Part 5
Investment and Wealth Management

Is AI the future of investment management? Part 5 will present a wide range of perspectives on this topic to help professionals navigate through the promises AI holds.

According to the 2017 Financial Stability Board report, “pure” AI and ML players had about $10 billion in assets under management, but this figure has grown rapidly since then as the scope for the use of AI and ML in portfolio management widened.

This part presents examples of real and possible uses of AI in this field, alongside challenges, risks and opportunities. The reader will be able to navigate through cases of how AI systems can support predictive analytics, trade processing and automate data collection for investment and wealth managers.

The use of AI in predictive analytics is flourishing. These AI systems can provide real help to traders and enable them to make better and faster pricing decisions. Algorithms can also be used to gather and analyse a huge volume of market information to identify better investment opportunities as well as reduce risks.

Key issues remain but do not override the general enthusiasm and positive approaches readers will find in these pages. With AI entering every corner of society, questions around the future of the profession among investment professionals cannot be underestimated. However, a view emerges from these pages, and that is that the deployment of AI will speed up the execution side of activities thus being able to provide answers to investment decisions in a fraction of the time currently needed. With the right digital transformation strategies in the investment management industry, these systems will in the end increase productivity and financial success for investors, investment management companies and private banks as the cost of managing portfolios for institutional, high-net-worth and retail clients will progressively decrease while the returns will increase.

Ultimately, technology will allow customers to have access to data-based decisions and greater insights, and all this will increase confidence and trust. In a sense, and this is what emerges from this part, investment management is an area where cooperation between humans and machines will bring great benefits.

It is certainly true that AI has been used in trading algorithms for years, but the huge amount of research that has now gone into it means AI could reap even greater efficiencies in investment management in the years to come.