The Robo-Adviser: Can an Algorithm Guard You from Yourself?

A gap called behaviour

Each year Morningstar measures the difference between what a fund earns and what its investors actually earn. In its latest report on US funds, investors earned 8.7% a year over the decade ending 2025, against 9.9% for the funds themselves: a gap of 1.2 percentage points every year. The study attributes the gap to the timing and size of purchases and sales, and notes that it does not necessarily mean poor behaviour, since regular investing and rebalancing also produce one. The gap was narrower in asset-allocation funds (7.8% against 8.4%).

These are American market figures and should not be carried over literally to other markets. But they show that the owner's timing affects what the owner earns. For the newer financial agents that follow the robo-adviser, see the article "Would You Trust an Algorithm With Your Savings? Financial Agents Examined".

Why do we mistime? The human psyche is a plausible culprit. In a 1992 paper, Daniel Kahneman and Amos Tversky estimated the median value of the "loss aversion" coefficient among participants at 2.25: a loss stings about two and a quarter times as much as an equal gain pleases. Kahneman received the Nobel Prize in Economics in 2002 for work done with Tversky, who had died in 1996.

Linking this tendency to the return gap is a reasonable explanation rather than direct proof; the financial study measures behaviour, not its motives.

What does a robo-adviser promise?

A "robo-adviser" is a platform that builds a diversified portfolio according to the risk profile the user sets, then rebalances it under declared rules. By definition, periodic rebalancing sells what has risen and buys what has fallen, which is often what instinct recoils from. It spares its owner the moment of decision, when emotion runs highest.

None of this guarantees a return; a portfolio can lose along with the market. The advantage is discipline in execution, not a prophecy of prices.

When machines resemble one another

Regulators warn of the other side of discipline. In 2017 the Financial Stability Board (FSB) noted that many participants relying on similar tools and data could create correlated risks, and that such herding "has the potential to amplify financial shocks". It added that concentrated reliance on a few providers could create shared points of failure, and that opaque models that are hard to audit could become a risk at the level of the whole system.

It takes no genius to see why: a model trained on years of rising markets may underrate the possibility of a fall, and err calmly and confidently, leaving the user no tone of doubt that would prompt a pause.

What Saudi Arabia's Capital Market Authority decided

On 5 March 2026 the Capital Market Authority announced that its board had approved a draft of rules for robo-advisory services, following trials by licensed firms in the regulatory sandbox. The draft provides that the service be offered only through licensed entities; that the Authority be notified in advance of portfolio-construction strategies and their updates; that algorithms be tested periodically, at least ten days before clients gain access; and that the role of the algorithms and their associated risks be disclosed. The report's headline speaks of approval while its details speak of a draft, so it is wise to consult the Authority's final text.

These proposed safeguards answer the concerns above: licensing clarifies responsibility, disclosure eases opacity, and testing limits silent error.

Four questions before you trust

• Who licenses this platform? Do not hand your money to a body whose supervisor you do not know.
• What does it do when the market falls sharply? Ask about the logic of its recommendations before you need it.
• What is the full cost? It goes beyond the advertised fees to what the platform collects from your data and how it uses it.
• Do the proposed products observe Sharia guidelines? And have you consulted a licensed professional? What appears here is knowledge and a framework for understanding, not a buy recommendation.

Taking precautions with money is part of trustworthiness: understand a tool before relying on it, and keep the big decisions, such as the level of risk you accept and your life goals, in your own hands.