Making Investment Decisions with AI

Key Takeaways:

• 1. Artificial intelligence can handle large volumes of data, and different types of data to pull insights that inform investment decisions
• 2. The goal of an AI-driven investment strategy is essentially the same as a traditional quantitative investment strategy - to find strong relationships between elements of data and future asset returns and exploit them
• 3. Robots will not replace investment managers, as they can leverage data and professional expertise to bring more value to investors.

Artificial intelligence (AI) has kickstarted significant changes across many industries. From the development of robotics in manufacturing to driverless cars on the road, the potential for its application is limitless. This begs the question: what can it do for investment and fund management?

Ben Dunn, Head of Quantitative Solutions Group at Eastspring Investments, believes that the potential of AI in investment is in allowing much larger volumes as well as different types of data to be used to inform investment decisions and potentially improving on the interpretation of that data in investment decision-making.

Ben Wicks and Mark Ainsworth of Schroders' Research Innovation and Head of Data Insights, Investment, respectively concur. In their white paper Harnessing the Data Science Revolution, they write: "The proliferation of information available for investment research is a profoundly disruptive force… the injection of new, and potentially unique, methods of data analysis into existing investment processes should enhance long-term alpha generation."

But can AI and big data deliver on their promise?

How technology can support investment decisions

AI and data can be used to find trends and insights that support investment decisions. By analysing large amounts of data and applying advanced algorithms, AI can identify patterns and trends that would be difficult for humans to detect.

The underlying goal of a purely AI-driven investment strategy is essentially no different from that of a traditional quantitative investment strategy - "That is, to find strong relationships between elements of data and future asset returns and exploit them," according to Dunn.

However, Dunn adds: "The AI-driven approach to finding these data relationships differs in that they tend to be entirely driven by data (evidence) and do not require upfront rationale or intuition from the analyst."

Dunn believes that this purely data-led outcome is both the greatest strength and the greatest challenge of AI techniques: "Machine Learning models can derive unique insights from the data that may not have been considered by a quantitative analyst working with the same data. But it can also identify relationships in the data that are spurious or temporary."

He adds that this is one of the reasons that the "Man + Machine" approach is more commonly pursued by the investment industry to date.

What does it mean for you as an investor?

By continuously monitoring and analysing a wide range of data sources, including market prices, economic indicators, and news and social media feeds, AI and data analytics can provide investors with up-to-the-minute insights into market trends and conditions.

This can help investors make more informed decisions about what and when to buy or sell, and can help them identify opportunities and risks that may not be immediately apparent.

Source: Eastspring Investments.

Wicks and Ainsworth agree on a dual "Man + Machine" approach, concluding that an active investment decision is a function of several factors: "A fund manager who has excellent information to hand and who is able to form a coherent but differentiated view, drawing inspiration from a broad range of sources at the appropriate time, is likely to generate good performance."

Another way that AI and big data can support investment decisions is by providing personalised investment advice. In analysing an investor's individual circumstances, goals, and risk tolerance, a platform can generate personalised recommendations for portfolio allocation and diversification.

We see this with robo-advisors where portfolio recommendations are generated by algorithms based on the investor's investment goals. In contrast, with an actively managed fund, the investment decisions are made by experienced fund managers based on their expertise and investment strategy.

With a dedicated personal relationship manager, he or she can take the time to fully understand an investor’s individual circumstances which may change at different stages of their lives, to build portfolios that are tailored to their specific needs and goals, and can help them maximise their returns while minimising their risk.

Furthermore, relationship managers have access to cutting edge tools that can help investors make informed decisions. Citi clients benefit from the Citi Wealth Analysis Dashboard, while Citigold Customers have access to the Total Wealth Advisor Tool, which can provide a comprehensive picture of client’s goals and analyse their financial situation,to help them achieve their aspirations.

Citi’s Relationship Managers can also make use of the Citigold Diversification Index (CDI) tool, to assess how diversified one’s portfolio is, giving customers greater insight into their portfolios and helping them be more informed on their investment strategy.

Having a relationship manager also means more transparency and accountability in the investment process. Not only do you benefit from years of professional expertise, you also can get regular updates to understand how your money is being invested.

Hence, it appears that investment managers will not be replaced by robots yet. In the new age of AI, investment managers will be able to make use of new and rapidly growing sources of data. Coupled with portfolio construction and risk management skills, this will help active managers add alpha for investors.

From helping you build your wealth to protecting your assets, our comprehensive suite of world-class products offers solutions for every wealth management objective. Speak to a Relationship Manager today.

Sources: Quantitative Investing Meets Machine Learning by Eastspring Investments and Harnessing the Data Science Revolution by Schroders.

Disclaimer:

This article is for general information only and is not intended to be a forecast of future events nor a guarantee of future results and should not be relied upon as financial advice. All views and opinions are as of the date hereof, and are subject to change based on market and other conditions without notice. The article has no regard to the specific objectives, financial situation and particular needs of any specific person. It is neither an offer nor a solicitation to purchase, nor endorsement or recommendation of any products or services mentioned therein, and the products or services mentioned may or may not be offered by Citibank Singapore Limited, its related entities and their respective directors, agents and employees (together "Citigroup").

This article and its contents do not constitute the distribution of any information or the making of any offer or solicitation by anyone in any jurisdiction in which such distribution, offer or solicitation is not authorised or to any person to whom it is unlawful to distribute such information or make any offer or solicitation.

Citigroup is under no duty to update this article and shall not be liable for any complaint, suit, action, claim, expense, loss or damages directly or indirectly arising out of or in connection with any person’s reliance on, or acting upon, or use of, any contents on this article. The article is subject to amendment without notice. Investment Products are (i) not insured by any government agency; (ii) not a deposit or other obligation of, or guaranteed by, the depository institution; and (iii) subject to investment risks, including possible loss of the principal amount invested. The information contained herein is not intended to be tax or legal advice, or an exhaustive discussion of the strategies or concepts mentioned herein. Please seek advice from your tax, legal or financial adviser as appropriate about the contents discussed herein or before investing in any investment products. Should you choose not to seek such advice, you should carefully consider the risks associated with any investments and make a determination based upon your own particular circumstances and assess whether such investment product is suitable for you.