Exploring the adoption challenges and strategies for robo-advisors
Meral Ahu Ozcan Karageyim, an Academic Associate at ICD Business School, delves into the transformative potential of AI-based social robots, particularly robo-advisors, within the financial industry, addressing the challenges they face and proposing innovative strategies to enhance their adoption.
Meral Ahu Ozcan Karageyim, an Academic Associate at ICD Business School, delves into the transformative potential of AI-based social robots, particularly robo-advisors, within the financial industry, addressing the challenges they face and proposing innovative strategies to enhance their adoption.
As technologies continue to develop, social robots are becoming increasingly popular in various industries, including retail, health, banking, tourism, services, entertainment, communications and media. Service robots are system-based, autonomous and adaptable interfaces that interact, communicate and deliver services to customers, employees and/or other (service) robots. Many people already interact with social robots at home (Siri, Alexa) or in working environments. Social or humanoid robots interact, engage and co-create value with customers in service. AI-based social robots are transforming service industries in one way or another. As these robots are also becoming more common in the financial services industry, let’s take a look at their transformative power and the challenges involved in their adoption.
Currently, social robots are becoming increasingly advanced owing to the latest technological developments. In addition to their mechanical skills, they use impressive analytic, intuitive and social skills for better service. Therefore, it may be useful for financial service providers to use these social robots, chatbots and robo-advisors because they offer productivity and efficiency, and may enhance customer experience. So, the big question seems to be, “How are these remarkable developments of AI-based social robots perceived by customers?”
Despite claims that AI may revolutionize the service industry, scientific evidence proves that customers are reluctant to use social robots in almost every industry. They do not prefer to follow the health, tourism or retail recommendations provided by social robots. The same seems to be true for financial services with robo-advisors. This reluctance can be explained by more than one factor. It’s partly because financial products are complex and financial market conditions are volatile.
Robo-advisors may offer transparent and unbiased financial advice and services at a low cost. However, financial advisors with high expertise can reduce customer anxiety. Why? Why do clients prefer human advisors? There are a number of factors behind this, but trust has emerged as the main reason. Customers prefer to talk to human advisors before making their investment decisions. Marketing literature provides sufficient evidence about this preference. Several studies comparing human advisors and robo-advisors reveal that customers prefer human financial expertise. One study conducted by Zhang, Pantina and Fan (2020) underlined that bank customers trust human financial advisors more and expect better performance from these financial advisors than robo-advisors.
However, this service is expected to grow owing to several advantages. As mentioned, robo-advisors provide unbiased investment ideas at low cost. This is a reachable service twenty-four hours a day for small investors. According to Statista, the number of robo-advisor users is projected to exceed 234 million by 2027. The average assets under management per user in the robo-advisor market are expected to amount to more than US$8,000 in 2023. Thus, we should also discuss effective strategies for robo-advisor adoption. How is it possible to overcome investors’ reluctance to use such fast-growing services?
First, building trust is essential for the adoption of robo-advisors. Banks and other financial institutions should focus on financial strategies that increase trust perceptions. Transparency may be another strategy to achieve better adoption. Explaining the decision-making processes of algorithms used by robo-advisors or the reasons for investment ideas could be useful for better customer engagement and trust perceptions. Using other investors’ comments and ideas about the service could also help in the acceptance of robo-advisors.
The second strategy is the use of anthropomorphic robots for advisory services. Marketing studies have found sufficient evidence for the impact of anthropomorphic cues and robots on building trust and engagement.
A hybrid model has also been suggested for better engagement and adoption. This model, which includes human contact and interaction with specific questions, could also foster emotional trust. Marketing scholars and practitioners suggest such a hybrid service model, arguing that some financial products may be too complex, and that collaboration between robo-advisors and human advisors may also be attractive for young investors.
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