Utilising AI and ML for the fund selection process

“Unlike active portfolio managers, financial advisors were unharmed by the index-fund revolution. Like active portfolio managers, they face little threat from artificial intelligence – and possible great benefit, if they harness its powers.”

Artificial intelligence (AI) and machine learning (ML) is a great asset to the fund selection process. Leveraging predictive analytics, personalised recommendations and reduced bias, the integration of AI accelerates and enhances the credibility of fund selection. AI algorithms use historical data to forecast fund performance, identify market trends, and assess potential risks. This predictive capability can help fund selectors make more accurate investment decisions and mitigate any risk. In addition, AI algorithms are less prone to biases that can affect human decision-making. By tailoring fund selection suggestions according to each individual investor’s risk tolerance, financial objectives, and preferences, AI-driven recommendations pave the way for appropriate investment selections tailored to each unique investor.

The Morningstar article by John Rekenthaler titled, “Who should worry about AI more? Active managers or advisers?”, highlights that portfolio managers are likely to experience minimal impact—whether positive or negative—from AI integration. While, financial advisers have potential for substantial benefits utilising AI due to its flexibility and ability to provide customised recommendations. The author highlights that it may be possible “that customers will grow accustomed to accepting its counsel, without hesitation.”

By using data and algorithms, fund advisors can reduce the impact of emotional or cognitive biases in their choices. Artificial Intelligence can continuously monitor fund performance and market conditions in real time. If a fund’s performance or market conditions deviate from predefined thresholds, AI systems can alert fund selectors, enabling quicker reactions to changing market dynamics. This reduces time and cost as the processing of information and data is much faster. Further, AI can assess the risk profile of investment funds by analysing various factors, such as historical volatility, asset correlations, and macroeconomic indicators. This can provide fund selectors with a more comprehensive understanding of the risks associated with different funds. 

FUNDSaiQ is an artificial intelligence and machine learning driven platform that empowers financial advisors to identify and monitor the 2-3% of active funds that consistently beat passives. In addition, the platform can identify the best lower-cost passives that perform just as well as the active options. The platform allows for customisation with exposure that financial advisors want – asset class, region, country, sector or theme, along with a flexible ESG ranking tool and curated news flow.

Furthermore, the system possesses the capacity to assess risk reward and enhance returns on investment. This capability is complemented by streamlined operations that can select and monitor the consistently best fund managers in each investment strategy globally. As a result, lower costs and improved efficiency is guaranteed, offering significant advantages to financial advisors.

However, it is clear that AI alone should not be providing decisions. So an effective fund selection involves a combination of artificial intelligence driven insights along with human judgement to make well informed investment decisions. Hence, by effectively harnessing AI, financial advisers can unlock substantial benefits.

Read Morningstar’s article by John Rekenthaler here