Navigating the future: AI’s impact on wealth management firms

In recent months, the financial services industry has witnessed significant advancements in artificial intelligence (AI), sparking both excitement and apprehension amongst wealth managers. While the potential benefits of AI are undeniable, the wealth management sector has been understandably cautious in embracing this transformative technology. This hesitation can be attributed to several factors, including a prioritisation of addressing critical gaps in services, concerns about client relationships, and the unique needs of different market segments.

In this blog, we explore the hopes and fears of integrating AI in wealth management, balancing the potential savings and efficiencies that can come from technological advancement alongside the concerns over an erosion of personalised client services.

Back office transformation

The potential for improved efficiency through AI and machine learning is substantial, particularly in areas like automating trade settlements, automating regulatory compliance, and risk management.

However, within the technology function of many wealth management firms, the primary focus often relates to implementing new traditional services and upgrades to address key operational gaps. Implementing non-AI solutions to enhance services such as regulatory compliance, Environmental, Social, and Governance (ESG), Customer Relationship Management (CRM), and digital services are typically considered more important and lower risk.

Because of the potentially significant benefits and the remarkable pace of change in AI, we believe that wealth management firms should put aside time and budget in 2024 to carefully evaluate the potential efficiencies and cost savings offered by AI, balancing these against the benefits of their current project portfolio. This assessment will help determine if prioritising AI integration is a strategic move that aligns with their operational goals.

Front office dilemma

We are starting to see the emergence of more AI-powered tools that can transform the front office experience for wealth managers and their clients. Early adoption of these innovations has the potential to allow client advisors and relationship managers to better serve “mass affluent” clients. Use of AI in this environment could combine the advantages of a human-led personalised service and advisor judgement with the scalability and insights that AI can provide.

However, implementation of AI in the front office remains a challenge. Securing funding to develop new AI capabilities requires proof of value to the organisation and clients. Wealth managers must also weigh up the benefits against factors such as data and integration challenges, evolving financial services regulations for AI, and the perceived lack of trust from clients in insights generated from AI.

Industry evolution

We believe a small number of early adopting wealth managers armed with AI capabilities are likely to start disrupting the industry at some point in the next year. Developing a strategy, plan, and business case for AI integration is important to avoid being left too far behind.

Key considerations

As wealth managers grapple with the prospect of integrating AI, some key considerations have emerged:

1. Early adoption dilemma: The decision to be an early mover or a follower with respect to AI in the wealth management market needs careful consideration of the associated risks and rewards.

2. Barriers to progress: For those who decide to invest in AI, there are some foundational elements that could act as barriers to AI progress if not addressed:

• Data governance and quality: Building a foundation of sound data governance and ensuring data quality is imperative for effective AI implementation. This discipline is important in any organisation but vital to get the best out of AI solutions.

• Robust data infrastructure: Modern platforms with adaptability to change swiftly are most suitable to form the backbone of successful AI integration.

1. Skilled resources: The availability of appropriately skilled individuals is critical for navigating the complexities of enterprise AI.

Conclusion

As the wealth management sector contemplates the role of AI, a delicate balance must be struck between embracing innovation and preserving the personal touch that defines many client relationships. While challenges exist, we believe that the potential rewards in terms of cost savings, productivity gains, and enhanced client experiences will make the journey towards AI integration worthwhile. Wealth managers should consider their strategy for when and how to look at the opportunities that AI can provide for them to ensure that they don’t fall behind their competitors.