The rise of AI has swept industries far and wide, and it has led to widespread innovation and disruption. In the wealth management sector, this has proven no different, with the sector evolving to meet the new demands created by AI.
According to Tamara Kostova, CEO of Velexa, the main focus of AI in wealth management has centered around the instant benefits wealth managers can gain from adding AI tools to their WealthTech stack.
“As illustrated also by industry awards the main use cases with measurable results evolve around relationship management, where wealth management advisors utilise AI to gain better personal insights on their client portfolios, risk appetite and historic decision making. This approach has led to an impressive 80% reduction in time spent on client portfolio reviews and consulting, allowing wealth managers to effectively service more clients and make their services accessible to larger audiences,” said Kostova.
While Kostova describes the above as an appealing use case for an individual financial services provider and their client base, the firm is more excited by future innovations that will impact end-investor experiences on scale.
She detailed, “For instance, on the financial education front, AI can be used to perform market sentiment analysis from diverse content formats like market news, social media posts, and videos. This market sentiment per company and/or financial asset class can be integrated into investing apps in the form of on-demand content for end-investors, helping to make guided financial decisions on a daily basis.”
A direction with ‘game-changing implications’ in the view of Kostova is the case of connected/unified investor data on a global scale.
She remarked, “By analysing vast datasets, GenAI would identify patterns and generate insights to support portfolio management and asset allocation strategies. Combined with AI models for optimising investment strategies to achieve specific financial goals, the outcome would be a highly personalised and automated wealth management plan for each individual. While the concept is not new, the challenge currently lies within fragmented and scattered data sets. A global and unified approach would require an industry-wide mindset shift and regulatory incentives.”
Beyond cold automation
In the view of Jurgen Vandenbroucke, managing director of EveryoneINVESTED, he likes to think of AI in the context of wealth management in terms of advice. “Can AI move beyond cold automation when it comes to generating tailored investment advice at scale?,” he said.
Vandenbroucke referred to Andrew Lo, a thought leader at MIT, who argued that in the context of wealth management, we need more artificial humanity rather than artificial intelligence.
Vandenbroucke remarked, “For many years, the wealth management business has been built on the notion of the cold, rational investor. To address the shortcomings of such an approach, and to recognise the human nature of the investor, many service providers are placing an advisor alongside the client. The challenge, says Lo, in delivering tailored investment advice at scale is to manage the emotional component of investing through technology.
“Yes, this means building digital processes and algorithms. But crucially, these algorithms should be better at understanding and anticipating human behaviour than the classic paradigm of rationality. I join Andrew Lo in applying insights from behavioural economics to improve the business contribution of digital investment processes. The pioneering work of Nobel laureates such as Daniel Kahneman and Richard Thaler is indeed helping us to refine our understanding of people’s risk preferences, to better understand the return distributions of products, and ultimately to build portfolios that people stick with by combining products in a way that matches people’s preferences.”
The EveryoneINVESTED managing director detailed that there are several reasons why he believed this has the potential to transform the wealth management business.
He explained, “First, success in digitising advice will help reduce operational costs, for example in dealing with the tidal wave of regulatory must-do’s. Greed for profit and fear of regulation tend to encourage change that improves. Second, and more on a missionary note, the success of digitising investment services will improve the chances of getting everyone invested and keeping them invested. Digitising the advisor and humanising the investor has a social impact by improving overall financial well-being.”
He continued, “A key element of success is trust. Investors should trust the model and, in particular, the advice it provides. Trusting the model is not a given. There is plenty of research documenting “algorithm aversion”, see for example a recent article in the Financial Times. The current research agenda of Lo and his team is, however, more focused on generating trustworthy output and developing AI that ensures the output is trustworthy.
“The criterion they use is that of “fiduciary duty”, the legal obligation of human advisors to make decisions on behalf of the investor and to put the investor’s interests first. The test for AI in the context of providing trusted investment advice is to pass the fiduciary test, so to speak. This means, for example, training the AI model on a dataset that includes all relevant regulatory requirements, lawsuits about things that have gone wrong, and so on.”
Many value-adds
In the view of Fredrik Daveus, CEO and co-founder of Kidbrooke, AI will continue to find more and more value-add use cases within wealth as the technology matures and the market gains more experience with this tech.
He said, “AI will continue to put natural language interface to and simplify sophisticated guidance and advice technology. This will broaden the appeal and lower the barriers to entry for inexperienced users.
“In addition, AI will improve efficiency as the tech is now so much better than the first wave of customer services bots and similar 5-7 years ago. Look, for example, at Klarna replacing repetitive and low skilled jobs at scale.”
Daveus also explained AI will start to gain entry into the recommendation and advice logic itself. “It will start to drive the execution flow of apps itself. Not just be a part of the interface. It apps internally ask AI to decide suitable paths of execution. This will impact the advice technology out there,” he said.
In addition, AI will be connected to task APIs and be able to execute tasks on behalf of users such as executing transactions.
He concluded, “Firms not adapting quickly enough will inevitable find themselves on a path toward irrelevance. The tipping point when an AI advisor will be more appealing than a physical one is getting ever closer. Once that tipping point is reached, we will see new business models emerging which is less about pushing product and more about satisfy real client needs,”
Revolutionary AI
Yohan Lobo, industry solutions manager at M-Files, believes that in 2025, wealth management firms will embrace knowledge work automation platforms to streamline back-office processes such as document management and data analysis.
“This will enable wealth managers to dedicate more time to high-touch client interactions and strategy development, reducing the manual workload that currently hinders service and productivity,” said Lobo. “Tribal knowledge, ringfenced in silos of experienced advisors, can be unlocked and made reusable, helping more advisors help more clients. By enhancing operational workflows, wealth firms will be able to offer clients more timely, personalized advice while improving cost efficiency across their operations.”
In addition, Lobo believes that wealth management firms will increasingly rely on AI to not just react to client needs but also to predict them.
He described, “By analysing past behaviors, market trends, and financial goals, AI will enable wealth managers to offer proactive advice on investment opportunities, portfolio adjustments, and risk mitigation strategies. This predictive capability will empower advisors to anticipate market changes and advise clients on actions before those shifts occur, strengthening client relationships and enhancing long-term wealth management strategies.
“GenAI tools that operate with a new level of autonomy, often referred to as Agents, will become increasingly interesting to the wealth management industry. Agents could eventually develop to monitor advisory work to ensure regulatory compliance or identify process challenges and suggest improvements that increase productivity.”
Lobo also predicted that wealth management in 2025 will see a democratisation of financial advice, due to AI-driven tools that will open up automated – yet personalised – investment advice to more people.
He remarked that mass affluent clients will have access to increasingly sophisticated, AI-powered advisory platforms that offer personalised reccomendations based on risk tolerance and financial goals.
“This trend will make wealth management more accessible to a broader demographic, enabling firms to expand their client base while maintaining high-quality, customized services,” said Lobo.
Lobo concluded, “Wealth managers continue to enhance their self-service offerings through AI-powered chatbots and virtual assistants. Wealth managers will use AI-driven tools to offer clients self-service access to portfolio tracking, investment adjustments, and financial planning. This will increase customer empowerment and provide firms with valuable data on user behaviors, helping them tailor services more effectively.”
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