach based on how each member communicates.

It is claimed that AI-assisted analysis can identify patterns, uncover market sentiment and signals, and suggest unorthodox future investment opportunities.

“This can lead to improved asset allocation and/or better diversification, resulting in higher long term returns and lower volatility.”

Additionally, AI could assist investors in assessing environmental, social, and governance (ESG) factors.

It is anticipated that the technology will also facilitate the automation of middle and back office environments, thereby reducing costs and narrowing the gap between passive and active investment strategies.

AI is also anticipated to facilitate the prediction of member behavior in response to a wide range of potential economic and political conditions that can impact the cash flows of a pension fund.

A summary of the use of AI in investment management. Source: Mercer CFA Institute Global Pension Index 2023

However, AI tools can generate false or misleading information, and uncertainty surrounding AI use is likely to persist because models “cannot accurately predict market prices.”

“For example, a stock market crash can lead to members switching to defensive asset classes, whereas a newly elected government may lead to some retirees withdrawing their accrued benefits.”

The report also emphasized the importance of “strong defenses against cyberattacks, scammers, and other security breaches.” The author describes how AI is already being utilized in investment markets to analyze data, reports, risks, and market trends to make judgments.

Since the 1980s, programmable trading has been utilized, and high-frequency trading has altered the way investments are managed.

Algorithmic trading is reported to contribute significantly to automated trading, accounting for up to 73% of equity trading in the United States in 2018.