Over the past 200 years the world has been through significant change, thanks to the advancement and disruption of technology. In the past 30 years we’ve seen how drastically technology can shape our lives. The 1980s saw the advent of home personal computers, and the mid-1990s brought the internet to the masses. In the mid-2000s it was the mobile revolution, bringing the internet to 50% of the world. We’re now moving into a new era – a new revolution – one that has artificial intelligence (AI) at its core.
WHAT IS ARTIFICIAL INTELLIGENCE?
AI is a sub-field of computer science that uses computers to generate knowledge by extracting meaningful intelligence from data. Its purpose is to help humans more efficiently process and interpret vast amounts of data.
Machine learning (ML) leverages AI by using algorithms to identify and act on patterns in the data. ML autonomously learns and adapts to new data without being pre-programmed and at speeds that are far beyond human capacity. These two factors together should help deliver better, more consistent outcomes. Examples include self-driving cars, Google Translate, image recognition and mobile phone personal assistants like Siri.
BEHIND THE CURVE
The real question is, what will AI mean for the world of investments? Compared to other industries, the mainstream asset management industry is a little behind the curve in terms of implementing AI.
The financial markets have been through significant change in recent years. With unprecedented central bank participation, markets now move faster than ever before and conventional valuation and asset allocation theories can struggle to keep up. AI can be used to help investment strategies adapt quicker to changing markets.
Broadly speaking, AI and ML can be applied to investment management in two ways:
- Total automation of the investment process, in which the AI selects the optimal portfolio allocation based on a predefined investment strategy with objectives, constraints and investable instruments.
- Working with an investment manager directly by enhancing the asset allocation and stock selection buy/sell signals based on the portfolio of instruments chosen directly by the manager.
MORE CONSISTENT OUTCOMES
However AI and ML are applied, their goal is to provide better predictive accuracy and more consistent outcomes. The advantage of AI is that it eliminates human emotions and can actively adapt to rapidly changing markets, helping investment managers achieve better results for clients with potentially significantly reduced downside risk.
Every major financial institution is looking at how AI can be applied. While most are focused on using it in back-office operations, very few have any solutions that focus on improving investment outcomes. Sanlam Global Investment Solutions (SGIS), a pioneer in the field, currently runs five AI portfolios, which can be used either as stand-alone or complementary portfolio solutions. The portfolios have distinct cash, bond and equity allocations based on Morningstar Target Risk Indexes that cater to multiple risk profiles.
The AI portfolios’ investment process is totally automated. The portfolios use a multi-purpose ML investment engine that takes the best of ML and applies it to the underlying portfolio instruments. Its purpose is to more accurately predict how asset prices will move and to select the optimal portfolio weights to hold for each asset until the next prediction point. The optimised portfolio tries to minimise expected capital loss risk, which is a significant factor affecting clients, especially those in retirement.
IMPRESSIVE RESULTS
The back-tested results are impressive. In simulated tests, Sanlam’s AI Dynamic US Portfolio in 2008 returned positive 24% while its benchmark lost 22%. In 2011, it gained 31% versus its benchmark’s gain of only 0.6%.
AI should be combined in an investment strategy and is no magic bullet, given it won’t be perfect in all market environments. While it does have good predictive accuracy or good generalised performance, it will never be 100% accurate or even close to this. It’s just currently the most advanced way for investment professionals to make sense of markets and improve their clients’ investment experience.
A FINAL WORD
The best way of knowing how any investment is doing is to measure it against another investment strategy or set of investment objectives. If the AI solution helps achieve an investment outcome in a more efficient, effective way, then it’s doing its job. If you measure it over time against a human discretionary strategy with the same goals, the differences should be clear. The bottom line is that in today’s world, it’s not man versus machine, it’s man with machine, versus man without.
WHAT SPW CLIENTS SHOULD KNOW
Additional comment by David Lerche, Senior Investment Analyst: As stated above, AI-driven investments should not be viewed in isolation, but rather as part of a balanced portfolio that includes various alternative assets. By reducing the influence of the human element, emotions are removed from the decision-making process. This is particularly attractive at times when markets behave less rationally. Just as investors strive to reduce company-specific risk through owning portfolios of assets, AI-driven investments serve to reduce manager-specific risks and therefore have a place in a well-constructed modern investment plan.
*Sanlam Global Investment Solutions provides offshore investment solutions to wealth management companies and financial advisers for their international clients’ investment needs. The focus is on providing capital preservation solutions, primarily through an open-architecture investment plan domiciled in Bermuda.
