The rise of the robo-advisor

AI is poised to revolutionise the banking industry in several ways: through stronger fraud prevention, increased operational efficiency and improved data-driven decision making. But one area has particular significance for consumers: the increasing use of robo-advisors, AI-powered financial planning services that offer consumers advice about investments.

Consumers use robo-advisors principally for investment portfolio management. To start, they outline their goals, which could be minimising tax liabilities or saving for retirement, and confirm their preferred investment criteria, including their risk tolerance, financial goals and investment horizon. The system then automatically creates a diversified investment portfolio based on these choices and manages the portfolio over time to maintain the optimal allocation of assets as market conditions and as the customer’s investment horizon changes.

By integrating generative AI into their processes, robo-advisors can offer hyper-tailored investment strategies that align with an individual client’s unique circumstances and life goals, and not only for standard retail clients but also for high-net-worth individuals. These advances have reinvigorated the robo-advisor market, which reached peak hype ten years ago, but which at the time delivered disappointing results. It is the use of AI that has delivered the highly personalised engagement that is driving the success of today’s robo-advisors.

The benefits of automated advice

Of course, a competent human advisor can do all the things robo-advisors deliver. And an automated system, even when powered by AI, may well be less good at responding to the nuances, and perhaps less-than-clearly expressed goals, of individual customers.

So why do people use robo-advisors when humans are perhaps a more natural choice? This is a question that providers must be able to answer.

Privacy is one issue. Some people are uncomfortable talking to a human about money; a well-designed robo-advisor can offer good advice while at the same time avoiding making the customer feel they are being judged for their financial choices.

Security is also important. Technological defences such as encryption and multi-factor authentication are available to AI-powered systems, enabling them to protect sensitive financial information. In contrast humans are, perhaps inevitably, leaky.

Cost efficiency is another clear advantage. Robo-advisors typically charge lower fees, around 0.25 per cent to 0.5 per cent, compared with traditional human financial advisors, who will normally charge between 1 per cent and 3 per cent. For someone investing, say, £5,000 a year for 40 years into a pension fund, the difference between paying fees of 0. 25 per cent and 3 per cent can be the difference between scraping by at the age of 70 and living in relative comfort.

One reason for these lower fees is that updating an online system with new rules and market trends is much less costly than preparing and rolling out new information to a team of human advisors and then checking that they understand it. In addition, most robo-advisors do not require a minimum investment because there are no major client set-up costs, allowing people with smaller amounts of money to start investing.

Convenience is yet another advantage. Users can access their accounts and manage their investments at any time, night or day, without having to schedule appointments with an advisor. Especially for people interested in investing in overseas financial markets, this can be a substantial advantage. In addition, portfolios managed by a robo-advisor are continuously monitored 24 hours a day, and adjusted as needed to stay aligned with the user’s goals and risk profile. A single human advisor will be unable to offer this level of service.

Perhaps counterintuitively, investment effectiveness will not always be an advantage for robo-advisors. It’s true that AI-systems can instantly access and analyse huge quantities of financial data and that they are less prone to human error, or to the biases and emotional drivers such as greed or fear that affect most humans. This can mean that for simple strategies such as market tracking, using a robo-advisor can be very effective.

However, more complex and speculative strategies, a good investment manager should be able to understand the cause of market swings, and react to them, while an AI system will only be able to know that those swings are happening, but not why. And ultimately robo-advisors are constrained by the “philosophical” parameters around risk tolerance and the like that the user has programmed into the system. In reality, therefore, in some circumstances a robo-advisor will outperform a human; in others, the human will win.

Challenges and limitations

It is not always simple for a consumer to choose between using a human advisor and a robot advisor. Considerations will include the amount of advice the consumer wants to have, their confidence with technology, the amount they have to invest, and even their investment strategy (more exotic strategies may be less well caterer for by automated systems).

Providers therefore need to understand the challenges of persuading consumers to use a machine rather than a human.

The primary challenge is the lack of human interaction when using a robo-advisor. Some customers will miss the personalised interactions that comes with human advisors, particularly for complex financial situations where they may want to ask multiple questions. In such circumstances, a human may provide more trusted advice than a machine. The emotional support that a human can provide may be particularly important during a time of market turbulence, when a human advisor can provide a calming influence and a long-term perspective that robo-advisors lack.

In addition, any digital system will almost inevitably be optimised for the most common situations. Clients with complex financial needs, such as inheritance planning or managing variable income streams, may not be well served by an automated approach. While robotic systems generally offer a degree of portfolio personalisation, the level of customisation may not match that provided by human advisors who may even have access to opportunities that are unavailable through normal online channels.

Taking action to improve outcomes

The challenges that robo-advisors face come down largely to one thing: consumer trust. Trust that the user is making the right decisions, has access to the best information, and is doing things correctly. Robo-advisors can enhance their trustworthiness by focusing on several issues including transparency, compliance, and customer support.

Transparency is perhaps the most important driver of trust. As well as explaining how the AI algorithms operate in a clear manner, robo-advisors should provide detailed information on all fees, and costs, ensuring there are no hidden charges. There should never be any nasty surprises.

Customer support is also critical. Multiple channels should be provided so that users can access their preferred means of communication, whether that is email, web chat, a comprehensive FAQ or even a human at the end of a phone line. A large part of customer support is ensuring customers have the right information on which to base their decisions. This can be achieved by providing educational materials, including opinion pieces and tutorials (using text, video and interactive methods), to help users understand investing principles.

Another important consideration is ease of use. It’s essential that any automated system provides its users with an intuitive and simple to learn and use interface. It should be simple for consumers to set up accounts, define their goals and start investing. And online systems should also be available via the web and via mobile applications, so that investment customers can access and manage their portfolios no matter where they are.

Finally there is compliance with regulatory and security requirements and ethical frameworks. For it to generate trust, compliance needs to be promoted to end users, for instance by using logos of standards and information about compliance status on the website. Ethical frameworks that guide the organisation should be described and where possible proved, for example by the publication relevant policies.

The future of robo-advice

Banks are increasingly offering robo-advisory services, often integrating them into their offerings and providing a hybrid model combining digital and human advice. And the digital part of this advice will only get more powerful over time. As this happens, robo-advisers will become better placed to extend into new services such as budgeting tools and debt management. This will be a powerful way for banks to increase the loyalty of their customers.

Banking robo-advisors represent a significant advance in financial technology. But while they offer numerous benefits, they also introduce challenges around the lack of human interaction and the ability to manage complex financial needs. If banks are to succeed in promoting automated advice to an ever-wider section of their customer base, they will need to accept the limitations of this exciting technology and to strengthen the trust consumers have in the ability of machines to protect and grow their money.