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An Accenture study found that “9 out of 10 financial advisors believe AI can help grow their book of business organically by more than 20%.”
But the question is – how will the impact on wealth management take shape?
A few years ago there was much fanfare made about robo-advisors, with some predicting that they would replace human advisors in certain situations. A few years on, the reality is proving to be quite different. While robo-advisors and similar tools will have a role in wealth management, their impact is always going to be in a support context alongside human expertise.
AI in wealth management
Sometimes with trends (as with robo-advisors), it’s difficult to tell if it’s a fad or if it is here to stay. When it comes to AI – particularly Generative AI – it looks like the technology is here to stay.
Almost all traditional approaches in the industry can be impacted or enhanced in some way.
Whether assessing financial risks, providing investment advice, detecting suspicious activities, or aiding in financial planning or strategic decision-making, AI-driven insights will certainly improve performance.
There are big expectations on the client side as well, with 68% of investors expecting their digital experiences to match leading technology companies. This will inevitably impact client behaviors, further driving the need for AI.
That’s not to say that human advisors will be replaced. Instead, the trend is moving towards the interplay between human intelligence and Artificial Intelligence, with AI able to draw on vast amounts of data to connect the dots between human-centric processes.
The result for advisors is that they can reduce the number of routine tasks they have to deal with. This will allow them to be much more engaged in the human aspect of their jobs – while dramatically improving their efficiency.
Achieving this experience involves empowering the wealth advisor.
Generative AI use cases for wealth managers
What kinds of efficiency use cases will be available?
Client onboarding
Client onboarding in wealth management firms often represents a point of friction in the client journey, and one that is particularly important as it comes so early in the client relationship. There are AI tools that can make this process more efficient and pain-free.
Automated security processes
For example, AI-enhanced know your customer (KYC) and anti-money laundering (AML) can automate the process of verifying identities and detecting fraud.
Beyond adding an extra lay of security and reducing compliance risks for the organization, it offers a more streamlined journey for the client.
Document processing and reporting
AI tools have reduced the time spent reviewing files by 50% according to a report by the BCG. This is thanks to automated document processing and reporting tools that extracts data-driven insights from financial statements, contracts, and regulations, which greatly eases routine tasks for advisors during onboarding and after. Beyond simply helping with administrative tasks, it can also play a significant role in helping inform investment decisions.
Quick access to advice
Generative AI is most powerful when it is aligned properly with an organization. As it can draw on the wealth management firm’s Large Language Model, the answers are highly accurate.
This is particularly useful when you are offering in-the-moment advice during a real-time messaging conversation.
Instead of having to take time to look through the knowledge base, financial advisors can search for information instantly. It works much like a chatbot sidekick, except that the advisors are able to check and edit the advice before sending it to the client.
More efficient advisors
Perhaps the most critical role that AI plays in wealth management firms is driving efficiency. With AI, advisors can get swift access to real-time financial advice, whether through AI-driven chatbots, advisory models, more efficient risk-management strategies or more.
The cumulative effect of AI when properly implemented can result in substantial efficiency gains. Our own statistics found that simply adding AI-enhanced texting and messaging services can improve advisor efficiency by 25%.
Another source found that “77% of wealth management firms see significant improvements in decision-making through predictive analytics to leverage real-time insights to better anticipate client demands and optimize their strategies.”
Proactive outreach
According to Accenture, 39% of clients want to hear from their advisors proactively. The reverse should also be true – clients should want to make more of an effort to make contact with their clients. The frequency of client interactions has been shown to have substantial, wide-ranging benefits for advisors, boosting everything from trust to driving AUM growth.
A mix of Generative AI and internal organization can make it easier for wealth managers to carry out proactive outreach.
By labeling current or potential clients according to needs, interests, or other factors, advisors can then send out messages – created by Generative AI and edited by the advisor – to the right people with minimal effort.
Quality client engagement
The frequency of interactions and improved organization means little if the advisor doesn’t have quality advice or financial products to share with the client.
AI can help in this area too, offering a broader range of hyper-personalized advice or product recommendations based on a mixture of market trends alongside the individual’s behavior, portfolio performance, and other life events.
Beyond offering deep insights, the tools can achieve a high level of sophistication when it comes to financial planning and other client services, empowering advisors to fine tune their strategies more efficiently. The subtlety of the new tools is particularly impressive, as the complexity of insights generated by AI have been historically too high to apply for advisors. In total, 55% of advisors claimed the predictive insights were too obtuse to be applicable. Now, with access to more advanced technology, advisors can spend 58% of their time on client-facing work.
Enhanced communication
Greater outreach efforts will, if done well, lead to more contact with the clients. And that means more meetings. Accenture claims that 28% of clients actually said that they would like more meetings with their wealth managers than they currently have. And AI is making the process easier than ever before.
How can it help?
Client mood. Imagine you are taking over a client from a colleague and want to know how to approach the meeting. Based on previous interactions and client feedback, the advisor can look at the Agent Desk to get an AI-generated client satisfaction score to see the best way to proceed.
Language gap. If your client speaks a different language from you, AI can help with real-time translated captions to ensure the conversation moves forward.
Meeting notes. After a call with the client, you can get access to automatically generated meeting notes that you can edit and search through at a later date.
Conversation summaries. Advisors can get access to a short AI-generated summary of what was discussed – which is particularly useful for long meetings.
Unresolved tasks. Something came up in the meeting? The AI can detect when there are tasks that need to be completed later, and automatically generates a to-do.
Overcoming challenges with Generative AI
Whether ChatGPT, Gemini, or the new Chinese AI DeepSeek, there are undoubtedly concerns surrounding the use of this technology.
Security and privacy
The chief challenges are often associated with security and privacy issues. And this is unsurprising. A Forrester survey found that executives in the banking sector consider security to be the largest obstacle to digital transformation and 4% of financial security leaders experience at least one ransomware attack within a year period.
This should be top of mind for any financial services institution without being a roadblock to progress. In a wealth management context, the tools should be employed as part of an overall company strategy – with failsafes built into the plan as approved by the security team. What we want to avoid is advisors using Generative AI tools on their own without prior approval, as this can lead to data leaks or other problems.
Wealth management and the AI Act
Another common challenge in wealth management is the issue of regulation. When legal frameworks come into force, particularly at a European level, there is often a perception that it will stifle innovation. TheAI Act, however, which was introduced in June, 2024, makes a concerted effort to ensure that the opposite is true.
The Act not only seeks to lay “down harmonized rules on artificial intelligence and amend” previous regulations relating to AI but to do so following “future-proof approach, allowing rules to adapt to technological change.”
This approach actually represents a strong strategic advantage for the financial sector, which the Act makes heavy reference to compared to other industries. The legislators wanted to avoid the need to duplicate work, particularly in well-regulated industries like finance, meaning that existing regulations can be applied.
Of course, there may be gaps and proper due diligence is always required to ensure adherence to the laws – but it’s more a matter of editing current processes rather than reinventing the wheel.
How should firms implement AI?
The general concept is that AI should serve humans, rather than the other way around. This means active human participation. For this reason, many of the boundaries surrounding AI from the Act focus on transparency.
But this also works to the advantage of the wealth management industry, where the focus is on the relationship between human intelligence and artificial intelligence combined, rather than one over the other.
Having human oversight on all AI tools can help with transparency, while also minimizing the risks commonly associated with the technology.
Managing risk with AI
Potential risks will always be present in the wealth management industry, particularly when AI is involved. And yet, there is no reason for it to stifle innovation. The best way to approach risk management with AI is to ensure that it is always built into human-centric processes with high levels of oversight, while also improving efficiency.
Take for example client investment portfolios. AI-powered tools on their own should not be used to make informed decisions regarding portfolios – but it’s a wonderful advanced tool to help manage them. Advisors and asset managers can set a number of predefined rules, depending on each client’s personal preferences, risk tolerance, and more. The advisor or asset manager can then review the recommendations to determine the best course of action for the client.
In fact, one of the use cases where advisors and asset managers perceive the greatest potential impact is with alpha generation, which seeks to gain higher returns without additional risk.
The way is clear – it’s time to embrace AI in wealth management
For almost a decade, heavily regulated sectors were reluctant to use cloud technology. This wasn’t because of the technology itself or concerns with data storage. It was because the legislation took a long time to be developed and organizations couldn’t predict what they could or couldn’t do.
With the AI Act, it’s clear that the EU is doing everything it can to encourage innovation in this area, and wealth management firms should embrace its potential. It does put down boundaries and other legislation – such as the proposed AI liability directive – will present challenges, but overall this is exciting news for the industry.
When it comes to improving operational efficiency, client interaction, or client engagement, the use cases surrounding AI are strong now and will only get stronger. They can already improve agent productivity while dramatically enhancing the client experience.
Many organizations are seeing this opportunity and are jumping at the chance to take advantage, defining the future of wealth management and the financial sector as they do. Those who hold back because of fear or indecision will find it difficult to reach the same levels of productivity and business growth.
Tomorrow may be too late. Now is the time to embrace AI.
Interested in finding out more?
