Using AI to tap into income

It's time for investors to think differently about income. For those looking to tap out of cash, the appeal of stable and consistent monthly distributions with the potential for upside is growing.

Stocks can play an important role in filling this gap. Notably, there are huge opportunities in established companies with strong balance sheets, growing earnings and a history of paying dividends to shareholders. But identifying this blend of attributes among thousands of these equities globally is easier said than done. Enter the power of AI.

Here, Robert Fisher, Senior Portfolio Manager within BlackRock’s Systematic Active Equity team, explains how AI is an effective solution to a pressing problem.

How do you see the rate-cutting cycle impacting traditional cash returns, and what’s the impact for income-hungry investors?

Currently, savers across Asia are relying heavily on cash savings and bank deposits to fund expenses like mortgage payments and school fees. But once the illusion of returns from two years of high interest rates fades due to rate cuts, things will soon feel out of sorts.

Even with relatively higher rate levels likely to continue, cash can’t keep up.

In short, inflation and potential interest rate cuts are eroding the ability of cash to deliver income – which means that iinvestors need alternative ways to achieve their target income.

How is AI being used to uncover income opportunities?

To create more predictable investment outcomes, our team uses an approach called “systematic investing”. This combines powerful data-driven insights, investment science, and disciplined portfolio construction to modernize the way we invest. By applying this approach, we’re able to unlock new ways to seek consistent outcomes amidst a world of unpredictability.

The process begins with data-driven insights. By using machine learning and large language models – forms of AI – we can assess a universe of over three thousand securities every day.

We use a vast range of signals to help identify alpha (and income) potential – from assessing online influencers to determine trending products among consumers, to analysing social media posts across different platforms and languages to evaluate investor sentiment. We can also use AI to spot early red flags in documents companies exchange with regulators, which might indicate potential negative impact on shareholder value.¹

The result? A bedrock for portfolios to mitigate the ups and downs which are inevitable in today’s markets.

Specifically for income-seeking investors, we’re able to use AI in our investment process to be better-informed when it comes to forecasting returns and trying to generate higher levels of stable and more consistent income over time – and at lower levels of risk and with enhanced diversification characteristics.

How are investors thinking differently about income when it comes to dividends? Does AI have a role to play?

Over time, dividends have played a meaningful role in boosting investors’ returns. But dividends also represent a diversifying source of income, offering three major benefits.

Firstly, they add resilience to portfolios. Companies with lower debt and higher profitability tend to be more mature, higher quality companies. That means they tend to maintain their earnings growth through market cycles.

Secondly, they mitigate potential losses from falling stock prices. Historically, stocks that have grown or maintained their dividends have outperformed stocks that haven’t paid or chose to cut dividend payments. Dividend-paying stocks may offer a cushion to help offset the unpredictability of equity markets in the short-term.

Finally, they can achieve recurring income. Inflation can erode investors’ total return if there is no dividend yield contribution to dampen the impact of the reduction in purchasing power of investor capital.

Equity sources of total return - last 12 months

Having said that, as with all investments, diversification within assets and instruments is essential. Dividends are no exception. Too narrow a focus on certain types of dividend-paying stocks can weaken an investor’s portfolio.

This is where AI plays a critical role. For example, we can use AI to help address the risk from a variation in yields from market to market and across sectors.

This can be seen in the banking, consumer staples, and utilities sectors, where stocks are typically well-represented in equity dividend strategies, but also tend to be established companies that offer lower growth potential. What’s more, dividend yields for the S&P 500 Index have fallen relative to their peaks in the early 1980s.

U.S sector sources of return - year to date

AI also enables investors to keep up with the wide range of dividend payment dates and frequencies from one country to the next. For instance, while companies in Canada and the US tend to pay quarterly, in Australia, Japan, South Korea, and the UK it’s more common to see semi-annual dividend payments. Meanwhile, annual payments are the norm among dividend-paying stocks in Continental Europe. The timing of all these payments is important, and investors need to know the months or seasons in which they can expect their income.

Can you share a real-life example of AI helping your income-investing clients?

Investment strategies powered by AI offer investors a brilliant way to identify trends and shifts in the health of a company, along with the future likelihood of it paying – and growing – dividend payments. Augmenting traditional data also helps to navigate dividend payment dynamics across industries and countries.

Rather than just buying and holding onto value stocks that are paying dividends, our team is using data to identify companies exposed to high growth in the near future, which are more likely to generate higher earnings. So, while they might not be the highest dividend paying stocks, they can deliver very high capital growth to a portfolio.

The success we’ve seen with that approach is a testament to the value of blending the power of machines and alternative data with insights from human experience.