How AI will transform employee and client experiences in wealth management?

By Yohan Lobo

Although topics such as inflation, market volatility, and interest rate mayhem are top of mind for most wealth managers, the evolving AI revolution is making the industry stand up and take notice.

But forward-thinking wealth management firms aren't necessarily asking the typical headline-making questions: Will AI take my job? Can we trust AI? Will AI take over the world? Rather, firms are asking: How can we leverage AI to create a superior client and employee experience?

According to a PwC survey, nearly 90 percent of wealth managers "believe that the use of disruptive technologies (including big data, AI and blockchain) will lead to better outcomes." But how will AI really help advisors, clients, and wealth management knowledge workers? The answer starts with connection.

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Re-connecting clients

The reality for a financial advisor in today's world of increasingly complex compliance issues and technological disconnect is that time spent advising clients is shrinking.

A report by McKinsey, shows that relationship managers are spending up to 70 percent of their time on non-advisory activities, including servicing, admin, and regulatory compliance—time better spent advising and interacting with clients, as well as generating revenue.

How do firms find themselves in such a less-than-productive spiral? In many cases, firms lack a unified platform—multiple systems for client information and analytics leads to information chaos and repetitive work.

In addition, firms with a high level of manual data processing end up stuck in a never-ending cycle of drudge work that leads to dissatisfied workers and neglected clients.

Clients expect interactions to be convenient, flexible, instant, and personalized — a tall order to fill when advisors spend so much time on non-advisory tasks. A knowledge work automation platform with AI can help automate workflows and can "learn" to find meaning in data from previous experiences, churn through a vast amount of information and recognize categories and patterns in data.

For managers, this means a reduction in low-value work. AI systems can observe how, what, and when users access information and provide insightful guidance the more the system's used over time.

Getting personal

As machine learning solutions get "smarter" by processing more of a firm's data, they learn how to provide personalized solutions for clients such as:

  • Onboarding: Hyper-personalized targeted offers based on client segment and demographic analytics
  • Portfolio: Propensity modelling based on client behavioral data such as spending or having habits.
  • Content in context: Machine learning and AI supports the creation of workflows that ensure that the right information is available at the right time.

By leveling up personalized service, wealth-management clients see immediate results—products and services designed and built based on their individual needs. The right product at the right time.

Improved process efficiency = happy employees

Powered by AI, a knowledge work automation platform can make daily work more rewarding—searching, managing, and using information gets faster, allowing front, middle, and back office teams to focus on outcomes and objectives rather than manual drudgery.

AI reduces time spent on manual tasks, knowledge workers don't have to think about where information should be kept—the platform automatically recognizes what the data is, what it relates to , and creates the relevant workflow. Who wouldn't want to work in that kind of office?

Staying safe, staying compliant

With an AI-fueled solution, wealth managers implement security measures and regulatory changes into templates, documents, and workflows through automated categorization. Correctly categorized documents are simple to analyze, review and audit, keeping workflows and processes under control, as well as preventing data leakage. Secure portals can be created that share, receive, and approve sensitive information without e-mails. Automated information retention policies are simple to implement ensuring manual compliance activity is minimized.

AI regulation has moved from a niche topic into the mainstream with both the US and EU setting out their vision of how this technology can be harnessed by society in the right way. Whilst this will have a bearing on how wealth management, and the wider financial services industry, is regulated, it won't change "What" is regulated. Regulation will continue to focus on client outcomes and the suitability of advice and products.

For example U.S. President Joe Biden recently signed an executive order while the EU passed new legislation demonstrating how serious governments are taking AI growth across all industries.

Other regulatory advances include:

  • The European Commission recent agreement by G7 leaders to release Principles on AI as well as a voluntary Code of Conduct.
  • As of December, around a dozen American states have passed AI legislation with more states introducing legislation in 2024.
  • As noted in a recent Reuters article:

"At the federal level in the US, the proposed American Data Protection and Privacy Act outlines rules for AI, including risk assessment obligations that would directly impact companies developing and utilizing AI technologies. The bill, proposed more than a year ago, remains stalled in Congress. The US government also has issued guidance through the National Institute of Standards and Technology (NIST), such as the AI Risk Management Framework and the Secure Software Development Framework."

One thing is clear for wealth management firms—while regulations may change due to emerging AI, it will still be up to individual firms and advisors to be responsible and accountable for client outcomes. Firms must always be able to explain and evidence why any given advice was given and if the client understood that advice.

The AI crystal ball

As AI solutions gain a deeper understanding and can better classify available data within a firm, they can begin to move from classification to prediction—generating new and actionable information to grow a wealth management firm's client base.

Employees can use assistive AI tech to ask targeted questions about documentation or summarize documents to help confirm trade execution. In addition, managers can grow their prospecting base by using AI to harvest predictive data—industry data, social media, markets/target demographics, and key
contacts at firms.

As the above-noted PwC report reminds us, wealth managers must choose wisely with future tech investments "to continue to adapt to evolving investor needs and market conditions, while also addressing the shift towards more personalized, digital-first solutions."

"Firms that can effectively leverage technology, build meaningful inroads to new and existing customers, and deliver exceptional client experiences will be well-positioned to thrive in this rapidly evolving landscape."