Artificial Intelligence and Data Science Will Transform the Asset Management Industry

By Karyn Williams


Most of us take for granted that asset managers deliver services to investors through investment products. Whether actively managed to pursue alpha or passively managed to track broad indexes, asset managers sell, and investors (advisors) buy them for portfolios. There are over 10,000 such products around the globe competing for a place in your investment portfolio. With advances in artificial intelligence and data science, this is about to change radically. 


Advances in computing power and the availability of real-time data on virtually every aspect of the global economy have changed the investment game. No matter how astute any human fund manager is, no person or team is as capable of processing, prioritizing, and analyzing all of this data as a set of well-calibrated algorithms. 


This state of play puts immense pressure on active asset managers. For those whose processes have not changed appreciably over the past ten years, alpha is increasingly hard to produce. They will have to innovate or otherwise compete with large fund complexes that offer nearly zero cost passive products.


Adding to this pressure are low yields. An investor who targets 5% for his or her investments to support for future goals and wants to keep pace with 2% and cover investment fees of 1.5% has to earn over an 8% annually. But with 10-year Treasury yields below 1%, as of this writing, investors have difficult portfolio choices to make: lower the overall cost of investing (by moving from active to passive products), increase the risk of the portfolio, change the investment objectives, or all of the above. 


A traditional investment product that fits within an asset class will not fill the return gap. They usually comprise between 1% to 5% of a portfolio, so even with expected outperformance it will have a small overall impact. A multi-asset product also may not help. Off-the-shelf and one-size-fits-all, they are designed for an average investor and do not necessarily fit with the rest of the portfolio. Private market and quant products may not help either, presuming the investor can get access to the best products. Not only are fees high, but the potential for large portfolio losses can actually lower long-term portfolio returns. 


Rather than traditional investment products, investors need solutions, and this is precisely what AI and data science can provide.


AI techniques can improve how we measure and manage market risks compared to traditional approaches. Applied to the investor’s challenge, an AI-based solution that maintains a portfolio’s exposure to equity markets while moderating large declines in value, can improve investor outcomes. AI also can better systematize data, interpret investor profiles, and control certain decision biases. An AI-based solution that is designed specifically for an investor’s unique risk capacity and can control biases can further improve investor outcomes. 


To sum up, the next generation of AI-enabled investment solutions not only better measures and manages portfolio risks, they are customized to serve each investor’s specific needs. At scale, AI-based solutions replace the traditional products we see in the market today.


Arguably, one of the roadblocks with the adoption of AI across the investment management industry is attitudinal, with the fear of AI either displacing advisors or making investment decisions that investors do not understand and cannot monitor. 


Approached correctly, with understandable algorithms that are aligned with client objectives and free of conflicts of interest, AI can help investment professionals to serve their clients better. AI frees them to focus on what their clients care about – achieving investment objectives. It replaces complex conversations about the latest products with overall value creation. By creating meaningful value, advisors become even more essential and clients feel confident.


AI and data science can drive a profound and positive transformation for investors. Better risk measurement and management, customization, and a holistic approach will upend products in favor of solutions, driving considerably better outcomes and empowering investors to invest more confidently.