Custom indexing has allowed investors to create personalized investment portfolios that go beyond simply replicating existing indexes, and artificial intelligence tools are beginning to inform that process.
At companies like Noonum, Canvas and Alphathena , AI assists in direct indexing, as well as portfolio management and rebalancing. Noonum, for example, uses AI to help create thematic strategies and to assist in asset discovery.
“Today, custom indexing gives us the flexibility to precisely align exposures with the outcomes our clients actually want and need. The benefits become even greater when we combine that flexibility with AI,” says Sandy Kaul, head of innovation at Franklin Templeton. “AI also lets us break away from the limits of static benchmarks. Instead of backward-looking reports, we can offer systems that learn, adjust and keep portfolios aligned with changing objectives. For CIOs, that means more accurate insights and greater adaptability across mandates.”
The promise of AI in indexing is that it could be more effective than human analysts at sifting through massive amounts of data to inform investment decisions. A 2024 paper, “AI-Powered Direct Indexing: Exploring Thematic Universes for Enhanced Risk-Adjusted Returns,” found that an AI-based search engine was more accurate and much faster at creating thematic indexes than were manager-curated ETF stock selections.
Never miss a story — sign up for CIO newsletters to stay up-to-date on the latest institutional investment industry news. ?
“Thousands of potential investment signals are now accessible through AI’s ability to analyze such varied data sources as return patterns, social media sentiment, macroeconomic indicators and the nuanced language embedded in corporate filings,” says Paul Kenney, a senior vice president of client solutions at Syntax Data, a financial data and technology platform.
Direct lender Maple is one asset manager that uses artificial intelligence to inform its direct indexing and has used the technology to improve its operations.
“We use [AI] to manage risk, optimize loan portfolios and give lenders a real-time view of how their capital is performing,” says Martin de Rijke, Maple’s head of growth. “For allocators, this means more transparency, faster decisionmaking and the ability to move with confidence in markets that were once opaque and slow.”
Informing Portfolio Management
Investors are increasingly adopting and seeking to adopt technology and AI tools to assist portfolio management. According to Northern Trust’s 2025 global asset owner peer study, approximately half of respondents said they plan to increase technology spending for portfolio analytics and portfolio management.
The CFA Institute noted—five years ago—that AI tools can strengthen investors’ risk management.
“Since the 2008 global financial crisis, risk management and compliance have been at the forefront of asset management practices. With financial assets and global markets becoming increasingly complex, traditional risk models may no longer be sufficient for risk analysis,” the CFA Institute wrote in a 2020 report. “At the same time, AI techniques that learn and evolve by using data can provide additional tools for monitoring risk.”
The CFA paper noted at the time that AI could help address some of the shortcomings of classical portfolio construction techniques.
“In particular, AI can produce better asset return and risk estimates and solve portfolio optimization problems with complex constraints, yielding portfolios with better out-of-sample performance compared with traditional approaches,” the paper stated.
Mercer, in a 2024 report, noted that 91% of surveyed investment managers said they already use or intend to use AI in their investment process and asset class research.
Adem Berk, a principal in EY, notes that artificial intelligence will be among the biggest innovations in institutional asset allocation over the next 10 years.
“We believe that investment organizations that adapt their current thinking to incorporate artificial intelligence will gain a significant edge,” he told CIO earlier this year. “By leveraging AI’s capabilities to analyze vast data sets and uncover valuable insights, asset allocation strategies and decisionmaking processes will be significantly enhanced. However, it is crucial to strike the right balance between machine-driven insights and the essential human element in fiduciary decisionmaking.”
Tags: Artificial Intelligence
#Informs #Indexing #Portfolio #Management