Advances in AI technology mean robo-advisers can offer a more personalised service and therefore build trust and engagement with investors, argues Reginald Warlop.
With its low costs, ease-of-use, and 24/7 accessibility, the arrival of robo-advice was once heralded as a revolutionary method of providing investment advice.
Yet, while more than a decade has passed since these algorithmic agents came to the fore, user surveys continue to show that most customers remain reticent to embrace robo-advice. It has become increasingly clear that a lack of human touch and empathy has limited the realisation of the technology’s true potential.
However, new technology designed to ‘humanise’ the automated transaction process may prove the necessary catalyst to driving greater adoption and acceptance of these robo-advisers. Recent artificial intelligence (AI) innovations enable more tailored, understanding, and authentic interactions between robo-advisers and customers. The age of interactive and accessible robo-advice has finally arrived.
Conversational communication
The rise of natural language processing (NLP) is central to these step-changes. In the past, robo-advice digital services generated one-size-fits-all generic questionnaires, designed to formulate a brief list of ready-made funds for potential investors to choose from. With NLP, robo-advice tools can now decipher the investor’s input and form a more fleshed-out understanding based on the tone and full picture of their preferences.
Today’s robo-advisers develop a more contextual understanding and deeper insight into the user’s intent. Mapping this data to the model’s programmed knowledge of wealth management strategies allows for more personalised, authentic and effective communication, putting the client at ease while adhering to necessary regulation.
Using this technology, digital assistants can go beyond standard, static questionnaires, towards a more conversational interface. Users can expect clear, simple responses directly addressing their questions; chatbots can also enable financial institutions to ask targeted questions based on their responses to gather the necessary information required to formulate a wealth management plan.
Take, for example, Key Investor Information Documents (KIIDs), which provide critical information about a fund. Rather than presenting users with a typical pdf-format report, a conversational interface, powered by generative AI, can draw upon thousands of previously existing KIIDs to help explain fund categories, asset allocation, and investment strategy in simple language.
This can help alleviate challenges that many customers face when digging through tables of data to evaluate available choices and create a more natural experience.
Data and behavioural finance
The enhanced capacity for natural language communications means NLP is also useful in back-end data analysis. For example, financial institutions can employ these tools for sentiment analysis to uncover useful insights from their large stores of customer data. Providers can gain a better understanding of the content, as well as the emotions behind their clients’ communication and thus update their products and responses to address issues accordingly.
Moreover, AI-enabled robo-advisers can pick up and record the user’s knowledge and experience in investing. For example, by analysing financial decision-making across various risks and outcomes, they can come to a more accurate judgement of a client’s genuine risk appetite. As the data grows, this reinforces the model’s effectiveness, narrowing the gulf in communication between a human and robot wealth adviser. Combined, NLP and AI can make strides in behavioural finance applied to wealth management.
A human-centred approach
AI can also help robo-advisers communicate with customers in the most effective and convenient way. For example, over time, the data collected can help the agent understand whether certain clients prefer to receive information over email, or in an attached pdf, and what time of day they are most likely to read about their investments.
The human touch can be further enhanced by consistently offering help and advice to investors. Scheduling regular reviews, providing frequent portfolio updates, and maintaining continuous investor profiling are just a few ways that wealth management firms can use robo-advisors to remain responsive to their customers’ developing requirements and preferences.
At last, robo-advice powered by AI is poised to disrupt wealth management. Increased technological sophistication means these advisers are more capable of building trust and engagement. This will ultimately free up time for human advisers to focus on solving distinct issues for customers and to deliver new opportunities and additional value to their customers.
Reginald Warlop is partner at Atomic Reply
