There is currently a lot of discussion about generative AI - a trending topic with the potential to significantly increase employee efficiency, especially in analytical and administrative processes. But in our view, this focus has fallen short.
While optimizing processes in the middle and back office areas, especially through the use of generative AI such as Large Language Models (LLMs), is currently the focus of attention in many companies, a fundamentally different question also arises in asset management: How can this be done? These technologies are used to increase assets under management through higher quality, more analytically sound, more predictive and more tailored services. Especially when it comes to supporting customers in the HNWI and UHNWI segment, the goal is rarely to be the cheapest service partner - but rather to be the best and most proactive advisor.
So let's take a look at the areas where data science and machine learning (or "real" AI, beyond the hyped language models) make a difference:
- Individualized investment strategies : AI can efficiently use large amounts of data to develop investment strategies that are much more precisely tailored to a customer's individual risk tolerance, financial goals and life stages.
In tandem with the emotional intelligence and personal relationships of a relationship manager, even higher quality solutions can be developed. - Improved Interaction : Through machine analysis of transactional data, asset managers can recognize or even predict their clients' evolving needs in real time, making interaction with the client richer and more proactive.
Atypical behavior patterns that arise at short notice for customer staff can therefore be used to improve interaction through individually tailored communication and advice. This makes clients feel better understood and more valued on their financial journey. - Predictive analytics for future planning : The predictive capabilities of data-rich AI also enable financial strategies to proactively adapt to life events, market changes and evolving financial goals, keeping wealth management services one step ahead.
Here, relationship managers can also learn from the strategies of other clients in similar life phases and situations based on numbers, data and facts. The understanding of customer behavior and demands thus loses its often static character and becomes dynamic in real time. - More customized customer segmentation : AI can also algorithmically support the process of defining customer personae, enabling the offering of specifically tailored services and investment options, thereby increasing customer satisfaction and loyalty. In addition to position and transaction data, information on customer behavior and digital preferences can also be taken into account in order to adapt not only the content, but also the type and channel of contact to the individual needs of the client.
The integration of AI into wealth management not only promises an overall increase in efficiency, but also opens up new dimensions of growth through improved quality customer service. In order to successfully embark on this exciting journey, asset managers should take the following basic strategic steps:
- technological foundation : The first step towards an AI-powered future begins with creating a robust technological infrastructure.
Invest in data analytics platforms and tools as well as the security of your systems that form the backbone of data-driven, personalized customer services. A solid platform that can efficiently process large amounts of data is key to meeting your clients' individual needs and offering them tailored investment strategies. - expertise : As is so often the case, technology alone is not enough.
The most important resource will be a team of experts who understand both the available technology and the markets relevant to asset management - and in particular have a deep understanding of customers and customer relationships. Train your staff in the basics of data science and promote a deep understanding of the possibilities and limitations of AI. The right mix of talent allows you to bridge technological innovation and world-class wealth management. - Partnerships and ecosystems: Open strategic partnerships with technology providers and FinTech start-ups to access innovation and foster creative exchange on evolving trends.
By taking these steps, you will position yourself at the forefront of innovation in wealth management. Not only do you create added value for your customers through personalized and predictive services, but you also redefine the future of wealth management.
Given the rapid developments in AI technology, we are on the threshold of a new era in wealth management. How might these innovations impact your investment strategies, and what ethical considerations should come to the fore as we use these new tools?
The future of wealth management with AI is not just a question of efficiency, but also of responsibility. We invite you to reflect and discuss with us the long-term impact of these technologies. The journey begins now – are you ready?