Human insight meets AI: The rise of systematic investing
IN THE fast-paced world of finance, the image of a seasoned investor poring over pages of company annual reports is rapidly giving way to a new reality. We are standing on the precipice of an investment revolution, where artificial intelligence (AI) is not just a tool but a transformative force, propelling the rise of a discipline known as systematic investing.
Systematic investing is the application of rules-based, data-driven models to analyse mountains of information – across structured data such as financial statements and stock prices, as well as unstructured data like news articles and satellite imagery.
These insights are then meticulously applied through predefined rules to select securities, manage risk and construct diversified portfolios.
The foundations of systematic investing were built by decades of academic research. Nobel Prize winner Eugene Fama, an economist, showed that some factors systematically explained returns, such as value, size and profitability.
By the 1980s and 1990s, institutional investors began turning these theories into practice through systematic investing by using disciplined, rules-based strategies to deploy capital across a large number of diversified positions, each designed to capture small performance edges.
“The defining strength of systematic investing is consistency. Decisions are rules-based, repeatable and less swayed by the emotional biases that often plague human judgment, such as buying high in a rally or selling low in a panic.”
The growth of computing power dramatically expanded what was possible. Advancements in AI, natural language processing and large language models have empowered asset managers to digest an unprecedented volume of structured and unstructured data, capturing thousands of small, repeatable performance edges across diverse global markets.
For example, AI can sift through thousands of corporate earnings calls in multiple languages globally, translate them instantly, and discern not just the words but the sentiment behind a CEO’s voice, whether it is cautious and evasive, or optimistic and forthcoming.
What’s in it for investors
Systematic investing is particularly relevant in the data-heavy environment in which we operate today. An estimated 90 per cent of the world’s data has been generated in just the last two years. This massive influx of information, from financial reports to shipping flows, is simply too vast for human processing.
Systematic strategies, armed with computational power, are designed to convert this deluge into investable insights.
The availability of such insights at speed and scale is what is accelerating systematic investing, providing investors and asset managers with unprecedented information on the characteristics and factors impacting returns. Available data has shown that assets under management for systematic investing have grown by more than 50 per cent in three years.
Once reserved for pension funds and sovereign wealth managers, the democratisation of AI has also made systematic investing strategies increasingly accessible to retail investors in the form of mutual funds in Singapore. They offer investors institutional-grade research and risk controls in a regulated, transparent wrapper.
The defining strength of systematic investing is consistency. Decisions are rules-based, repeatable and less swayed by the emotional biases that often plague human judgment, such as buying high in a rally or selling low in a panic.
By systematically harvesting proven sources of return across thousands of securities, these strategies offer investors diversification, discipline and the ability to tap into insights that no human could process alone.
“The powerful synergy of man and machine, blending computational scale and human judgment, is the winning formula.”
BlackRock calls this “alpha reimagined” – small information edges sourced from big data and diversification, rather than headline-grabbing stock picks. The result is outperformance that may appear modest in the short run, but more durable across cycles.
Systematic approaches are also spreading into liquid alternatives. Once the domain of hedge funds, strategies such as long-short equity or market-neutral investing are now offered in mutual fund formats.
Here, algorithms can go long and short across thousands of stocks simultaneously, continuously rebalancing positions based on shifting signals. For investors, this means exposure to diversification and downside protection tools once reserved for institutions, delivered in a regulated, daily-priced structure.
What investors should watch for
While systematic funds offer discipline and access to institutional methods, they are not a silver bullet. Investors must exercise due diligence and understand the underlying basics of each fund solution – whether it tilts towards value, momentum or other factors.
For the diversification objective, it is also important to incorporate solutions with low correlation to market returns.
In addition, while machines excel at processing data at scale, models have their limits, and no single approach works in all markets. Data can be noisy, assumptions can fail, and black-swan events can upend predictions. Higher fees compared to passive trackers necessitate a clear justification for the strategy’s cost.
This is where human oversight matters. Portfolio managers frame the hypotheses, monitor outputs and adapt strategies when markets behave in ways history cannot predict. A robust track record from the asset manager is essential to ensure human judgment effectively adapts models to unforeseen surprises.
The powerful synergy of man and machine, blending computational scale and human judgment, is the winning formula.
The road ahead
The explosion in data and advancements in AI are reshaping portfolio construction itself. AI is no longer just a theme to invest in; it has become an integral tool to invest with.
By combining the scale and objectivity of machines with the judgment and oversight of humans, systematic mutual funds may not deliver outperformance in every market, but they offer a disciplined path to capturing return drivers that have historically delivered results.
For Singapore investors, the opportunity is clear. Systematic investing is not just about seeking excess returns; it is about building resilient, diversified portfolios. By systematically allocating across thousands of securities, these strategies reduce reliance on any single position, diversify across factors and geographies, and create more balanced portfolios for the long term.
In a world where markets are increasingly shaped by volatility and vast amounts of data, the winners will be those who can harness AI as the apex technology of the information era – not only to generate outperformance, but also to design portfolios that are more diversified, resilient and future-ready.
The writer is head of investment advisory for Asia South wealth, Citi
